A Stigmergy Collaboration Approach in the Open Source Software ...

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V. EXPERIMENTAL RESULTSWe used detailed OSS community log data onSourceForge to illustrate the model’s theoreticalmechanisms. SourceForge, an online center for OSSdevelopment communities, provides collaborative resourcesfor approximately 200,000 projects. This data consists of allthe activity information of OSS software developers andusers registered on SourceForge from 2003 to 2008. Wedeveloped scripts that query the SourceForge Research DataArchive hosted by the University of Notre Dame [5] forproject empirical data that meet our criteria. We wereinterested in OSS projects that reached a minimum team sizeof 20 developers at some point in the project lifetime inorder to insure that the social and technical factors were wellrepresented. In addition, we eliminated data on projects thatappeared to use SourceForge only as a means to downloadthe software, not as a development environment. In all, weidentified 67 projects as viable for use as data for our OSSmodel.Our first experiment simulates the forum postingbehaviours of users and developers in the OSS community.We use the values observed in empirical data derived fromreal log data in OSS repositories to calibrate and evaluateour stigmergy collaboration model. In our simulation, thereare 20 developers and 1000 users. The users randomly postnew message threads or leave messages on existing threadson the message board and leave pheromones on the messageboard. The developers respond to answer the questionsposted by users and choosing work that is posted on themessage board, such as bug fixes and new function modules.Both user and developer agents follow the stigmergy rulesdiscussed in the previous section. The simulation output isshown in figure 1. In figure 1, the x axis represents the logvalue of the number of total posted messages of each threadcreated by agents. The y axis represents the log value of thethread number in the message board. It indicates that a largenumber of threads have only a very small amount of postedmessages. But some threads have large numbers of postedmessages. The large amount of messages in some threadsnormally indicates there are some bugs or new softwarefunctions that need to be fixed or implemented. Thedeveloper agents who post messages in the thread will bemotivated to contribute to solving the problems discussed inthe thread. Developer agents will turn to the developerforum to start a new thread or to contribute work to anexisting thread in the developer forum. Because of spacelimitations, the developer forum simulation will be discussedin another publication.We compared the simulated outputs to empiricallyobserved behavior. Figure 2 represents the real averagedistribution of the thread and the message numbers for eachthread. The distribution patterns in figure 1 and figure 2indicate that the simulation is able to partially reproduce theforum evolution trend in many OSS projects. The closenessof the simulated results to the empirical data indicates thatour model may reflect the processes that occur in OSSevolution.Figure 1: Posted message number and thread number distribution –simulationFigure 2: Posted message number and thread number average distribution -OSS community dataVI. CONCLUSIONIn this research, we presented a stigmergy approach tosimulate the collaboration model in the OSS developercommunity. In this research, we examined how the selforganizingbehavior of individuals affects the emergence ofdifferent types of organizational characteristics. Thestigmergy concept provides a theory for explaining thecollaboration model in the OSS community and other onlinecommunities. Our hypothesis is that the collaborations ofindividual OSS developers and users are stigmergycollaborations. We compared the simulated output toempirically observed behaviors in different OSS projectforums. Our preliminary experiment simulation is able topartially reproduce the forum evolution trend and forumposting behaviors of OSS users and developers in manyOSS projects. The closeness of the simulated results to theempirical data indicates that our model may reflect the realprocesses that occur in OSS evolution. A thoroughvalidation needs to be conducted to prove the model’saccuracy. Our next research step will be to build asimulation to simulate the work choosing behaviors ofdevelopers and continue to investigate how the choicesagents make in contributing their work on projectsdetermines the global status of the whole OSS project.Further research will be to extend the research model toother self-organized communities. Our hypothesis is if thesame mathematical model captures the behavior of different
systems, then we can talk about similarities between systemsbeyond simple analogies. We can use our mathematicalmodels to make predictions that apply to many differentsystems. Furthermore, if two systems obey the samemathematical laws, we can perform experiments on onesystem and infer how another system might behave undersimilar conditions.ACKNOWLEDGMENTPrepared by Oak Ridge National Laboratory, P.O. Box2008, Oak Ridge, Tennessee 37831-6285, managed by UT-Battelle, LLC, for the U.S. Department of Energy undercontract DE-AC05-00OR22725; and by Lockheed MartinCompany. The views and conclusions contained in thisdocument are those of the authors and should not beinterpreted as representing the official policies, eitherexpressed or implied, of the Oak Ridge National Laboratory,Lockheed Martin Company, the Department of Energy orthe U.S. government.REFERENCES[1] Audris, M., T.F. Roy, and D.H. James, Two case studies of opensource software development: Apache and Mozilla. ACM Trans.Softw. Eng. Methodol., 2002. 11(3): p. 309-346.[2] Dorigo, M., E. Bonabeau, and G. Theraulaz, Ant algorithms andstigmergy. Future Generation Computer Systems, 2000. 16(8): p. 851-871.[3] Yutaka, Y., et al., Collaboration with Lean Media: how open-sourcesoftware succeeds, in Proceedings of the 2000 ACM Conference onComputer Supported Cooperative Work. 2000, ACM: Philadelphia,Pennsylvania, United States.[4] Xu, J., Y. Gao, and G. Madey. A Docking Experiment: Swarm andRepast for Social Network Modeling. in Seventh Annual SwarmResearchers Meeting (Swarm2003). 2003. Notre Dame, IN.[5] Christley, S. and G. Madey, Collection of Activity Data forSourceForge Projects. 2005, Dept. of Computer Science andEngineering, University of Notre Dame: Notre Dame, IN.[6] Crowston, K., et al. Towards a Portfolio of FLOSS Project SuccessMeasures. in Open Source Workshop of the International Conferenceon Software Engineering (ICSE 2004). 2004.[7] Hackman, J.R., The Handbook of Organizational Behavior, in Thedesign of work teams, J.W. Lorsch, Editor. 1986, Prentice-Hall:Englewood Cliffs, NJ.[8] Neil Smith, A.C., Juan Fernández-Ramil, Users and Developers: AnAgent-Based Simulation of Open Source Software Evolution, inSPW/ProSim 2006. 2006.[9] Jin Xu, Y.G., Scott Christley, Gregory R. Madey, A TopologicalAnalysis of the Open Souce Software Development Community inHICSS 2005. 2005.[10] Elliott, M., Stigmergic Collaboration: The Evolution of Group Work.M/C Journal, 2006. 9(2).[11] Heylighen, F., ed. Why is Open Access Development so Successful?Open Source Jahrbuch, ed. M.B.R.A.G. B. Lutterbeck. 2007,Lehmanns Media.[12] Dorigo, M., Ant colony optimization and swarm intelligence in 4thInternational Workshop, ANTS 2004, Brussels, Belgium, September 5-8, 2004 : proceedings. Lecture notes in computer science. 2004,Berlin: Springer.
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