intensive metrics software evolution
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In natural sciences, intensive properties do not depend on the size of the system. These slides summarize how we have found intensive metrics for the case of open source software, and how to use these ...

In natural sciences, intensive properties do not depend on the size of the system. These slides summarize how we have found intensive metrics for the case of open source software, and how to use these metrics to evaluate open source evolution. These slides have been presented at MSR 2013. There is a preprint of the paper at http://oa.upm.es/14698/

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intensive metrics software evolution Presentation Transcript

  • 1. Intensive Metrics for the Study of the Evolutionof Open Source Projects: Case Studies from theASFSantiago Gala-Pérez (ASF), Gregorio Robles (URJC),Jesús M. González-Barahona (URJC), Israel Herraiz (UPM)10th Working Conference on Mining Software RepositoriesSF, California, May 18th, 2013Preprint available at http://oa.upm.es/14698/Slides at http://slideshare.net/herraiz/intensive-metrics-software-evolution, Intensive metrics for open source evolution – http://oa.upm.es/14698/ 1/13
  • 2. Metrics for Software EvolutionCommon metrics are extensiveDifficult to compare projects of different sizeSuccessful projects undergo large size changes over their lifetimeIntensive metrics in natural sciencesMetrics not depending on the size of systemScale invariant, Intensive metrics for open source evolution – http://oa.upm.es/14698/ 2/13
  • 3. Metrics for Software EvolutionCommon metrics are extensiveDifficult to compare projects of different sizeSuccessful projects undergo large size changes over their lifetimeIntensive metrics in natural sciencesMetrics not depending on the size of systemScale invariantAre there any intensive metric for software?Can we find intensive metrics to study software evolution?, Intensive metrics for open source evolution – http://oa.upm.es/14698/ 2/13
  • 4. The case of the Apache Software FoundationASF members mailing list, November 29 2008Joe Schaeffer sayssomething IMO interesting about the ASF: the fact that the number ofcommits and the number of mailing list posts have grown in linearrelationship [...] over the years., Intensive metrics for open source evolution – http://oa.upm.es/14698/ 3/13
  • 5. Goal of the paperRatio Communication flow / development activityHypothesis: the ratio is an intensive metric for software evolutionIt varies withMaturity, technology, community compositionBut not with project source code size, Intensive metrics for open source evolution – http://oa.upm.es/14698/ 4/13
  • 6. Goal of the paperRatio Communication flow / development activityHypothesis: the ratio is an intensive metric for software evolutionIt varies withMaturity, technology, community compositionBut not with project source code sizeCase study: the ASFBroad and diverse range of projectsSize, scope, technology, maturityIf it didn’t happen on-list, it didn’t happenCommunications between developers (decisions)Issue trackersCode review tools, automated builds, wiki page editsCommits, Intensive metrics for open source evolution – http://oa.upm.es/14698/ 4/13
  • 7. ASF projects under studyProject kSLOC Technology Maturity ScopeHTTPD 156 Web server Active, long-lived UsersAPR 66 Library Active, long-lived DevsLucene 414 Index & search Active, long-lived UsersTurbine 41 Java web fwork Stagnated DevsTomcat 213 Servlet API Active, long-lived DevsJackrabbit 344 JSR-170 ref. impl. Active DevsHadoop 1270 Big Data Very active DevsGeronimo 370 JavaEE app. srv. Active, long-lived DevsSpamAssassin 54 Spam filter Mature End usersPortals 202 Web fwork Nearly dead DevsBeehive 88 J2EE Struts Attic Devs, Intensive metrics for open source evolution – http://oa.upm.es/14698/ 5/13
  • 8. ASF projects under studyProject kSLOC Technology Maturity ScopeHTTPD 156 Web server Active, long-lived UsersAPR 66 Library Active, long-lived DevsLucene 414 Index & search Active, long-lived UsersTurbine 41 Java web fwork Stagnated DevsTomcat 213 Servlet API Active, long-lived DevsJackrabbit 344 JSR-170 ref. impl. Active DevsHadoop 1270 Big Data Very active DevsGeronimo 370 JavaEE app. srv. Active, long-lived DevsSpamAssassin 54 Spam filter Mature End usersPortals 202 Web fwork Nearly dead DevsBeehive 88 J2EE Struts Attic DevsRatioWhat’s the ratio evolution for these projects?, Intensive metrics for open source evolution – http://oa.upm.es/14698/ 5/13
  • 9. Apache httpd156 kSLOC, active and long lived web server, Intensive metrics for open source evolution – http://oa.upm.es/14698/ 6/13
  • 10. Apache Portable Runtime (APR)66 kSLOC, active and long lived library used by httpd and Subversion, Intensive metrics for open source evolution – http://oa.upm.es/14698/ 7/13
  • 11. Apache Hadoop1270 kSLOC, very active development and community, higher presence ofnon-human emails, Intensive metrics for open source evolution – http://oa.upm.es/14698/ 8/13
  • 12. Apache SpamAssassin54 kSLOC, spam filter, intended for end users, maturing project, Intensive metrics for open source evolution – http://oa.upm.es/14698/ 9/13
  • 13. Apache Beehive88 kSLOC, project in the Attic (no longer under development), Intensive metrics for open source evolution – http://oa.upm.es/14698/ 10/13
  • 14. Overall comparisonAllows for comparison of projects with large differences in size, scope,technology, maturity, Intensive metrics for open source evolution – http://oa.upm.es/14698/ 11/13
  • 15. Overall comparisonLessons learnedHealthy Apache projects have smooth ratiosProjects with little activity, or small core group, are noisierPeaks to infinity are evidence of stagnation, Intensive metrics for open source evolution – http://oa.upm.es/14698/ 12/13
  • 16. Overall comparisonLessons learnedHealthy Apache projects have smooth ratiosProjects with little activity, or small core group, are noisierPeaks to infinity are evidence of stagnationUser-oriented projectsEvolution:Starts with high valuesStabilize and matures with 3 <ratio< 8Developer-oriented projectsEvolution:Smaller community, no peaksAlways within 3 <ratio< 8, Intensive metrics for open source evolution – http://oa.upm.es/14698/ 12/13
  • 17. Conclusions and further workMetricIntensive and expressive metric.Not depending on size, maturity,scope or technology.End-usersMore suitable for users-orientedprojects. Ratio works better withlarge and active communities.StagnationCan identify stagnated projects.Can signal potential stagnationthreats.Other ratios, other casesDevel-only messages, issues,commits complexity.Study beyond the ASF., Intensive metrics for open source evolution – http://oa.upm.es/14698/ 13/13
  • 18. Conclusions and further workMetricIntensive and expressive metric.Not depending on size, maturity,scope or technology.End-usersMore suitable for users-orientedprojects. Ratio works better withlarge and active communities.StagnationCan identify stagnated projects.Can signal potential stagnationthreats.Other ratios, other casesDevel-only messages, issues,commits complexity.Study beyond the ASF.Get a preprint of the paper at http://oa.upm.es/14698Replication packagehttp://gsyc.es/∼grex/repro/2013-apache-intensive/, Intensive metrics for open source evolution – http://oa.upm.es/14698/ 13/13