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M.A., University of Delhi, India, 1999 M.S., Kansas State

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1. 44 Figure 23 KeyObjectPackage 45 Figure 24 Class diagram of GooglePackage 48 iii Figure 25 Sequence diagram for GooglePackage 49 Figure 26 TeomaPackage 57 Figure 27 Sequence Diagram for TeomaPackage 58 Figure 28 AgentKeyPackage 65 Figure 29 ProducerPackage 72 Figure 30 AgentProducer Sequence Diagram 74 Figure 31 ManagerPackage 79 Figure 32 ManagerPackage Sequence Diagram 80 Figure 33 User Interface 103 Figure 34 Conducting Search Without Preference 105 Figure 35 Conducting Search With Preferences 107 Figure 36 Results Page After Clicking DisplayResult Button 108 Figure 37 Installing Macros
2. 110 Figure 38 Installing Macros 2 110 Figure 39 Installing Macros 3 111 Figure 40 Installing Macros 4 112 Figure 41 Installing Macros 5 113 Figure 42 Phase 1 Break down 119 Figure 43 Phase 2 Breakdown 119 Figure 44 Phase 3 Breakdown 120 iv CHAPTER 1 VISION DOCUMENT Introduction Motivation Writing articles is an important part of work for a researcher at a university or a content provider working for a media company While writing research or news articles the author often conducts searches on the World Wide Web WWW and dig out relevant information that can be used to write the article However when an author is writing an article it is often a distraction to stop writing visit a few search engines conduct keyword searches retrieve relevant information and then use them in the article This is not a very efficient especially when the author in writing an article under a deadline The motivation of the Multi Agent Research Tool MART is to develop a
3. name String prank int Wnhooftime int RawResult from KeyObjectPackage Key Object 8getName String SgetRank int WMgetFrequency int WSsetRank r int void WsetFrequency f int void SsetName n String void SKeyObject name String rank int nooftime int Bresult String Bid int Pagent_name String SRawResult result String WsetResult r String void 8getResult String Wgetld int Wsetld i int void 8getName String setName n String void Figure 23 KeyObjectPackage 45 KeyObjectPackage Class Documentation KeyObjectPackage KeyObject Class Reference Public Member Functions e KeyObject String name int rank int nooftime e String getName e int getRank e int getFrequency e void setRank int r e void setFrequency int f e void setName String n Public Attributes e String name e int rank e int nooftime Detailed Description This is a data object used by all the agents The documentation for this class was generated from the following file e KeyObject java 46 KeyObjectPackage RawResult Class Reference Public Member Functions e RawResult String result e void setResult String r e String getResult e int getId e void setId int i e String getName e void setName String n Package Attributes e String result e intid e String age
4. button 8 Invalid AgentTeoma java Port number Error message Agent port number already taken by does not start some other service 9 Invalid AgentProducer java Port number Error message Agent port number already taken by Producer does not some other start service Test id 1 Typing in Word After integrating the macro buttons for MART inside MS Word the developer tested if typing in Word was still possible and if all the features still worked after MART was completely installed and running The developer found that MS Word continued to work without any errors and or change in existing configurations Test id 2 Search When the user types out some words inside a document in MS Word and or in the keywords field after pressing the FilteredSearch Result a file called final_result html gets created at the specified folder The developer found that some of the keywords that were inputted by the user are also found in the search results This was one of the properties that needed to be true all the time and was validated using a USE model in phase 2 of the project Test id 3 Display result When the search has been conducted and there are no error messages and the user presses the DiplayResult button in MS Word Internet Explorer browser opens up and the result file final_result html is displayed in it If the user clicks on one of the URLs in the document he she is taken to that website inside the same 99 brows
5. TEST PLAN Test plan identifier MSE V1 0 Introduction The purpose of this document is to outline the plan for testing the critical use cases and all functionalities of the Multi Agent Research Tool MART software The document will also describe the activities related to testing the software and the environment and tools that will be used to test the software The following documents will be used for reference Vision Document sections 3 1 and 3 2 describing Software Requirements Specification Software Quality Assurance Plan SQAP Test items The following items of the MART software will be tested The test will be performed after the second presentation and when the coding is complete The following item of the MART software will be tested The critical use cases Features to be tested The following features of the MART software will be tested The description of each feature is described in the corresponding sections of the Vision document Type article in MS Word Section 3 3 1 in Vision Document Search for research material Section 3 3 2 of Vision Document Display research material Section 3 2 3 of Vision Document Features not to be tested Not applicable since all features will be tested 93 Approach The developer will use the specific requirements part of the vision document to test the above mentioned features of the MART software Type article in MS Word The tester should be able to install the provided macro in MS Wor
6. KeyObject trun Hwrite recelveMessage rawResults RawResult IManagerPackage rankKeywords_AgentManager_ janagerPackage readUserPreferences_AgentManager_ 1 rankKeyMangerAgentManager c 1 i 1 readPrefConvManager 1 searchTheWebConvGoggie ManagerPackage AgentManager keyfile KeyObject searchTheWebAgentGoogle rawresult RawResult finalresult RawResult coglePackage searchTheWeb_AgentGoogle_R readPrefAgentManager genResultsAgentManager 1 searchTheWebManagerConv ManagerPackage searchTheWeb_AgentManager_ getKeywords unrankedKeywords searchTheWebManager janagerPackage generateResults_AgentManager_ ProducerPackage generateResults_AgentProducer_R RECON zguggerResultAgentProducer ProducerPackage AgentProducer finalResult RawResult tun write teceiveMessage finalResultFile RawResult genResultsConvManager 1 eomaPackage searchTheWeb_AgentTeoma_R searchTheWebConvTeoma searchTheWebAgentTeoma 1 RawResult trawResults RawResult Figure 13 Object diagram The object model shows each and every class of the software and the associations 30 between them The packages afit and KeyObjectPackage are accessible to all the other packages in the system The KeyObjectPackage hold the classes that store the keywords and the final resu
7. void ite String 5 void recelveMassage Sockel server ObjectinputStream Input ObjectOutputStream output void ProducerPackage finalResultFile serawfile controller prawfile conv_f_generateResults Object controller Object raw ile void rreadRawFile Object rawfie object l generateHtmi Object rawfile object serializeFile Object rawfile object prun TeomaPackage rawResults feomaPackage makeRawResults seraufile serawfle Falla rari conv Search Thelen Object controler Obje Keywords vod serialize Object rawfile void run void erun void Figure 12 Classes generated after transformation with components Object Model When AgentTool generated code using newAgentMom it made separate 29 classes for each component The object model for the code generated is shown in Figure13 However since it is simpler to have components as separate methods in the agents the object model was redesigned as shown Figure 14 Packages afit and KeyObjectPackage A is accessible to all other packages in the system KeyObjectPackage a Aa jentKeyPackage Agent Ao Paha AGSONrY readPrefAgentKey keys KeyObject rankKeywordsConvKey Agent KeyPackage rankKeywords_AgentKey_R AgentKeyPackage readUserPreferences_AgentKey_R readPrefConvKey GooglePackage AgentGoogle awfile KeyObject serawflle
8. BreceiveMessage sener java net Socket input java io ObjectInputStream output java io ObjectOutputStream void Bsearch keyfile Object Object Bserialize rawfile Object Object MulticastSend Bmain args String void amp from GooglePackage DEST PORT int SMCAST_ADDR String Byparentport int Mja int BMulticastSend port int id int Brun void Parent searchTheWeb_AgentGoogle_R from GooglePackage ko java util Vector searchTheWeb_AgentGoogle_R s java net Socket i java io ObjectinputStream o java io ObjectOutputStream a GooglePackage AgentGoogle m1 afit mom Message Srun void Figure 24 Class diagram for GooglePackage 48 Google Broadcaster eS 4 uticastsendi ni EEEa p a ConversationThread searchTheWeb AgentGoogle R 2 searchTheWeb_AgentGoogle_R java net Socket java io ObjectInputStream java io ObjectOutputStream GooglePackage AgentGoogle afit mom Message GoogleCrawer Crawler 3 Crawler 4 run 5 search Object lt Object 6 doSearch String gt 7 serialize Object lt Figure 25 Sequence diagram for GooglePackage 49 GooglePackage Class Documentation GooglePackage AgentGoogle Class Reference Public Member Functions e AgentGoogle String n i
9. Sleuth AgentKey Keywords reader Keywords ranker serPreferences AgentManager Controller parchThevWeb AgentTeoma Sleuth generateResults AgentProducer Result producer Figure 10 Agent Template diagram 27 Deployment diagram The following diagram shows that since the agents are independent entities they can be placed on different systems machines or networks and yet talk to each other using pre defined conversations The following diagram also shows that for the current version of the software the AgentManager and AgentKey will be on the same machine as the one which has the Microsoft Word running on it This is because both the AgentManager and the AgentKey need to have access to the file that the user is typing the article on Agent Boss Google sleuth AgentManager AgentGoogle Agent keymaker Agent Result Generator Agentkey AgentProducer Teoma Sleuth AgentTeoma Figure 11 Deployment diagram 28 afit Packages afit and KeyObjectPackage is accessible to all other packages in the system AgentKeyPackage rankedKeywords keywords controller rank showKeywordsAgentKay AgentKayPackage AgentKey keys KeyObject owKeywords_Comp showKeywords ankedKeywords Comp rankKeywords_AgentKay R nun void te String s void receiveMessaga Socket server ObjectinputStream input ObjectOutputStrea
10. research tool that helps the author to research while writing an article and save valuable time This means that the research tool should not only be smart and efficient in conducting searches it should also be able to work in the background fairly independently and at the same time be non intrusive to the user Moreover since the Internet has now become a very common commodity and it is assumed that a person using MART has access to the Internet it would be further more useful if the research tool could use distributed computing to retrieve research material and present them to the user whenever he she decides to view or use them MART is intended to be such a tool Multi Agent Systems Multi Agent Systems are one of the recent programming paradigms used to build intelligent software agents An intelligent agent can be defined as some object that is fairly autonomous goal driven pro active and reactive This means that intelligent agents should be able to inhabit an environment and not only should they be capable of responding to external stimuli they should be fairly independent and have an end result in their mind while going about doing small set of activities There are several methodologies for building Multi Agent systems such as Gaia Societies in Open and Distributed Agent SODA Methodology for Engineering Systems of Software Agents MESSAGE and Multi Agent Software Engineering MaSE MART will be built in the multi
11. AgentTeoma m1 afit mom Message Brun wid Figure 26 TeomaPackage 57 Teoma Broadcaster Conversation AgentTeoma Multicast Send t in MulticastSend searchTheWeb AgentTeoma R earchTheWeb_AgentTeoma_R lava net Socket E java io ObjectOutputStream TeomaPackage AgentTeoma afit mom Message gt 3 runt gt 4 search Object lt 5 serialize Object lt Figure 27 Sequence diagram for TeomaPackage 58 TeomaPackage Class Documentation TeomaPackage AgentTeoma Class Reference Public Member Functions e AgentTeoma String n int p int id e void run e void write String s e void receiveMessage Socket server ObjectInputStream input ObjectOutputStream output e Object search Object keyfile e Object serialize Object rawfile Static Public Member Functions e void main String args Package Attributes e intp e intid 59 Detailed Description AgentTeoma crawls on a search engine and returns with the search results automatically generated by agentTool agentMom transform ver 0 4 Constructor amp Destructor Documentation TeomaPackage AgentTeoma AgentTeoma String n int p int id inline Constructor for agent Note Agent tool has a bug which is why the developer has to manually create and start an instance of MessageHandler inside the Agent constructor The co
12. String name e String machine_name e intid e int port Detailed Description This is a simple class to store an agent discovered by MulticastReceiver This class stores the agent s name id port number and has simple get and set methods for all the above attributes The documentation for this class was generated from the following file e RunningAgent java 86 ManagerPackage searchTheWeb_AgentManager_I Class Reference Public Member Functions e searchTheWeb_AgentManager I AgentManager a String hostName int portNum Object keyfile_in e void run Package Attributes e AgentManager parent e Object keyfile Detailed Description Conversation class for searchTheWeb_AgentManager_I automatically generated by agentTool agentMom transform ver 0 4 This class starts a conversation with AgentGoogles and AgentTeomas 87 Constructor amp Destructor Documentation ManagerPackage searchTheWeb_AgentManager_I searchTheWeb_AgentManage r_I AgentManager a String hostName int portNum Object keyfile_in inline Constructor for searchTheWeb_AgentManager I automatically generated by agentTool agentMom transform ver 0 4 Member Function Documentation void ManagerPackage searchTheWeb_AgentManager_I run inline Conversation run method controls conversation automatically generated by agentTool agentMom transform ver 0 4 It sends the Vector of KeyObjects and gets back a RawResult object fr
13. The phase would also involve development of a user manual that would describe how to install and run the final software A test report will also be developed that would outline how the tests were conducted and what were the results from the tests An evaluation report will also be written during this phase that would give a brief evaluation of the entire project The phase will be considered over once the committee members approve the final 13 version of the software demonstrated during the third and the last presentation and the set of documentation mentioned above with or without changes 7 oo oo oe EREEREER EEEE a e a S oo e a E E A A a OO a A T OA e E T DETE E a OEE a a A OE a E errr Figure 4 Gannt Chart 14 Cost Estimate Function point analysis Type Simple Average Complex Total Inputs 1 Entire Word 6 file being typed by user Outputs 1 Comments l Search 13 2 Error results in an Messages HTML Page Inquiries l Search 6 Keywords Files 1 Results file 20 HTML 2 Text file of relevant keywords Interfaces 1 Microsoft 10 Word A Internet Explorer Total 55 COCOMO Since COCOMO II is used mostly for large development teams Constructive Cost Model COCOMO originally developed by Barry Boehm will be used to estimate total cost of the project in terms of effort and time The estimation will be based on the assumption that the MS
14. are being built into agentTool next version and eagerly awaits its release Usefulness of reviews The reviews helped the project move in a tightly regimented process which is similar to the process of building software in a commercial setting The reviews also helped the developer in getting valuable feedback from committee members on how to smooth the edges of the final product and ensure that the product is actually usable to the end user Product quality The developer believes that given the project and deadline constraints the final product is fairly efficient and bug free However the product could still be improved on two counts First the Sleuth agents could be made faster by cutting down communication overheads and also by exploiting result caching on the user s machine Second the final result page could be refined further so that the search results are more relevant to what the user types in the MS Word document The ranking of keywords could also be refined further to make the process of making keywords more efficient 121 REFERENCES IEEE Std 829 1983 IEEE Standard for Software Test Documentation 1983 Edition IEEE 1983 IEEE Std 828 1998 IEEE Standard for Software Configuration Management Plans 1998 Edition IEEE 1998 IEEE Std 730 1998 IEEE Standard for Software Quality Assurance Plans 1998 Edition IEEE 1998 IEEE Std 730 1 1995 IEEE Guide for Software Quality Assurance Planning 1995 E
15. are in windows If you are on a Linux machine simply run the AgentGoogle sh file You will now be prompted for the number of instances of AgentGoogle you want to run When you type in the number of instances of AgentGoogle you want to run you will be prompted for port numbers that the Agents should run on Type the port numbers that are not in use by any other services on the computer Running AgentTeoma Descend into the directory where TeomaPackage directory is installed and double click on AgentTeoma bat file if you are in windows If you are on a Linux machine simply run the AgentTeoma sh file You will be prompted for the number of instances of AgentTeoma you want to run When you type in the number of instances of AgentTeoma you want to run you will be prompted for port numbers that the Agents should run on Type the port numbers that are not in use by any other services and or agents on the computer Running AgentProducer Descend into the directory where ProducerPackage directory is installed and double click on the AgentProducer bat file if you are in Windows If you are on a Linux machine simply run the AgentProducer sh file 104 Conducting Searches Click on Search macro button from the MS Word and continue typing your article You will see a new DOS prompt window open up and some messages When the final result page has been created the DOS prompt window will go away on its own You can continue typing in MS Word by mini
16. do not type http prefix in the website text field 106 Smith er 7 __ Click this button to OREBE 0 Bh seach G Aterese Ont BB 1E 515 HE O 2 A Odepayrenit TE Oi apga aaeoa ey yea Seve a Meee ay ang agus user ig t t t Figure 35 Conducting search with preferences 107 Viewing search results When you are ready to view the results simply click on the DisplayResult macro button and Internet Explorer will open up with the final results file displayed in it You can click on any one of the links to navigate to the relevant websites BG T 100 2 Search Fiteredsearch EO An SOisplayResut Fie Edt View Favorites Toos Help Q O DAG Poe Yorn Gun O BS o WKS Address E C Documents and Settings Madhukar Kumar Desktop Madhukar Mad is nse lpresentation3 codesepts fnal_resuit htmi Here are the results Google Result URL http www navwy com pdds pangram html DESCRIPTION The quick brown fox jumps over a lazy dog Prized waxy jonquils choke big farm vats A quick brown fox jumps over the lazy dog Google Result URL http raph levien com screenshots waterfall pdf DESCRIPTION 22 The quick brown fox jumps over the lazy dog 24 The quick brown fox jumps over the lazy dog 22 The quick brown fox jumps over the lazy dog Google Result URL http i iyi j DESCRIPTION AL Fal 2002 Spring 2003 Aba
17. invoked by the rawResults task of the Sleuth once it receives the searchTheWeb request from the controller 25 Keywords reader Sleuth 14 1 1 24 ee ee showKeywo rds readUserPreferences Para makeRaw tawResults 222 makeRawResults Bees patel Bats search eb a Keywords ranker getkeywords i r ee S search A EN Controller a A O rankKeywords r eg nrankedKeyword 1 4 eedan SS A T makeFinalResull gen rateResult Pa Pe finalResultFile K Result producer 131 132 1 3 3 Figure 9 Role Diagram Agent Template diagram The agent template diagram shows that the current version of the software MART has five different agents namely AgentManager AgentKey AgentProducer AgentGoogle and AgentTeoma The red lines connecting between the agents represent the conversations that are initiated between the agents For example searchTheWeb is a conversation that is initiated by AgentManager and it requests the sleuth agents AgentGoogle and AgentTeoma to conduct a search and return the raw results The different agents in the following diagram represent independent entities with their own separate main methods These agents could be placed on different machines and still be able to talk to each other using the conversations defined in the system 26 AgentGoogle
18. m1 inline Constructor for generateResults AgentProducer_R merely initializes all the variables automatically generated by agentTool agentMom transform ver 0 4 Member Function Documentation void ProducerPackage generateResults AgentProducer_R run inline Conversation run method controls the actual conversation This method calls Agent Producer s readRawFile and generateHtml method and returns the final result to AgentManager automatically generated by agentTool agentMom transform ver 0 4 76 The documentation for this class was generated from the generateResults AgentProducer_R java ProducerPackage MulticastSend Class Reference Public Member Functions e MiulticastSend int port int id throws Exception e void run Package Attributes e int DEST_PORT e String MCAST_ADDR e int parentport e intid e JInetAddress thismachine following file Detailed Description This class is identical to the MulticastSend class of GooglePackage Please refer to the GooglePackage documentation The documentation for this class was generated from the following file MulticastSend java Manager Package 77 The ManagerPackage acts as the main controller of the system and has the following five main classes as shown in the figure below When AgentManager gets started it creates a new instance of MulticastReceive MulticastReceive joins a predefined multicast address and finds out how many A
19. nooftime record the ranking of the keyword as compared to the other keywords and the frequency with which it appears in the typed article respectively The RawResult class is also a simple object that holds XML html string in its main attribute called result KeyObject name string rank int nooftime int getName string RawResult result string getRank int getFrequency int setName in name string setRank in rank int setFrequency in nooftime int Figure 15 The KeyObjectPackage 32 AgentKeyPackage AgentKeyPackage has three classes the AgentKey rankKeywords AgentKey_R and readUserPreferences AgentKey R The AgentKey is the main class of the package and has the main method as well as methods to read user keywords and rank keywords When AgentKey receives a message from AgentManager it does not respond to message from any other class it creates the instances of conversation responder class based on the kind of message The responder classes then invoke the methods that actually reads user inputted keywords and ranks them keys KeyObject rankedKeywords KeyObject showKeywords KeyObject recelveMessage readPrefAgentKey rankKeywordsAgentKey rankKeywordsConvKey ankKeywords_AgentKey_R readPrefConvKey eadUserPreferences_AgentKey_R Figure 16 AgentKey package 33 GooglePackage Go
20. see whether some field is non empty Finally it collects the input and calls the forNewPref method in the AgentManager The forNewPref method calls the search make results etc The documentation for this class was generated from the following file NewPref java AgentKeyPackage UserPref Class Reference Public Member Functions UserPref e String getSite e String getKeywords e String getFileFormat e void actionPerformed ActionEvent e Static Public Member Functions e void main String args 69 Detailed Description UserPref displays a frame to the user and gets preferences If the user clicks on the OK button the class NewPref handles the event Constructor amp Destructor Documentation AgentKeyPackage UserPref UserPref inline Constructor creates a frame and waits for an event Member Function Documentation void AgentKeyPackage UserPref actionPerformed ActionEvent e inline This method handles Cancel button Graceful exit String AgentKeyPackage UserPref getFileFormat inline This method merely extracts what the user typed in the fileformat textfield String AgentKeyPackage UserPref getKeywords inline This method merely extracts what the user typed in the keywords textfield String AgentKeyPackage UserPref getSite inline This method merely extracts what the user typed in the site textfield 70 void AgentKeyPackage UserPref main String
21. some scenarios it stopped working in other scenarios without throwing any errors Three lessons were learnt from this problem First multicasting can work only on a single network To make multicasting work across networks the developer needs to have access to the routers so that they can be enabled to carry forward the multicasting packets Second to make multicasting work on a Windows machine the computer has to be connected to the Internet Multicasting will not work on a Windows machine if a cable or wireless card is disconnected The Windows native Firewall also has to be either switched off or configured to allow packets transmission of certain port numbers to make multicasting work on the machine Finally if the developer is trying to send and receive multicasting packets on a Linux machine he she has to ensure the machines are configured not to drop multicasting packets Debugging As the system grew in size it became incredibly hard to trace bugs since MART is a multi agent system and the agents were behaving as independent systems running on 115 different machines The lesson learnt from this problem was that with each increment the whole system should be compiled and tested before moving on to the next increment This is time consuming but useful in debugging parallel programs interacting with each other Numbers of lines of code The original estimate of the number of lines of code for MART was based on the develop
22. started and tried to contact the Sleuth Agents with an empty string as keywords This is not desirable so the developer made changes to the UserPref class and now if the user does not fill out all three of the fields then he she will get an error message Not a valid input and the system will exit The user has to 100 complete at least one field in the dialog box to start the AgentManager If the user does not type any keywords the system will extract keywords that have already been typed in the MS word article Test id 6 Invalid port number When the user starts the AgentGoogle class he she is prompted for the number of instances of the Agent that the user wants to start followed by the port numbers that those Agents should listen on These port numbers have to be free and not taken by another service already running on the server For example port numbers 0 to 1024 are taken by known services and several port numbers from 1024 to 7000 have been registered If the user tries to use one of the above mentioned port numbers he she will get a message Bad port number given to Listener constructor for agent AgentGoogle and the program will stop To give a valid port number the user should try any number between 7000 and 65000 Test id 7 No keywords inputted by user When the user does not type anything in an open document in MS Word and or also does not type any keywords from the FilteredSearch dialog the AgentGoogle and Agent
23. the whole distributed system 1 Produce Search Results 1 1 Refine and rank 1 2 Search search keywords the Web pn 1 1 2 Rankall 1 1 1 Read keywords 1 2 1 Search 1 3 1 Read raw 1 3 2 Refine 1 3 3 Produce final keywords and preferences Website results results results file inputted by user and from typed article r 1 4 Manage the system 1 3 Produce Results Figure 5 Goals of the system The rank and refine search keywords role is also partitioned and is divided into reading user inputted keywords and in ranking the keywords for search The search role is also partitioned and for the current version consists only of 21 searching websites In future versions another role could be added into it that would also conduct searches on database located on the host computer and or local network The role produce results is partitioned into creating raw results refining the results and producing the final result Use Cases There are three primary use cases for the entire system namely Read User Preferences Search the Web and Generate Results Read User Preferences In this sequence diagram the manager sends a message to the Keyword reader to read the user inputted keywords and preferences The manager then takes this object and sends it to the Keyword ranker with a request to rank a
24. 4 The documentation for this class was generated from the following file e generateResults AgentManager_I java ManagerPackage MulticastReceive Class Reference Public Member Functions e MulticastReceive e void run e String getName String m e int getId String m e int getPort String m e boolean checkExistence String n int x int y 82 e Vector getRunningAgents e void printVector Package Attributes e int BUFFER_LENGTH e int DEST_PORT e String MCAST_ADDR e intx 0 e inty 0 e Vector running agents e boolean check Detailed Description This class is responsible for finding out how many Sleuth agents and AgentProducer is running and what are their port numbers The class creats a RunningAgent object for each Agent that it discovers and adds them to a Vector This Vector is finally sent back to AgentManager 83 Constructor amp Destructor Documentation ManagerPackage MulticastReceive MulticastReceive inline The constructor sets the multicast address to 225 4 5 6 since this and port 5000 since this is the combination used by the MulticastSenders to broadcast their messages Member Function Documentation boolean ManagerPackage MulticastReceive checkExistence String n int x int y inline This method is also used by runQ It checks to see if an agent is already stored in the vector If not then add it to vector otherwise ignore do nothing int ManagerPa
25. BUILDING MULTI AGENT RESEARCH TOOL MART USING AGENT ORIENTED SOFTWARE ENGINEERING AOSE AND AGENT TOOL by MADHUKAR KUMAR B A Hons University of Delhi India 1995 M A University of Delhi India 1999 M S Kansas State University 2003 A REPORT Submitted in partial fulfillment of the requirements for the degree MASTER OF SOFTWARE ENGINEERING Department of Computing and Information Sciences College of Engineering Kansas State University Manhattan Kansas 2003 Approved by Major Professor Dr Scott A DeLoach ABSTRACT Multi Agent Research Tool MART is a multi agent system that helps a researcher author in writing an article by automatically searching and dynamically generating links while an article is being typed in Microsoft Word The project built over a period of approximately ten months is implemented in Java agentTool was used to develop the analysis and design of the system The critical properties of the system were modeled in USE and OCL The system consists of several fairly independent agents that can be placed and executed on any machine on a local network The main agent is triggered when the user clicks a button from MS Word which in turn finds other agents establishes connection with them requests them to do a search with given keywords and then collects the result and makes an html page on the user s computer When the user clicks on another button in MS Word the final results page is dis
26. Bx int 0 int 0 unning_agents java util Vector Becheck boolean generateResults_AgentManager_ from ManagerPackage Bserawfile Object Bruni BgenerateResults_AgentManager_I parent BMulticastReceive parent searchTheWeb_AgentManager_ SorintVector gt from ManagerPackage Bokeyfile Object i Brn aa RunningAgent from ManagerPackage Y Bname String Bimachine_name String Bd int Boor int 8RunningAgent BoetPort Boetid jetName etPort etld BsetName S setMachine amp 8getMachine BsearchTheWeb_AgentManager_I Figure 31 ManagerPackage 79 Manager Receiver SearchGoogleandTeoma ResultGenerator AgentManager MulticastReceive searchTheWeb AgentManager generateResults AgentManager I 2 searchheWeb_AgentManager_I ManagerPackage AgentManager String int Object 1 MulticastReceive 3 generateResults_AgentManager_I ManagerPackage AgentManager String int Object Figure 32 ManagerPackage sequence diagram ManagerPackage Namespace Documentation KeyObjectPackage Namespace Reference Detailed Description This class is the Controller of the entire system It resides on the same machine on which MS Word is runni
27. ConvManager rankKeyMangerAgentManager keyfile KeyObject awresult RawResult finalresult RawResult readPrefAgentManager makeFinalResult search genResultsAgentManager getKeywords H unrankedKeywords searchTheWebManagerConv 1 searchTheWebManager genResultsConvManager generateResults_AgentManager_ searchTheWeb_AgentManager_ Figure 20 ManagerPackage 38 Formal Requirement Specification A model to test and formally specify a primary property of the MART system was developed The USE model has four different classes the most important being the AgentManager The AgentManager represents the AgentManager class from the system and has access to both the keywords that are generated from the user typed article and the results file created after a search has been conducted The KeyObject class in the USE model represents the KeyObject class of the KeyObjectPackage in the Object diagram The class has three attributes name rank and nooftime These attributes store the keyword itself the number of times the word appears in the user typed article and a corresponding rank based in comparison to the other keywords The RawResult class in the USE model represents the RawResult class in the KeyObjectPackage of the object diagram In actual implementation the entire result is stored as a string in the RawResult class However to show the property of the entire system that some of the original
28. E project is fairly uncomplicated and flexible and hence the organic mode will be used in the COCOMO model The equations used for COCOMO model is as follows Effort C1 EAF Size P1 LS Time C2 Effort P2 where Effort number of person months C1 constant scaling coefficient for effort C2 a constant scaling coefficient for schedule P1 an exponent that characterizes the economics of scale inherent in the process used to produce the end product P2 an exponent that characterizes the inherent inertia and parallelism in managing a software development effort EAF an effort adjustment factor that characterizes the domain personnel environment and tools used to produce the artifacts of the process Size size of the end product in human generated source code measured by the number of delivered source instructions Time total number of months Since we are assuming that the current project is in the Organic mode the following values will be used for the above mentioned equations Cl 3 2 C2 2 5 P 105 P2 0 38 Since the project has only one developer EAF is not applicable in this situation In the second phase once the code was generated from the design model and after the second executable prototype was built it was found that there are 17 classes instead of 9 as originally envisaged Since each class has approximately about 130 lines of code the total lines of code will be somewhere aroun
29. Mom transform ver 0 4 Object GooglePackage AgentGoogle search Object keyfile inline This method first casts the object it has received into a Vector It then extracts the KeyObjects and checks to see if there is a KeyObject with an id of 9999 or 8888 If 51 there is one KeyObject with and id of 9999 then the word attached to the object is a website filter that needs to be attached to the end of keywords If there is an Object with an id of 8888 then the word attached to it p or d is the filefilter for pdf or doc file The method then checks the current AgentGoogle s id If the current id is 1 then all keywords are extracted it the id is 2 then top 5 keywords are taken If the id is 3 then the top 3 keywords are taken If the id is greater than 3 then only the top most ranking keywords are taken Once the keywords and the filters are extracted they are appended to a string that is sent to Crawler s doSearch method Whatever doSearch returns is cast into a RawResult object and sent back to the caller of this method the conversation responder automatically generated by agentTool agentMom transform ver 0 4 void GooglePackage AgentGoogle write String s inline Write method used to write conversation error messages to output automatically generated by agentTool agentMom transform ver 0 4 The documentation for this class was generated from the following file e AgentGoogle java 52 GooglePackage Crawl
30. T PLAN Individual tasks breakdown Inception phase The inception phase would involve development of a prototype that would display the feasibility of the project and also give an idea to the users about how the final product will finally look and behave The phase will also involve the development of documentations that will be presented during the first presentation These documents would include a vision document that will outline the requirements and the functionalities of the product a project plan and a Software Quality Assurance SQA plan The requirements phase will be over once the committee approves the documents and the executable prototype after the first presentation with or without changes Elaboration Phase The inception phase would involve developing the overall architecture of the product using the agentTool The agentTool program will be used to develop the overall goals of the system MART the roles and the concurrent tasks Specific use cases inside the system will also be designed in this phase using the Agent Tool Finally an agent template will be developed that will outline the different agents and the way they will communicate with each other through conversations The conversations will also be verified using the Spin tool A Deployment plan also developed inside the Agent Tool will also be developed in this phase The design phase will also involve development of a second executable prototype that will be demonstrat
31. Teoma_ returned an NullPointerException This was corrected by adding code to the AgentManger Now when AgentManager asks AgentKey to read the keywords it checks whether it gets back a non null String means the user did type some words If the String returned by AgentKey is empty then the AgentManager outputs an error message Sorry no keywords inputted and then makes a graceful exit Test id 8 Invalid port number When the user starts the AgentTeoma class he she is prompted for the number of instances of the Agent that the user wants to start followed by the port numbers that those Agents should listen on These port numbers have to be free and not taken by another service already running on the server For example port 101 numbers 0 to 1024 are taken by known services and several port numbers from 1024 to 7000 have been registered If the user tries to use one of the above mentioned port numbers he she will get a message Bad port number given to Listener constructor for agent AgentGoogle and the program will stop To give a valid port number the user should try any number between 7000 and 65000 Test id 9 Invalid port number When the user starts the Agent Producer he she is prompted for the port number that the agent should run on If the port number is below 7000 then chances are that it already taken by some other service on that computer If the user types a port number that is already taken by some other serv
32. agent programming paradigm and it will use MaSE as the Agent Oriented System Engineering AOSE methodology to construct the system Multi Agent Software Engineering MaSE Of all the Agent Oriented Systems Engineering AOSE methodologies probably the simplest the most logical and the most elaborate is the Multi agent Systems Engineering MaSE methodology Like most of the other methodologies the MaSE methodology also has an analysis phase and a design phase The analysis phase yields goals use cases and roles of the overall system while the design phase results in the development of agent classes tasks and conversations To build an agent s system under the MaSE methodology a developer must use the agentTool that not only helps in designing the system but also generates the stub code of the entire system in Java Under MaSE the first step in the analysis phase is to break down the functional requirements of the overall system into a set of hierarchical goals These goals are primarily of four types summary partitioned combined and non functional Once the goals of the system have been identified the next step in the analysis phase is to apply use cases and to develop sequence diagrams At this state the aim is to develop as many event sequences of the system as possible without repeating any events The last step in the analysis phase is to develop roles and refine them from the goals and the sequence diagrams of the first two st
33. al requirements described under section 3 2 of the Vision document Each feature will be considered to be passed if it satisfies the corresponding requirement in the Vision document and failed if any or none of the behavioral expectations are met as described Suspension criteria and resumption requirements Suspension criteria If the user is unable to get any search results for an article after typing at least a paragraph then the testing will be suspended till the bug is traced and corrected While testing new versions or releases of the MART software testing will be suspended if any of the features of the previous release fails the test Resumption requirements Testing will be resumed if and when the search function works adequately and when the user is able to view some relevant results When testing for new releases the testing will resume when all previously passed features of the previous release is considered to be passed Test deliverables The following artifacts will be produced after the tests are conducted on the MART software Test Plan Assessment report Environmental needs This section will outline the necessary and desired properties needed for the test 95 environment Physical Characteristics System Software All tests will be performed using MS Word running under Windows XP or Windows 2000 Some of the agents will be tested while running under Unix or Linux platforms 96 CHAPTER 7 ASSESSMENT EVALUATION Tes
34. anager inv keysalsoinresult km keys name gt asSet gt intersection km resultfile resultword word gt asSet gt notEmpty If a word appears more number of times in the user inputted article its ranking will be higher 1 is higher than 2 than a word which appears lesser number of times in the article context key AgentManager 42 inv rankings key keys gt ForAll r s KeyObject s nooftime implies r rank lt s rank 43 ftime r noo l gt CHAPTER 4 COMPONENT DESIGN Overview of the system The overall system has seven major packages as shown in the diagram below Each package has several classes inside them and their roles and functions are discussed later afit ProducerPackage KeyObjectPackage KZ i i GooglePackage IN T Ag 7 N TeomaPackage Y V K AgentKeyPackage li ManagerPackage z Figure 22 Overview of the system KeyObjectPackage The KeyObjectPackage consists of the classes as shown in the next figure KeyObject is used to store individual keywords with their rank and the number of times it was found in the user typed article The RawResult object stores the result sent by sleuth agents It also stores the id of the agent that sent the RawResult object 44 KeyObject from KeyObjectPackage
35. and generateResults AgentProducer R The AgentProducer has a method called generateResult which creates the final HTML file and returns it to the AgentManager The responder class is used for conversation with the AgentManager AgentProducer finalResult RawResult genResultAgentProducer genResultConvProducer 1 generateResults_AgentProducer_R Figure 19 ProducerPackage 36 ManagerPackage ManagerPackage which acts as the controller for the whole system has several classes namely AgentManager readUserPreferences AgentManager I rankKeywords_ AgentManager_I searchTheWeb_AgentManager I and generateResults AgentManager_I The AgentManager creates instances of the conversation initiator classes when it has to get some job done from the other agents in the system At first it initiates a conversation with the KeyPackage and gets back the keywords typed in the user and also the search preferences It then initiates a conversation with the GooglePackage and TeomaPackage and requests them to conduct searches based on the keywords and preferences and return the raw results Once the raw results arrive the ManaagerPackage calls the ProducerPackage and requests it create a final result in HTML based on all the raw results The final result is then placed by the Manager in the same computer where the user is typing the article 37 lrankKeywords_AgentManager_ 1 rankKeyConvManger readPref
36. ank the words typed by the user using some algorithm Search constraint Some of the words typed by the user should be at least present in the final results page Use Case 3 Display research material Description The user should be able to click on a button somewhere in the MS Word menu that should immediately open a window of Internet Explorer browser that will have all links to web sites with information relevant to the current article being typed in MS Word Assumptions 1 The user has an internet connection when ever he she is using MART 2 Every agent knows the port numbers of the every other agent that they need to collaborate with Constraints 1 Since the Agent Tool generates stub code in Java the program will be developed in Java 2 The Google API only returns the first 10 search results per query 3 There is a limit to the number of searches a program can conduct every day using the Google API 10 Environment 1 The software package will be compiled using the JDK 1 4 0 2 agentTool will be used for the design and analysis part of building the system and to generate the stub code 3 IBM Visual Age will be used for coding the software package 4 USE 2 0 along with Object Constraint Language OCL will be used for formal specifications 5 The software package will be tested on Windows XP and the individual agents will be tested on Windows XP Red Hat Linux 9 0 and Unix Solaris 2 7 11 CHAPTER 2 PROJEC
37. args inline static Create a new instance of UserPref The documentation for this class was generated from the following file UserPref java ProducerPackage The ProducerPackage has three classes as shown in the following figure The MulticastSend object behaves identically to the one in the GooglePackage When AgentProducer receives a request for conversation it starts a conversation responder thread The conversation responder thread receives a Vector of RawResults which it passes on to AgentProducer The AgentProducer takes the Vector extracts the results and based on the ids of the agents that sent the result it produces a list of relevant results and wraps HTML around it It then sends the HTML wrapped String to the conversation responder which in turn sends back the final result to the AgentManager 71 AgentProducer from ProducerPackage Bp int Bigot_Vector java util Vector AgentProducer n String p int Brun wid Fwrite s String void BreceiveMessage sener java net Socket input java io ObjectInputStream output java io ObjectOutputStream void BreadRawFile rawile Object Object BoenerateHtml raw Object Object igenerateFinall String BXparseGoogle googleresult String out java io PrintWriter no_of extractions int void parseTeoma teomaresult String outfile2 java io PrintWriter no_of_extractions int void erializeFile rawfile Obj
38. b 24 Figure 8 Generate Results 25 Figure 9 Role Diagram 26 Figure 10 Agent Template Diagram 27 Figure 11 Deployment Diagram 28 Figure 12 Class Diagram after transformation with components 29 Figure 13 Object diagram 30 Figure 14 Component Diagram of Entire System 31 Figure 15 KeyObjectPackage 32 Figure 16 AgentKeyPackage 33 Figure 17 GooglePackage 34 Figure 18 TeomaPackage 35 Figure 19 ProducerPackage 36 Figure 20 ManagerPackage 38 Figure 21 USE Model 40 Figure 22 Overview of System
39. ckage MulticastReceive getId String m inline A simple method to extract the agentid from the string passed on to it as a parameter Returns an int This method is called by the run method String Manager Package MulticastReceive getName String m inline A simple method to extract the name from the string passed on to it as a parameter This method is called by the run method 84 int ManagerPackage MulticastReceive getPort String m inline A simple method to extract the agentid from the string passed on to it as a parameter Returns an int This method is called by the run method void Manager Package MulticastReceive printVector inline Debug method Please ignore void Manager Package MulticastReceive run inline This is where the thread polls on the classD address and each time it spots a unique MulticastSend message it extracts the agent name id and port numbers from it creates a RunningAgent object from it and inserts it into the Vecot called running agents The documentation for this class was generated from the following file MulticastReceive java ManagerPackage RunningAgent Class Reference Public Member Functions e RunningAgent String name int id int port e int getPort e int getId e String getName e void setPort int p e void setId int i e void setName String n e void setMachine String mac 85 e String getMachine Package Attributes e
40. d 2550 instead 16 of 1170 as originally estimated By plugging these numbers in the above two equations the following results are obtained Effort 3 2 2 500 1 05 8 4 person months earlier it was 4 9 months Time 2 5 8 4 0 38 7 9 months earlier it was 4 6 months Productivity 2500 7 9 316 LOC month earlier it was 330 LOC month Staff 8 4 7 9 1 person Earlier 1 person This means that the developer will require approximately eight months instead of four and a half months originally estimated to implement the project if about 316 lines of code are generated each month and if the coder works five days a week for eight hours every day It should be noted here that the developer may or may not be able to work for eight hours a day for five days a week only on the project since he is also expected to attend classes and do other school related work However keeping in mind that since there are no other team members in the development team and hence there are no overhead management costs in communication and coordination and the fact that the production phase is scheduled over see Gannt Chart the summer break the production may actually just finish in roughly eight months This means that the original date of finishing the project August 2003 will now move to sometime in the end of November 2003 Architecture elaboration plan The following tasks should be completed before the second presentation Revision of Vis
41. d and none of the preset preferences and page settings should change or stop working Search for research material The user should be able to click on the button on the menu bar that says Search and Save and that should automatically read all the relevant keywords already typed by the user in the article Once the search is complete without any errors a message should appear on the screen that the search was OK When the search is complete a file called keywords txt should be created in the My Documents folder of the computer Opening the file in any text editor should show all the keywords that were created by the MART software Display research material The user should be able to click on the button macro on the menu bar in MS Word and that should open up Internet Explorer with the displaying all relevant results The user should be able to click on links that will open the relevant websites in the same window Functional Requirements Testing All functional requirements will be tested against their requirements described under sections 3 2 of the Vision document Portability Testing The developer team will try and run some of the agents from a Unix Linux while running MS Word under Windows operating system Any installation or running 94 problems that are encountered will be recorded in the Test log document Item pass fail criteria The MART software must be able to pass the tests for all the critical uses cases and the function
42. designed from both the initiator as well as the responder s perspective These conversations are much like the state diagrams that have initial and end states A designer can also develop other states inside the responder and the initiator keeping in mind the previous tasks and roles and finally verify to see whether the conversations are deadlock free or not The verification is done by the Spin tool which is embedded inside the agentTool Another advantage of using MaSE is that while designing the individual agents it is totally up to the designer on what architecture to use for making the internal components of the agents It is here that Beliefs Desires and Intentions BDI architecture can be used to design the agent architecture or the designer can choose his her own architecture and make the components accordingly Finally the structure of an instance of the entire system can be developed using the deployment model in which several systems are designed the agents are placed in the systems from the list of agents and the agents are made to talk using conversations already developed from the previous step Project Overview Figure 1 Overview of MART The MSE project involves building the Multi Agent Research Tool MART software that will help researchers and authors to dynamically search for information and write articles Put simply MART is intended to be a software package that will be integrated with one of the most commonly
43. di MT Condensed Extra Bold The ack brown Paga jamps over the lazy dog abcdefghijkimnoparstuvwxyz ABCDEFGHUKLMNOPQRSTUVWXYZ Google Result URL http pages iweb DESCRIPTION Arial The quick brown fox j jumps over rm lazy dog abcdefghijkimnoparstivwxyz ABCDEFGHIIKLMNOPQRSTUVWXYZ 1234567890 _ 20 amp EQA Arial Black The quick Google Result URL Figure 36 Results page after clicking DisplayResult Suit 108 System Configuration Requirements The following are required to use MART 1 A Windows machine with MS word installed on it This will be referred to as the host machine 2 JDK 1 4 Gava installed on the host machine and the other machines that will be used to run agents 3 The ManagerPackage and KeyPackage should be installed and run from the host machine 4 All agents of MART are capable of running from either the host machine or from any other machine s with jdk1 4 installed on them located on the same network Installing Macros in MS Word To install the Macros in MS Word the user should perform the following steps 1 Unzip mart zip in your system root folder at c 2 Open MS Word 3 Navigate to mart folder and open mart dot 4 Click on Tool gt Macro gt Macros 109 Delete Macros in fan active templates and documents Cancel Description m created 10 9 2003 by Madhukar Kumar Figure 37 Installing Macros 1 5 Click on the Organizer button Styles Au
44. dition IEEE 1995 Java 1 4 API Pressman Roger S Software Engineering A Practitioner s Approach Fifth Edition Mc Graw Hill NY June 2001 Scott A DeLoach agentMom User s Manual July 2000 Scott A DeLoach Mark F Wood amp Clint H Sparkman Multi agent Systems Engineering The International Journal of Software Engineering and Knowledge Engineering Volume 11 no 3 June 2 122
45. e the project plan and the cost estimate were refined Using COCOMO the developer estimated that the actual lines of code would be around 2550 and not 1500 and hence the effort would actually be 8 4 months instead of 4 9 months estimated during the first phase This also meant that the time of development would now be 7 9 months instead of 4 6 months as derived in the first phase of development After the new effort and time of development was derived in the second phase the developer set the new final deadline to be on November 27 2003 as against Aug 2003 estimated during the first phase Since the implementation and the first phase of documentation finished by October 7 2003 the project actually finished ahead of schedule and the cost estimation in the second phase turned out to be fairly accurate Project Duration The following table details the expected time of finish for each phase and the actual finish time Expected Finish Time Actual Finish Time Phase 1 Feb 5 2003 Feb 4 2003 Phase 2 August 20 2003 August 28 2003 Phase 3 Nov 24 2003 Oct 31 2003 The following table details the break down of activities in each development phase 117 Phase 1 Spring Phase 2 Summer Phase 3 Fall 2003 2003 2003 Meetings 130 min 430 min 150 min Documentation 589 min 626 min 771 min Coding 230 min 189 min 1239 min Research 80 min 0 min 90 min Keeping Timelogs 74 min 30 min 95 min D
46. e Object generateHtml Object raw Static Public Member Functions e void main String args Package Attributes e intp e Vector got_Vector Detailed Description Class AgentProducer gets a vector of RawResults It filters out the result and returns a string that is written to a file by AgentManager and results in the final_result html file that is shown to the user automatically generated by agentTool agentMom transform ver 0 4 73 Constructor amp Destructor Documentation ProducerPackage AgentProducer AgentProducer String n int p inline Constructor for agent automatically generated by agentTool agentMom transform ver 0 4 Member Function Documentation Object ProducerPackage AgentProducer generateHtml Object raw inline Method generateHtml referenced in conversation is actually responsible for creating the final html string It takes all the RawResult objects one by one and sees if it was sent by Teoma or Google Agent Based on who sent the result the string is parsed by calling either parseGoogle or parseTeoma methods Finally it checks to see the id of the agents that sent the result and picks only certain amount of results and adds them to the final result string The html result string is finally cast into a serializable object before it is sent back automatically generated by agentTool agentMom transform ver 0 4 74 Object ProducerPackage AgentProducer readRawFile Object ra
47. e selectionSort method Once it receives the vector it reconverts the array to a vector adds the ranks and returns the vector String AgentKeyPackage AgentKey readFile inline This method merely reads the keywords txt file saved by the word Macro and returns everything as a string Object AgentKeyPackage AgentKey selectionSort Object r inline This is a reusable method It takes an array as a parameter and returns a sorted array to its called This method uses findLeast for its internal computation 67 String AgentKeyPackage AgentKey stripArticles String s inline This method takes a sting as a parameter It goes through the string and stips out all the irrelevant words that will not be used for ranking or searching The documentation for this class was generated from the following file AgentKey java AgentKeyPackage NewPref Class Reference Public Member Functions e NewPref UserPref my_view e void actionPerformed ActionEvent evt Detailed Description This class handles the OK button push action from the UserPref GUI class Constructor amp Destructor Documentation AgentKeyPackage NewPref NewPref UserPref my_view inline Constructor Does nothing 68 Member Function Documentation void AgentKeyPackage NewPref actionPerformed ActionEvent ev inline actionPerformed handles the OK button push event This method extracts the user input from the fields and checks to
48. ect Object Bmain args String void MulticastSend from ProducerPackage PRDEST PORT int RMCAST_ADDR String Bparentport int Ma int WwulticastSend port int id int Bun wid generateResults_AgentProducer_R from ProducerPackage oenerateResults_AgentProducer_R s java net Socket i java io ObjectinputStream o java io ObjectOutputStream a ProducerPackage AgentProducer m1 afi mom Message Brun void Figure 29 ProducerPackage Producer Broadcaster AgentProducer MulticastSend z MulticastSend int int Conversation generateResults AgentProducer_R 2 generateResults_AgentProducer_R java net Socket java io ObjectInputStream java io ObjectOutputStream ceil soh eb aes afit mom Message ET 3 readRawFile Object A 4 generateHtml Object lt 5 parseGoogle tring java io PrintWriter int l 6 parseTeoma Stting java io PrintWriter int l 7 generateFinal l Figure 30 AgentProducer sequence diagram 72 ProducerPackage Class Documentation ProducerPackage AgentProducer Class Reference Public Member Functions e AgentProducer String n int p e void run e void write String s e void receiveMessage Socket server ObjectInputStream input ObjectOutputStream output e Object readRawFile Object rawfile
49. ed during the second presentation in front of the committee members In the elaboration phase the vision document the project plan and the software quality assurance plan document will also be revised based on the feedback provided by 12 the committee members during the first presentation The design phase will be over once the committee members approve the second prototype and the design artifacts developed during this phase with or without changes Production Phase The production phase would involve generation of stub code from the agentTool design file MAML file and developing all the individual agents that would perform separate tasks This phase would also involve development of the user interface components and the search algorithm that will be incorporated in one of the agents Finally this phase would involve integration of all the agents and the individual components that will constitute the whole system Testing The testing phase would involve testing of all the requirements and the functionalities outlined in the vision document This phase would also include integration testing for the entire system Documentation The documentation phase would involve developing several artifacts that will submitted along with the final software at the end of the third presentation The documents would include the API web pages that would outline each and every java package with information about individual classes attributes and methods
50. em class AgentManager end Every instance of class KeyObject signifies a Single keyword read from a the User typed article from MS Word class KeyObject attributes name String rank Integer nooftime Integer end class RawResult end Every instance of ResultWord represents single words that are found in the RawResult file created by the Sleuth agent The RawResult file is created by the Sleuth agent after it has conducted the search In actual implementation RawResults will be one single flat file with several words String in it class ResultWord attributes word String end 41 ASSOCIATIONS Keys Manager has several keys attached to it association Keys between AgentManager 1 role manager KeyObject role keys end ResultWords RawResult has several ResultWord attached ECO EC association ResultWords between RawResult 1 role resultfile ResultWord role resultword end Result KeyManager is attached to several Result File because each sleuth agent generates one RawResult file association Result between AgentManager 1 role keymanager RawResult 1 role resultfile end gt CONSTRAINES constraints Some of the keywords in the KeyManager are also present in the RawResults Some of the keywords are also present in the RawResult context km AgentM
51. eps Usually the mapping of goals to roles is one to one in the sense that one goal maps to one role However closely related goals may be combined into a single role It is ultimately the overall system requirements and its characteristics that decide the goals use cases and roles After the roles are created tasks associated with each role that describe the role s behavior and that are required to achieve the goals associated are developed The role diagram is the first step in MaSE which defines the interactions between different tasks of different roles Here the tasks are also developed in the form of state diagrams These tasks are either transient or persistent These individual tasks are then developed in to their concurrent task models which have an initial state a termination state and transitions between the two and or other states The design phase in MaSE starts after all the roles and tasks have been defined Once this is done the first step in the design phase is now to develop agents by assigning them roles Since the roles reflect the overall goals of the system and can be manipulated modularly the authors refer to them as a bridge between the analysis and the design phase of this methodology It is up to the system designer on how many agents finally show up in the overall system and what roles each agents play Once the agents have been defined the designer should now connect the agents using conversations Each conversation is
52. er s earlier experience in developing a multi agent system using AgentTool The original estimate was 1500 lines of code during the first phase of development During the second phase the developer estimated that the actual lines of code could be near 2550 However the final size of the entire package turned out to be almost 3 000 lines of code The aberration in the original estimate and the actual lines of code in the final product was because the original estimate of 1500 lines of code was wrong due to developer s inexperience in estimating size during the first phase of the project During the second phase the developer estimated the final software to be around 2550 and this would have been fairly accurate but for the fact that a new requirement was added during second presentation multicasting Due to addition of some new classes which had not been taken into account in the second phase the final product had about 350 more lines of code than the estimated 2550 in the second phase The lines of code according to packages are listed below TeomaPackage 469 GooglePackage 545 ProducerPackage 576 ManagerPackage 859 KeyObjectPackage 64 AgentKeyPackage 450 116 Total 2963 lines of code Cost Estimate Though the final lines of code of 3000 was almost double the original estimate of 1500 lines of code the developer actually managed to finish a few days ahead of the schedule This is primarily because at the end of second phas
53. er Class Reference Public Member Functions e String doSearch String keywords Detailed Description This class actually does the Google search using the Google API and the key provided to the developer If you are not Madhukar then please sign up at Google for a new API key and copy and paste it below in String s Currently String s holds the key issued to Madhukar Member Function Documentation String GooglePackage Crawler doSearch String keywords inline This method actually does the search It takes a string as a parameter which is used as keywords to search Google The documentation for this class was generated from the following file Crawler java GooglePackage MulticastSend Class Reference Public Member Functions e MiulticastSend int port int id throws Exception 53 e void run Package Attributes e int DEST_PORT e String MCAST_ADDR e int parentport e intid e JInetAddress thismachine Detailed Description This thread is like a public address system It broadcasts a String holding AgentGoogle s name id and port number to a multicast class d address 225 4 5 6 Anybody who joins this address will be able to read the String sent out by this class Note This works only if the receiver is on the same network Member Function Documentation void GooglePackage MulticastSend run inline The model for the class This method opens a MulticastSocket and then continou
54. er window Caveats for test id 2 and 3 For the tests id 2 and 3 to pass the following conditions must be true 1 User must have inputted keywords either by typing something in MS Word or through FilteredSearch user menu 2 There must be at least one Sleuth agent AgentGoogle or AgentTeoma and one AgentProducer running on the same machine or the same network 3 The machines hosting the Sleuth Agents must be connected to the Internet 4 The firewall on the user s machine that has MS Word running on it should have the Windows and or personal firewalls either switched off or configured to send receive multicasting packets Test id 4 Portability testing The developer tried to run AgentGoogle AgentTeoma and AgentProducer on the following machines a Windows 2000 machine Windows XP Professional machin a Suse 8 2 Linux machine and a Solaris machine All the times the Agents started and worked properly and returned results A caveat for the above test is that the machines running the Agents should have java 1 4 installed on them Test id 5 All three field empty in User Preferences dialog menu When the user is in MS Word and presses the FilteredSearch button he she is presented with a user interface which asks for the user to input one or all three of the following fields keywords website and file format Initially when the developer conducted a test of not inputting any of the values in the field the Manager Agent still
55. esigning 0 min 523 min 0 min Integration 30 min 0 min 80 min debugging troubleshooting 118 Phase 1 Break down Research MMe OIS taaeatigh meeungs 80 74 130 7 T 3 11 Codin 230 3 Document tion 20 a i 589 52 Figure 42 Phase 1 Break down Phase 2 Break down Meeti Designing p 523 24 29 Timelogs Document 30 ation 2 Coding 626 189 34 G Meetings E Documentation O Coding O Timelogs E Designing Figure 43 Phase 1 Break down 119 Phase 3 Break down Integration Meetings 80 150 Timelogs 3 6 95 4 Documentation 771 Coding 33 1239 54 Meetings E Documentation O Coding OTimelogs E Integration Figure 44 Phase 3 Break down Lessons Learnt Usefulness of methodology One of the biggest advantages of using Agent Oriented Software Engineering AOSE to develop the system was the fact that agents are fairly independent programs and when one goes down the entire system is still functioning 120 Since the developer had used agentTool to develop a multi agent system before he was aware of the smaller nuances of using the tool and had no big learning curve This greatly cut down the implementation time It would be nice if agentTool allowed the design of some external components into the system during the design and analysis phase and it would be also nice if it had multicasting feature built into it The developer is aware that both these features
56. gentGoogle and AgentTeoma are running For each unique agent discovered MulticastReceive creates a RunningAgent object and stores the agents name id and port number It then stores all the RunningAgents object in a Vector and sends the Vector back to AgentManager The MulticastReceiver also records the port number and machine IP address of a running AgentProducer and passes it on to AgentManager AgentManager now contacts the AgentKeyPackage and gets back a Vector of KeyObjects It then sends the Vector to the running instances of AgentGoogle and AgentTeoma It gets back RawResult object from each sleuth agent that it stores in a vector AgentManager now sends the vector of RawResult to AgentProducer AgentProducer in turn makes a list of the final result and encapsulates it with html headers and footers When AgentManager gets this String it merely writes it to a file called final_result html in the c mart folder 78 AgentManager from ManagerPackage indicator boolean false llagents java util Vector results java util Vector Boroducer_port int 0 BSproducer_machine String gentManager un write BreceiveMessage RreadUserPreferences rankKeywords EXgenerateResults BsearchTheWeb Bunserialize SgenHtmi QoetAlIRaw Stalk ToP roducer SsetFinalResult Eo ain MulticastReceive from ManagerPackage UFFER_LENGTH int EST_PORT int CAST_ADDR String
57. he class that handles the event from the OK button push event of the UserPref class The AgentKey has two main methods that are responsible for extracting keywords and making KeyObjects out of them and also for ranking the keywords UserPref from AgentKeyPackage WuserPref WoetSite String getKeywords String AgentKey from AgentKeyPackage keywords java util Vector WeetFileFormatt String SactionPerformed e java awt event ActionEvent void ee sa Bmain args String void stripArticles s String String iew WcreateKeyObject s String java util Vector SrankKeywords v java util Vector java util Vector WselectionSort r Object Object BMfindLeast r Object start int end int int SmakeKeyFile Object NewPref from AgentKeyPackage NewPref my_view AgentKeyPackage UserP ref SactionPerformed evt java awt event ActionEvent void Figure 28 AgentKeyPackage AgentKeyPackage Class Documentation AgentKeyPackage AgentKey Class Reference Public Member Functions e AgentKey e String readFile 65 e String stripArticles String s e Vector createKeyObject String s e Vector rankKeywords Vector v e Object selectionSort Object r Public Attributes e Vector keywords Detailed Description This is not like the rest of the agents in the sense it does not converse w
58. he user should be able to specify that the results should be only from a specified website and should only between two certain dates 5 Allow the user to choose when he she wants to view the results Requirement Specification Information Analyzer Agent Google specialist Agent Search Agent Manager Local database specialist Agent Citeseer specialist Agent Local Database Figure 2 Overview of the MART structure Main requirements 1 Multi Agent Systems based architecture Specific functions will be performed by individual agents that are fairly independent goal driven proactive and reactive 2 Use of Multi Agent Software Engineering MaSE methodology and agentTool in developing the system 3 The final product MART should be integrated with MS Word processor 4 The individual agents should be able to run on any machine that has a Java virtual machine This includes machines running on the following platforms Windows Linux Macs 5 Internet Explorer a common web browser used by Windows users will be used to display the search results 6 For testing and demonstration purposes the software should use the Google API to conduct searches on Google search engine 7 Failure of one agent should not crash the whole software Specific Requirements 1 Allow a user to write an article in MS Word 2 The user interface would include buttons embedded inside MS Word which will allow the user
59. hen the AgentGoogle is be able to conduct a search on the Google web site using the keywords provided to it and then return an object with the raw results to the AgentManager Implement AgentTeoma This task will be considered complete when the AgentTeoma is be able to conduct a search on the Google web site using the keywords provided to it and 19 then return an object with the raw results to the AgentManager Implement AgentProducer The implementation of the AgentProducer will be considered complete when it is able to respond to a message by AgentManager by refining the results from raw results and sending back the final result file Integration The integration will be considered complete when a user is able to click on the Search and Save macro that would initiate AgentManager to complete all its tasks 20 CHAPTER 3 ARCHITECTURE DESIGN Introduction The purpose of the document is to describe the architecture design of the project Multi Agent Research Tool MART as outlined in the requirements in section 3 of the vision document The document will outline and describe the goals the role model the object diagram and the sequence diagrams of MART Goals The overall goal of the system is to produce searched results This goal is partitioned into four sub goals mainly to rank and refine the keywords that will be used for search searching the web for results producing the result output file for the user and to manage
60. hould be completed by the final presentation User Documentation The document will describe all the features of MART and also explain to the user how to install and use the software The document will be considered complete when all the features have been described adequately in the document Revision of Architecture Design document 18 The revised Architecture Design document will record any changes made to the design and will also have detailed design description of the individual components of the software Assessment Evaluation The Assessment Evaluation document will describe all the tests that were done on the MART software and the results of the test Project Evaluation The Project Evaluation document will give an overall evaluation of the project regarding the efficiency of the methodologies used and the usefulness of reviews Implementing individual packages and classes Implement AgentManager The implementation of the AgentManager would be considered complete once it is able to perform the following tasks The AgentManager should be able to send out a message to the AgentKey to read the user preferences and keywords Once the keywords are read and ranked the AgentManager should send out messages to the Sleuth agents and get back the raw result Finally the AgentManager should be able to send the raw results to the AgentProducer and get back a final result file Implement AgentGoogle This task will be considered complete w
61. ice he she will get a message Bad port number given to Listener constructor for agent AgentGoogle and the program will stop To give a valid port number the user should try any number between 7000 and 65000 102 CHAPTER 8 USER S MANUAL System Overview Multi Agent Research Tool MART is a multi agent system that helps a researcher and or author in conducting searches on the web while the user is typing the article in MS Word The user while typing the article can use the system by clicking one of the two buttons Search and FilteredSearch available in the MS Word menu Each time the buttons are pressed the system conducts a search creates an HTML page and stores it on the user s computer When the user is ready he she can press the DisplayResult button that will show the results page in Internet Explorer MART User Interface The quick brown fox jumps over the lazy dog Figure 33 User Interface Using the System To use the system first run AgentGoogle and or AgentTeoma and AgentProducer as detailed in the following steps and then start typing the article in MS Word When you 103 are ready just click on the StartSearch or FilteredSearch buttons When you are finally ready to view the result click on the DisplayResult button from the MS Word menu Running AgentGoogle Descend into the directory where GooglePackage directory is installed and double click on AgentGoogle bat file if you
62. ion Document After the first presentation based on the suggestions provided by the committee member the vision document will be modified The revised document will be approved by the major professor 17 Revision of Project Plan After the first presentation based on the suggestions provided by the committee member the project plan will be modified The revised document will have an updated cost estimate and will be approved by the major professor Architecture Design Development of overall goals roles concurrent tasks use cases agent templates conversation between different agents and the verification of conversations should be completed in the agentTool In addition to the above tasks an object model should also be developed that would describe all the objects of the system and the important methods and attributes of each object Development of a second prototype Development of the second prototype should establish the fact that agents could talk to each other and return with some relevant search details if some keywords are passed as search parameters Test plan Development of a test plan should show that all requirements specified in the vision document are satisfied Formal Technical Inspection The architecture design shall undergo formal technical inspection by two MSE students who have agreed to participate in the inspection Cem Oguzhan and Esteban Guillen Implementation Plan The following tasks s
63. it around a RawResult object before sending it back to the caller automatically generated by agentTool agentMom transform ver 0 4 void TeomaPackage AgentTeoma write String s inline Write method used to write conversation error messages to output automatically generated by agentTool agentMom transform ver 0 4 The documentation for this class was generated from the following file e AgentTeoma java 61 TeomaPackage MulticastSend Class Reference Public Member Functions e MiulticastSend int port int id throws Exception e void run Package Attributes e intid e int DEST_PORT e int parentport e String MCAST_ADDR Detailed Description This class is identical to MulticastSend of GooglePackage Please refer to GooglePackage documentation for more information about this class The documentation for this class was generated from the following file MulticastSend java TeomaPackage searchTheWeb_AgentTeoma_R Class Reference 62 Public Member Functions e searchTheWeb_AgentTeoma_R Socket S ObjectInputStream 1 ObjectOutputStream 0 AgentTeoma a Message m1 e void run Package Attributes e AgentTeoma parent e Message gotm Detailed Description Conversation class for searchTheWeb_AgentTeoma_R This class manages the conversation with AgentManager s conversation initiator and finally returns the search result which it gets from AgentTeoma s search method automatically genera
64. ith any other agent but the Manager The methods here are all called by AgentManager This class reads a txt file and filters out words like of a etc then creates a KeyObject for each word Finally it adds the ranking and nooftime in each object and returns a Vector of the KeyObjects to the Manager Constructor amp Destructor Documentation AgentKeyPackage AgentKey AgentKey inline Just initializes the Vector which will be filled with KeyObjectss 66 Member Function Documentation Vector AgentKeyPackage AgentKey createKeyObject String s inline This method takes a string as a parameter It takes the string breaks them into individual words makes KeyObject of each word and adds them to the vector keywords It returns the Vector or all KeyObjects when it finishes Algorithm First check if the word exists in the keyword if it does then merely increment its nooftime attribute by 1 If it does not then just create a new KeyObject and add to the vector At this point all ranks are 0 invalid The ranking will be done by rankKeywords Vector AgentKeyPackage AgentKey rankKeywords Vector v inline rankMethod takes the Vector of KeyObjects and arranges everything in decending order based on the frequency nooftime of each keywords It then takes the sorted vector and sets the rank for each one of them by giving 1 to top most 2 to next and so on Algorithm It takes the vector converts it to an array and calls th
65. keywords are also present in the result the USE model has ResultWord classes that are attached to the RawResult class The ResultWord class represents each and every result words String that will be present in the RawResult class in actual implementation Constraints The first constraint keysalsoinresult specifies that the search results RawResult will have some of the keywords that exist in the keywords KeyObjects The second constraint rankings specifies that if a keyword appears more number of times in the user typed article then its rank will be higher than keywords that appear lesser number of times in the typed article 39 name agents nooftime 3 practices ResuttWord tank 1 word practices rasuttword manager resultfileresuttfile resuttfile software KeyObject paradigm KeyObject name software name paradigm nooftime 2 nooftime 1 rank 2 tank 3 resultword ResulttWord Figure 21 USE Model 40 MART use in mad cis mse presentation2 folder The model demonstrates the primary property of MART project being built for the MSE project The property it tries to state and check is that some of the keywords originally typed by the user should also present in the final results file Author Madhukar Kumar Date July 25 2003 model MART CLASSES The AgentManager agent is the main controller of the entire syst
66. ll the keywords The Keywords ranker ranks the keywords based on the number of times they appear in the user typed article and returns the ranked keywords to the manager 22 Keywords reader reader readUserPreferences Controller Manager Keywords ranker ranker rankKe Figure 6 Read User Preferences Search the Web The following sequence diagram shows that the manager sends a message to the Sleuth along with the keywords and requests it search the web The sleuth conducts the search and returns the raw result to the manager 23 Controller Manager Sleuth Searcher searchThevveb Figure 7 Search the Web Generate results The following diagram show that the Manager once it has the raw results sends a message to the Result producer along with the raw results The producer refines the results and then sends back the final result to the manager 24 Controller Manager Result producer ResultGenerator generateResults finalResult Figure 8 Generate results Role diagram The role diagram depicts how the different goals are mapped to the roles of the system The following diagram shows that the controller has a bunch of tasks that collaborate with the other roles in order to read keywords perform a search and generate the final result The dotted line in the Sleuth role makeRaw shows that it is an internal method call The makeRawResults task is
67. lt of the search The primary packages representing the agents and their component classes are AgentKeyPackage ManagerPackage GooglePackage TeomaPackage and ProducerPackage Figure 15 shows the interaction between all the packages ManagerPackage holds the AgentManager class which is the main controller of the whole system and initiates all the conversations with other Agents lt lt uses gt gt lt lt uses gt gt et OP ee te ke 8 IS re ee Sn ee ERNA I I l I i l rankKeyords i l l I lt lt conversation gt gt I AgentKeyPackage K I GooglePackage i l C I C l 1 i lt lt uses gt gt l l lo a i i 1 l I i searchirheWeb lt lt useb gt gt lt lt convarsation gt gt l readUserPreferences ee J i lt lt conversation gt gt C l i ManagerPackage l I LJ I Gn sa lee ies ace Sh fe i l l j lt lt uses gt gt 1 searchTheWeb eee een l lt lt conversation gt gt generatgResults ProducerPackage K S lt conversation gt gt L Figure 14 Component diagram of the entire system 31 KeyObjectPackage The KeyObjectPackage is the data package that is used by all other packages to send results and keywords to each other Class KeyObject is a simple class with three main attributes called name rank and nooftime The actual keyword is stored in the variable name while the integers rank and
68. m output void readPrefAgentKey SoogePackage makeRawResuls smakeRawResults serawhile rawile serialize Object rawfile void run void 1 rankKeywordsAgentKey tankKeywordsConvKey 1 teadPrefConvKey AgentKeyPackage rankKeywords_AgentKkey_R PoenikeyPackage readUserPreferences_AgentKoy_R oi CE ZZ i tws wile Object ferun Object MManagerPackage rankKeywords AgentManager_ ManagerPackage readUserPreferences_AgentManager_ ief Object ti recelveMessage Sockel server ObjectinputStream input ObjectOutputStream output E ManagerPackage makeFinalResult GooglePackage rawResults producer 1 rankKeyConvManger cerawile serawtile rawie convi generateResults Object producer Object serawfile tconv_r_searchTheWeb Object controller Object Keywords void un trun void ManagerPackage search searchTheWebManager genResultsConvManager conv_ _readUserPreferences Object reader Object reader run ManagerPackage generateResults_AgentManager _ aaa roducerPackage generateResults_AgentProducer is ee 1 f SearchTheWebConvTeoma 4 searchTheWebAgentTeoma TeomaPackage AgentTeoma ferun Object fwrite receiveMessage Sockat server ObjactInputStream input ObjactOutputStream output itrun
69. mizing the DOS prompt window The following figure shows how a user has typed a line in MS Word and then clicked on the Search macro button i When you have ty g something in the document AO 4 A T wm just click this button E ZE tE 5 2 HELE r Z The quick brown fox jumps over the lazy dog Figure 34 Conducting search without preference Conducting Filtered Search MART can also be used to conduct searches with user defined preferences To do this simply click on the FilteredSearch macro button in the MS Word You will see a dialog menu as shown in Figure 3 If you type some keywords in the first text field and 105 then give a name of the website and also specify the document format by typing d or p then MART will conduct a search only on those keywords on the website you specified and only in pdf or doc documents For example if you typed everything exactly the same preferences as shown in Figure 4 then MART will conduct a search only on words software agents and restrict the search to the citeseer nj nec com website and search only pdf documents If you leave any field empty in the dialog menu for example if you don t type in the keywords then MART will automatically pick up keywords from whatever you have typed out in MS Word However if you leave all three fields empty and then press the OK button then you will get an error message When you are typing out the website address please ensure that you
70. ng and also on which the AgentKey since AgentKey needs to read what the user has already typed in MS Word is running Author Madhukar Kumar September 16 2003 ready for presentation 3 80 ManagerPackage Class Documentation ManagerPackage generateResults_AgentManager_I Class Reference Public Member Functions e generateResults AgentManager I AgentManager a String hostName int portNum Object serawfile_in e void run Package Attributes e AgentManager parent e Object serawfile Detailed Description Conversation class for generateResults_AgentManager_I This class is responsible for handling the conversation with AgentProducer automatically generated by agentTool agentMom transform ver 0 4 Constructor amp Destructor Documentation ManagerPackage generateResults AgentManager_I generateResults_AgentMana ger_I AgentManager a String hostName int portNum Object serawfile_in inline Constructor for generateResults AgentManager_I automatically generated by agentTool agentMom transform ver 0 4 81 Member Function Documentation void ManagerPackage generateResults_ AgentManager_I run inline Conversation run method controls the conversation with AgentProducer The method sends a Vector of RawResults and gets back an html wrapped String This String is passed on to AgentManager through its setFinalResult method automatically generated by agentTool agentMom transform ver 0
71. nstructor also creates and starts an instance of MulticastSend automatically generated by agentTool agentMom transform ver 0 4 Member Function Documentation void TeomaPackage AgentTeoma receiveMessage Socket server ObjectInputStream input ObjectOutputStream output inline Required method for agentMom framework Whenever someone tries to start a conversation with this Agent it checks to see if the message performative is search If it is then a new conversation responder thread is started otherwise a sorry message is sent back automatically generated by agentTool agentMom transform ver 0 4 60 void TeomaPackage AgentTeoma run inline Run method for agent merely prints a statement that the Agent is now successfully running at the specified port number automatically generated by agentTool agentMom transform ver 0 4 Object TeomaPackage AgentTeoma search Object keyfile inline Method rawfile search referenced in conversation The method looks at the current Agent s id and then decides how many keywords will be extracted for search It then calls a private method called alttVista that actually conducts the search on the search engine automatically generated by agentTool agentMom transform ver 0 4 Object TeomaPackage AgentTeoma serialize Object rawfile inline Method serawfile serialize referenced in conversation This method takes an Object as a parameter It casts the Object to a String and then wraps
72. nt p int id e void run e void write String s e void receiveMessage Socket server ObjectInputStream input ObjectOutputStream output e Object search Object keyfile e Object serialize Object rawfile Static Public Member Functions e void main String args Package Attributes e intp e intid Detailed Description This agent is responsible for getting search results from the Google website by using the Google API 50 Constructor amp Destructor Documentation GooglePackage AgentGoogle AgentGoogle String n int p int id inline Constructor merely initializes the agents s name port number and id Member Function Documentation void GooglePackage AgentGoogle receiveMessage Socket server ObjectInputStream input ObjectOutputStream output inline This method is called whenever someone tries to start a conversation with AgentGoogle This message checks to see if the performative of the message sent to it is search If it is then it spawns a new conversation responder thread and passes it the socket and the input and output streams to start conversation If the message performative is not search then it returns a sorry message automatically generated by agentTool agentMom transform ver 0 4 void GooglePackage AgentGoogle run inline Run method for agent Google Simply outputs a message that it is now running on the specified port number automatically generated by agentTool agent
73. nt_name Detailed Description This class is used to transfer result by all Agents The documentation for this class was generated from the following file e RawResult java GooglePackage 47 GooglePackage consists of the following four classes shown in the diagram The class MulticastSend is a thread that broadcasts the AgentGoogle s name port number and id to a class D address When AgentManager is started it joins the multicast address and receives the agent name id and port number Class crawler has one method called doSearch and it is actually responsible for conducting search on the Google search engine using the Google API and a license key issued to the developer AgentGoogle is the main controller of the system When it receives a request for conversation from AgentManager it spawns a new conversation responder thread that controls the conversation During the conversation AgentGoogle receives the keywords and based on its current id it decides how many keywords it should take to conduct a search Finally when the package has accumulated the result it returns it as a RawResult object found in KeyOnjectPackage to AgentManager s conversation initiator AgentGoogle Crawler 5 from GooglePackage from GooglePackage p int Mjo int Bicrawler loSearch keywords String Strin BAgentGoogle n String p int id int Li key 9 s Brun void Ruiite s String void
74. oglePackage has two classes AgentGoogle and searchTheWeb_ AgentGoogle R AgentGoogle has one important method called search When AgentGoogle receives a message from AgentManager it creates an instance of the searchTheWeb_ AgentGoogle R that handles the conversation from there on The conversation is closed once AgentGoogle conducts the search serializes the result and sends back the serialized object in the form of an instance of RawResult class in KeyObjectPackage to the AgentManager AgentGoogle rawfile KeyObject serawhile KeyObject searchT heWebAgentGoogle Figure 17 GooglePackage 34 TeomaPackage TeomaPackage is similar to the GooglePackage and consists of the following two classes AgentTeoma and searchTheWeb_AgentTeoma_R These two classes perform the same functions like the classes in the GooglePackage The main difference between the two packages lie in the way AgentGoogle and AgentTeoma conduct searches AgentGoogle uses Google API to conduct keyword search on Google com while AgentTeoma opens a URL connection with the website and gets back raw results AgentTeoma rawfile KeyObject serawfile KeyObject H run write receiveMessage makeRawResults RawResult rawResults RawResult tsearchTheWebAgentTeoma searchTheWWebConvTeoma 1 Figure 18 TeomaPackage 33 ProducerPackage ProducerPackage also has two classes called AgentProducer
75. oject plan and for the implementation of the final project The developer will perform all tasks under the supervision of the Major Professor and will meet with him every week to show him the progress in work and also take further instructions and suggestions from him Formal Technical Inspectors The formal technical inspectors will submit a formal report after inspection on the architecture design artifacts The tasks to be performed for the entire project and the breakdown of individual tasks have been defined in the project plan document and the Gannt Chart Documentation 90 The required documentation is outlined in the MSE portfolio handbook for the MSE students at the CIS department at Kansas State University These documents would include a vision document a project plan document a software quality assurance plan document a test report and a user manual These documents will be posted on the web http www cis ksu edu madhukar and also be presented to the committee members during the three presentations and demonstrations The committee members will evaluate the documents Standards Practices Conventions and Metrics Documentation standard Wherever applicable IEEE standards and practices will be used to develop all documents for the project Coding standard The environment agentTool will ensure that all standard coding practices will be used like indenting all control structures and embedding descriptive commen
76. om the Sleuth agents The documentation for this class was generated from the following file e searchTheWeb_AgentManager ljava 88 CHAPTER 5 SOFTWARE QUALITY ASSURANCE Purpose The purpose of the documents is to define the Software Quality Assurance SQA plan that will be adopted throughout the project to maintain an acceptable quality of the final product References 1 Vision Document 2 Project Plan Document 3 IEEE Guide for Software Quality Assurance Planning 4 IEEE Standard for Software Quality Assurance Planning 5 agentMom User s Manual 6 Scott A DeLoach Mark F Wood amp Clint H Sparkman Multi agent Systems Engineering The International Journal of Software Engineering and Knowledge Engineering Volume 11 no 3 June 2001 Management Organization Supervisory Committee Dr Scott A DeLoach Dr Daniel Andresen Dr Virg Wallentine Major Professor Dr Scott A DeLoach Developer Madhukar Kumar 89 Tasks Formal Technical Inspectors Cem Oguzhan Esteban Guillen Responsibilities Supervisory Committee The committee would be responsible for attending reviews at the end of each phase and provide feedback and suggestions Major Professor In addition to the responsibilities of the supervisory committee the advisor will be responsible for supervising and evaluation of work done by the developer on a weekly basis Developer The developer will be solely responsible for all the tasks outlined in the pr
77. orm ver 0 4 The documentation for this class was generated from the following file searchTheWeb_ AgentGoogle R java TeomaPackage The TeomaPackage consists of the classes shown in the next figure When AgentTeoma receives a conversation request with a search performative it starts the conversation responder thread The conversation responder thread searchTheWeb_ AgentTeoma_ R class then invokes the search method in AgentTeoma that crawls on a search engine with the keywords received from AgentManager and 56 returns the result wrapped in a RawResult object The MulticastSend object behaves identically to the one described under GooglePackage MulticastSend an from TeomaPackage gentTeoma id int from TeomaPackage A zint W int Boparentport int Bic int _ gt BJMCAST_ADDR String BAgentTeomain String p int id int MulticastSend port int id int Brun wid n void Swiite s String void BreceiveMessage serer java net Socket input java io ObjectinputStream output java io ObjectOutputStream void Bsearch keyfile Object Object PRaltaVista keywords String String Bserialize rawtile Object Object Bmain args String void Parent searchTheWeb_AgentTeoma_R from TeomaPackage SsearchTheWeb_AgentTeoma_R s java net Socket i java io ObjectInputStream o java io ObjectOutputStream a TeomaPackage
78. played in Internet Explorer TABLE OF CONTENTS TABLE OF CONTENTS 0 REETA EEEE ee eee ee ee ee ee eee eee ii LIST OF FIGURES neslra aaea E A eae era er E EEEE iii CHAPTER 1 VISION DOCUMENT 2 eee eee eee eee 1 CHAPTER 2 PROJECT PLAN ee eee ee ee eee eee 12 CHAPTER 3 ARCHITECTURE DESIGN e 2000 21 CHAPTER 4 COMPONENT DESIGN 0 eee eee eee eee 44 CHAPTER 5 SOFTWARE QUALITY ASSURANCE 89 CHAPTER 6 TEST PLAN oeo ccc ee ea Ee ele ee ee 93 CHAPTER 7 ASSESSMENT EVALUATION 2 255 97 CHAPTER 8 USER S MANUAL 2 eee eee eee ee ee eee 103 CHAPTER 9 PROJECT EVALUATION 20 5c ee eee 115 REFERENCES o rusya pa ra arg se OU gle Woh Baten gol eee FIRE Ce Pea es ee iat ats 122 LIST OF FIGURES Figure 1 Overview of MART 5 Figure 2 Overview of MART structure 7 Figure 3 Critical Use Case 9 Figure 4 Gannt Chart 14 Figure 5 Goals of the system 21 Figure 6 ReadUserPreferences 23 Figure 7 Search The We
79. s shown in the above figure Now drag Normal Modulel Search and drop it anywhere in your MS Word menu Right click on it and rename it to Search and choose an icon image of your choice Do the same steps for Normal Modulel FilteredSearch and Normal Module1 DisplayResult and rename them FilteredSearch and DisplayResult respectively MART in ready to be used from within MS Word 113 Installing Agents Unzip mart zip and copy the GooglePackage directory and TeomaPackage directory to any machine on your local network The GooglePackage consists of a file called googleapi jar Make sure this is in the classpath of the system where you plan to run this agent or unjar it in the directory where you see it For installing AgentProducer simply copy the file to any machine on your local machine where you plan to run it from Make sure that ManagerPackage and KeyPackage are located on the same machine that you will be using to run MS Word 114 CHAPTER 9 PROJECT EVALUATION Problems encountered Multicasting During the end of the second phase of the project a new requirement was added The requirement was that the AgentManager should somehow be able to know of all the Sleuth agents that are running on the local network To implement this the concept of multicasting was explored and finally implemented in the project The main problem that the developer faced while implementing multicasting in the project was that while it worked in
80. sly keeps sending the String out as a message in a never ending loop 54 The documentation for this class was generated from the following file MulticastSend java GooglePackage searchTheWeb_AgentGoogle_R Class Reference Public Member Functions e searchTheWeb_ AgentGoogle R Socket S ObjectInputStream 1 ObjectOutputStream o AgentGoogle a Message m1 e void run Package Attributes e AgentGoogle parent e Message gotm e Vector ko Detailed Description Conversation class for searchTheWeb_AgentGoogle_R This thread is responsible for the conversation with AgentManager automatically generated by agentTool agentMom transform ver 0 4 Constructor amp Destructor Documentation GooglePackage searchTheWeb_AgentGoogle_R searchTheWeb_AgentGoogle_R Socket s ObjectInputStream i ObjectOutputStream o AgentGoogle a Message 55 m1 inline Constructor for searchTheWeb_AgentGoogle_R merely initializes the variables it receives from the AgentGoogle automatically generated by agentTool agentwom transform ver 0 4 Member Function Documentation void GooglePackage searchTheWeb_AgentGoogle_R run inline Conversation run method controls the conversation with AgentManager This method calls the AgentGoogle s search method and collects the result which it wraps around a message object and sends back to AgentManager s conversation initiator automatically generated by agentTool agentMom transf
81. t cases overview Test Id Test Unit Test Case Result Comments 1 Specific User Interface MS Do all existing Passed requirements Word Word features Typing in work Word 2 Specific The whole integrated Does MART Passed requirement system create a results Search page if some words are typed in MS Word 3 Specific The whole integrated Does the result Passed requirement system page open up in Display Result Internet Explorer when user presses DisplayButton in Word 4 Portability ProducerPackage Do the agents Yes except on the testing GooglePackage and run on Linux machines in TeomaPackage Windows Unix the CIS lab where the and Linux machines are 97 machines configured to drop multicasting packets The agents work fine on Suse 8 1 and Windows XP professional on developer s laptop 5 All three UserPref java No input for Error message Not fields empty keywords a valid input in User website and file Passed after Preferences format modifications were dialog menu made to UserPref java 6 Invalid AgentGoogle java Port number Error message Bad port number already taken by port number some other service 7 No Agent Manager No keywords Error message keywords package inputted in MS Sorry no keywords inputted by Word and in inputted user Dialog box triggered by FilteredSearch 98
82. ted by agentTool agentMom transform ver 0 4 63 Constructor amp Destructor Documentation TeomaPackage searchTheWeb_AgentTeoma_R searchTheWeb_AgentTeoma_R Socket s ObjectInputStream i ObjectOutputStream o AgentTeoma a Message m1 inline Constructor for searchTheWeb_AgentTeoma_R Note that AgentTool has a bug The developer has to ensure that the Message m it receives in the parameter is the same that is used in the run method AgentToo generates code in which there are two different Messages and hence this class will not run if the above bug is not fixed by the developer automatically generated by agentTool agentMom transform ver 0 4 Member Function Documentation void TeomaPackage searchTheWeb_AgentTeoma_R run Q inline Conversation run method controls the conversation with AgentManager s conversation initiator It receives a search message with the keywords The keywords String is sent to the search method in AgentTeoma that returns the search result The search result is finally sent back to the AgentManager automatically generated by agentTool agentMom transform ver 0 4 The documentation for this class was generated from the following file searchTheWeb_AgentTeoma_R java AgentKeyPackage 64 This package has three main classes as shown in the next figure It has the GUI user interface UserPref java that shows up when the user clicks on FilteredSearch button from MS Word The NewPref object is t
83. to search save and display the results 3 The program will generate HTML 4 0 result pages so that they can be viewed using a common web browser Internet Explorer Critical Use Cases System MS Word and MART Type Article Researcher Display Results Figure 3 Critical Use Case Use Case 1 Type article in MS Word Description The user should be able to type an article in MS Word with his her normal settings and preferences and when MART is finally integrated with the word processor none of the features preferences and settings should either change or stop working The user should also be able to save the articles as any other regular files Use Case 2 Search for research material Description The user should be able to click on a button somewhere in the MS Word menu that should trigger off the MART search agents Once the button is pressed the agents should collect all the words from the article being currently typed out in the article figure out the relevant keywords conduct a search with those keywords using some search engines and then create an HTML file with all the valid results Filter results The user should be able to specify that the results should only be from a particular web site or that the results should be filtered by date The user should also be able to specify that only certain kinds of files like doc html or pdf files should be searched Keywords ranking The program should be able to r
84. toText Toolbars Macro Project Items a Macro Project Items available in Macro Project Items available in Document Document hd Normal dot global template v Figure 38 Installing Macros 2 110 6 Now click on Module and click on the lt lt Copy button so that Module now also shows in the left panel as in the following figure Styles AutoText Toolbars Macro Project Items To Document4 In Normal Module 1 Macro Project Items available in Macro Project Items available in Documents Document 4 Normal dot global template X Figure 39 Installing Macros 3 7 Now right click any where near the menu in MS Word and then click Customize 111 Toolbars Commands Options To add a command to a toolbar select a category and drag the command out of this dialog box to a toolbar Selected command Desciption Modify Selection Figure 40 Installing Macros 4 8 Click on Macro button on the left panel 112 9 10 11 12 Toolbars Commands options To add a command to a toolbar select a category and drag the command out of this dialog box to a toolbar Categories Commands Normal AutoExec AddOurToolba_ Normal Module 1 DisplayResult Normal Module 1 FilteredSearch Normal Module 1 Search Normal NewMacros AddOurToolt Figure 41 Installing Macros 5 Scroll down in the right panel till you see Module macros a
85. ts and invariants in all the methods and attributes of the separate classes Reviews and Audits The reviews will be conducted by the committee members as outlined in the MSE portfolio handbook of the CIS department at Kansas State University This includes three presentations and submission or required documentation to the committee members at the beginning of each presentation The three presentations would also include demonstration of prototypes intended to establish the feasibility of the various aspects of the project Test and problem reporting The test report documents will outline all the tests conducted and the results of the test All problems will be reported to the committee chair Dr Scott DeLoach Significant problems will also be reported on the time logs posted at the project web site Tools techniques and methodologies 91 The following tools will be used in the project Software Development Environment O agentTool O Java java net packages O Visual Basic Application O MS Visio for developing object model and other design artifacts Deliverables The following deliverables will be submitted at the end of the project agentTool mam file Java source code with Javadoc API HTML documents Source code for MS Word macros Design artifacts object model use case documents Vision document Project Plan document Software Quality Assurance SQA plan document User Manual Test report 92 CHAPTER 6
86. used word processor program MS Word and help the user to conduct relevant searches in the background based on the words that have been typed in the article and then display the results to the user The primary goal of creating MART is develop a smart Multi agent system that would intuitively and independently search and display information about an article while it is being typed by a researcher The main feature of the software is to do relevant searches and display the results dynamically even while the user is typing the article and the real challenge is to find results that are relevant to the article being written and are not redundant Goal To develop a tool that will be integrated with MS Word and help an author in searching research information for an article based on the words that have already been typed in an article The search results should be fairly accurate relevant to the current article being typed and non redundant Purpose To build a multi agent system with a collection of intelligent software agents that are fairly autonomous and use distributed computing to achieve a common goal Features 1 Integrated with MS Word 2 There will be separate agents responsible for specific tasks For example one agent should be a specialist only in conducting searches in Google 3 The search should be conducted only when the user want to use MART 4 The user should be able type in the preferences for the search results For example t
87. w ile inline Method readRawFile referenced in conversation merely casts the object that it receives into a Vector and then extracts all the elements of the vector and casts them into RawResult object void ProducerPackage AgentProducer receiveMessage Socket server ObjectInputStream input ObjectOutputStream output inline This method is called when someone tries to start a conversation with AgentProducer This method checks to see if the attempt is valid and if it is then it spawns a new conversation responder thread by passing the values of socket and the input and the output streams The documentation for this class was generated from the following file AgentProducer java ProducerPackage generateResults_AgentProducer_R Class Reference Public Member Functions e generateResults_ AgentProducer_R Socket S ObjectInputStream 1 ObjectOutputStream o AgentProducer a Message m1 e void run Package Attributes e AgentProducer parent e Message gotm 75 Detailed Description Conversation class for generateResults_AgentProducer_R is responsible for carrying out the conversation with AgentManager and sending back the final result automatically generated by agentTool agentMom transform ver 0 4 Constructor amp Destructor Documentation ProducerPackage generateResults_AgentProducer_R generateResults_AgentProd ucer_R Socket s ObjectInputStream i ObjectOutputStream o AgentProducer a Message

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