Intensive Metrics for the Study of the Evolution
of Open Source Projects: Case Studies from the
ASF
Santiago Gala-Pérez (A...
Metrics for Software Evolution

Common metrics are extensive
Difficult to compare projects of different size
Successful proje...
Metrics for Software Evolution

Common metrics are extensive
Difficult to compare projects of different size
Successful proje...
The case of the Apache Software Foundation
ASF members mailing list, November 29 2008
Joe Schaeffer says
something IMO inte...
Goal of the paper
Ratio Communication flow / development activity
Hypothesis: the ratio is an intensive metric for software...
Goal of the paper
Ratio Communication flow / development activity
Hypothesis: the ratio is an intensive metric for software...
ASF projects under study
Project
HTTPD
APR
Lucene
Turbine
Tomcat
Jackrabbit
Hadoop
Geronimo
SpamAssassin
Portals
Beehive

...
ASF projects under study
Project
HTTPD
APR
Lucene
Turbine
Tomcat
Jackrabbit
Hadoop
Geronimo
SpamAssassin
Portals
Beehive

...
Apache httpd
156 kSLOC, active and long lived web server

,

Intensive metrics for open source evolution – http://oa.upm.e...
Apache Portable Runtime (APR)
66 kSLOC, active and long lived library used by httpd and Subversion

,

Intensive metrics f...
Apache Hadoop
1270 kSLOC, very active development and community, higher presence of
non-human emails

,

Intensive metrics...
Apache SpamAssassin
54 kSLOC, spam filter, intended for end users, maturing project

,

Intensive metrics for open source e...
Apache Beehive
88 kSLOC, project in the Attic (no longer under development)

,

Intensive metrics for open source evolutio...
Overall comparison
Allows for comparison of projects with large differences in size, scope,
technology, maturity

,

Intens...
Overall comparison
Lessons learned
Healthy Apache projects have smooth ratios
Projects with little activity, or small core...
Overall comparison
Lessons learned
Healthy Apache projects have smooth ratios
Projects with little activity, or small core...
Conclusions and further work
Metric
Intensive and expressive metric.
Not depending on size, maturity,
scope or technology....
Conclusions and further work
Metric
Intensive and expressive metric.
Not depending on size, maturity,
scope or technology....
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Intensive metrics software evolution

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Intensive metrics software evolution

  1. 1. Intensive Metrics for the Study of the Evolution of Open Source Projects: Case Studies from the ASF Santiago Gala-Pérez (ASF), Gregorio Robles (URJC), Jesús M. González-Barahona (URJC), Israel Herraiz (UPM) 10th Working Conference on Mining Software Repositories SF, California, May 18th, 2013 Preprint 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. 2. Metrics for Software Evolution Common metrics are extensive Difficult to compare projects of different size Successful projects undergo large size changes over their lifetime Intensive metrics in natural sciences Metrics not depending on the size of system Scale invariant , Intensive metrics for open source evolution – http://oa.upm.es/14698/ 2/13
  3. 3. Metrics for Software Evolution Common metrics are extensive Difficult to compare projects of different size Successful projects undergo large size changes over their lifetime Intensive metrics in natural sciences Metrics not depending on the size of system Scale invariant Are 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. 4. The case of the Apache Software Foundation ASF members mailing list, November 29 2008 Joe Schaeffer says something IMO interesting about the ASF: the fact that the number of commits and the number of mailing list posts have grown in linear relationship [...] over the years. , Intensive metrics for open source evolution – http://oa.upm.es/14698/ 3/13
  5. 5. Goal of the paper Ratio Communication flow / development activity Hypothesis: the ratio is an intensive metric for software evolution It varies with Maturity, technology, community composition But not with project source code size , Intensive metrics for open source evolution – http://oa.upm.es/14698/ 4/13
  6. 6. Goal of the paper Ratio Communication flow / development activity Hypothesis: the ratio is an intensive metric for software evolution It varies with Maturity, technology, community composition But not with project source code size Case study: the ASF Broad and diverse range of projects Size, scope, technology, maturity If it didn’t happen on-list, it didn’t happen Communications between developers (decisions) Issue trackers Code review tools, automated builds, wiki page edits Commits , Intensive metrics for open source evolution – http://oa.upm.es/14698/ 4/13
  7. 7. ASF projects under study Project HTTPD APR Lucene Turbine Tomcat Jackrabbit Hadoop Geronimo SpamAssassin Portals Beehive , kSLOC 156 66 414 41 213 344 1270 370 54 202 88 Technology Web server Library Index & search Java web fwork Servlet API JSR-170 ref. impl. Big Data JavaEE app. srv. Spam filter Web fwork J2EE Struts Maturity Active, long-lived Active, long-lived Active, long-lived Stagnated Active, long-lived Active Very active Active, long-lived Mature Nearly dead Attic Intensive metrics for open source evolution – http://oa.upm.es/14698/ Scope Users Devs Users Devs Devs Devs Devs Devs End users Devs Devs 5/13
  8. 8. ASF projects under study Project HTTPD APR Lucene Turbine Tomcat Jackrabbit Hadoop Geronimo SpamAssassin Portals Beehive kSLOC 156 66 414 41 213 344 1270 370 54 202 88 Technology Web server Library Index & search Java web fwork Servlet API JSR-170 ref. impl. Big Data JavaEE app. srv. Spam filter Web fwork J2EE Struts Maturity Active, long-lived Active, long-lived Active, long-lived Stagnated Active, long-lived Active Very active Active, long-lived Mature Nearly dead Attic Scope Users Devs Users Devs Devs Devs Devs Devs End users Devs Devs Ratio What’s the ratio evolution for these projects? , Intensive metrics for open source evolution – http://oa.upm.es/14698/ 5/13
  9. 9. Apache httpd 156 kSLOC, active and long lived web server , Intensive metrics for open source evolution – http://oa.upm.es/14698/ 6/13
  10. 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. 11. Apache Hadoop 1270 kSLOC, very active development and community, higher presence of non-human emails , Intensive metrics for open source evolution – http://oa.upm.es/14698/ 8/13
  12. 12. Apache SpamAssassin 54 kSLOC, spam filter, intended for end users, maturing project , Intensive metrics for open source evolution – http://oa.upm.es/14698/ 9/13
  13. 13. Apache Beehive 88 kSLOC, project in the Attic (no longer under development) , Intensive metrics for open source evolution – http://oa.upm.es/14698/ 10/13
  14. 14. Overall comparison Allows 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. 15. Overall comparison Lessons learned Healthy Apache projects have smooth ratios Projects with little activity, or small core group, are noisier Peaks to infinity are evidence of stagnation , Intensive metrics for open source evolution – http://oa.upm.es/14698/ 12/13
  16. 16. Overall comparison Lessons learned Healthy Apache projects have smooth ratios Projects with little activity, or small core group, are noisier Peaks to infinity are evidence of stagnation User-oriented projects Evolution: Starts with high values Stabilize and matures with 3 <ratio< 8 Developer-oriented projects Evolution: Smaller community, no peaks Always within 3 <ratio< 8 , Intensive metrics for open source evolution – http://oa.upm.es/14698/ 12/13
  17. 17. Conclusions and further work Metric Intensive and expressive metric. Not depending on size, maturity, scope or technology. End-users More suitable for users-oriented projects. Ratio works better with large and active communities. , Stagnation Other ratios, other cases Devel-only messages, issues, commits complexity. Study beyond the ASF. Can identify stagnated projects. Can signal potential stagnation threats. Intensive metrics for open source evolution – http://oa.upm.es/14698/ 13/13
  18. 18. Conclusions and further work Metric Intensive and expressive metric. Not depending on size, maturity, scope or technology. Stagnation End-users More suitable for users-oriented projects. Ratio works better with large and active communities. Other ratios, other cases Devel-only messages, issues, commits complexity. Study beyond the ASF. Can identify stagnated projects. Can signal potential stagnation threats. Get a preprint of the paper at http://oa.upm.es/14698 Replication package http://gsyc.es/∼grex/repro/2013-apache-intensive/ , Intensive metrics for open source evolution – http://oa.upm.es/14698/ 13/13

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