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An Approach to Discovering Processes in OSS Projects Chris Jensen Institute for Software Research University of California, Irvine Irvine, CA 92697-3425.

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Presentation on theme: "An Approach to Discovering Processes in OSS Projects Chris Jensen Institute for Software Research University of California, Irvine Irvine, CA 92697-3425."— Presentation transcript:

1 An Approach to Discovering Processes in OSS Projects Chris Jensen Institute for Software Research University of California, Irvine Irvine, CA 92697-3425 cjensen@ics.uci.edu http://www.ics.uci.edu/~cjensen/papers/Jensen-Scacchi-SPIP03.pdf

2 Introduction  Goal: Demonstrate the feasibility to automate the discovery of process workflows via manual search and analysis tools in open source software development communities

3 Motivation  Manual simulation provides insight into: The feasibility of an automated approach Techniques for implementation  Without: Costly, high-risk investment

4 A Directed Approach  Domain: large scale online open source software development (OSSD) projects Short duration, frequent enactment, and a propensity for available evidence  Contextual clues guide process discovery Project Web information structure Site contents Update patterns

5 Our Study  Phase1: reference model  Phase2: project history: development in context  Phase3: process-fragment mining relevancy issues  Phase4: process modeling, prototyping  Phase5: analysis

6 Sun Microsystems The Board Release Manager MaintainerDevelopers/ Contributors Website Mailing Lists Users Contribute to community, Meet time constraints for the release Maintain a project/ module, manage a group of developers ensure that the netbeans community is being run in a fair and open manner Start new release phase, propose schedule/pla n Download and use free software CVS Funds, support, Promote Java/Open source IssueZilla QA team Produce Q builds and ensure quality of the software Release proposalRelease proposal, Release updates, branch for current release, release post mortem, review Release Candidates & decide final releaseRelease updatesbranch for current releaserelease post mortemreview Release Candidates decide final release download development builds and testdownload development builds and test, Release Q-buildsRelease Q-builds Download new release report bugs Select feature to developSelect feature to develop, bug to fix, download netbeans, commit codebug to fix download netbeanscommit code decide features for the project and merge patches/bug fixesdecide features for the project and merge patches/bug fixes, create module web pagecreate module web page make decisions for the community, on high level grant CVS commit privilege to developers Link to all Use casesLinks to all Agents CVS Manager Configu re and Maintai n CVS Grant Access Site Administrator Manage website Deploy Builds SourceCas t Tools Link to Tools

7 Release candidate 2 Release candidate 1 Development build Q build Release Manager source code Module maintainer QA Team Test (Netbeans) User Use (Netbeans, Issuezilla) List of bugs to fix Final release Developer Write bug fix (Netbeans) Check (Netbeans, Mailing list) Module plan Roadmap Decide future release dates Determine project features (Mailing list) Schedule Release proposal Start a new release phase (Mailing list) Determine main features (Mailing list) Build (CVS scripts) Board memberRelease Manager Netbeans Web Site Create module web page (Web site) List of bugs Release information update (SourceCast) Check (Netbeans, Mailing list) Check (Netbeans, Mailing list) Decide which bugs to fix (Issuezilla) Site administrator Download links (SourceCast) Module Web Page

8 Towards a Formal Model

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13 Lessons Learned  Information availability Web pages, asynchronous communication via threaded communication lists, software product source code, development tools, development resources, OSS extension mechanisms  Granularity Control  Process Validation Inconsistency between prescriptions and implementation  Accountability for Evolution Need for temporal locality indication for process footprints

14 Prognosis  What makes us believe such an approach could actually work? Frequent iteration of a small number of tasks Tasks performed lend themselves to automation  Keyword search of domain-related terms Existence of technological enablers  Web Data Mining, Probabilistic Relational Modeling

15 The End  Questions?  For more information, see: Jensen, Scacchi. Simulating an Automated Approach to Discovery and Modeling of Open Source Software Development Processes. http://www.ics.uci.edu/~cjensen/papers/Jensen-Scacchi- SPIP03.pdf http://www.ics.uci.edu/~cjensen/papers/Jensen-Scacchi- SPIP03.pdf


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