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Redundancy-free analysis of multi-revision software artifacts

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Abstract

Researchers often analyze several revisions of a software project to obtain historical data about its evolution. For example, they statically analyze the source code and monitor the evolution of certain metrics over multiple revisions. The time and resource requirements for running these analyses often make it necessary to limit the number of analyzed revisions, e.g., by only selecting major revisions or by using a coarse-grained sampling strategy, which could remove significant details of the evolution. Most existing analysis techniques are not designed for the analysis of multi-revision artifacts and they treat each revision individually. However, the actual difference between two subsequent revisions is typically very small. Thus, tools tailored for the analysis of multiple revisions should only analyze these differences, thereby preventing re-computation and storage of redundant data, improving scalability and enabling the study of a larger number of revisions. In this work, we propose the Lean Language-Independent Software Analyzer (LISA), a generic framework for representing and analyzing multi-revisioned software artifacts. It employs a redundancy-free, multi-revision representation for artifacts and avoids re-computation by only analyzing changed artifact fragments across thousands of revisions. The evaluation of our approach consists of measuring the effect of each individual technique incorporated, an in-depth study of LISA resource requirements and a large-scale analysis over 7 million program revisions of 4,000 software projects written in four languages. We show that the time and space requirements for multi-revision analyses can be reduced by multiple orders of magnitude, when compared to traditional, sequential approaches.

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Notes

  1. http://www.eclipse.org/

  2. https://doi.org/10.5281/zenodo.1211549

  3. https://bitbucket.org/sealuzh/lisa

  4. The top 500 sites on the web. http://web.archive.org/web/20170626103223/http://www.alexa.com/topsites. Accessed 26 June 2017

  5. For example, https://github.com/antlr/grammars-v4 contains grammar files for over 60 structured file formats.

  6. See http://goo.gl/7grx8L for more information on the performance of Scala collections.

  7. SuperMicro SuperServer 4048B-TR4FT, 64 Intel Xeon E7-4850 CPUs with 128 threads, 3TB memory in total

  8. The example projects for each language, ending in ‘-example-repository‘, can be found online at https://bitbucket.org/account/user/sealuzh/projects/LISA

  9. Awesome python. https://github.com/vinta/awesome-python. Accessed 20 June 2017

  10. We analyzed 30,000 GitHub projects – here are the top 100 libraries in Java, JS and Ruby. http://blog.takipi.com/we-analyzed-30000-github-projects-here-are-the-top-100-libraries-in-java-js-and-ruby/. Accessed 20 March 2016

  11. The JSON representation can be found in the repository, here: https://goo.gl/oMDxzv

  12. All parser integrations and mappings can be found here: https://goo.gl/6pT7sG

  13. Infusion by Intooitus s.r.l. http://www.intooitus.com/products/infusion. Accessed 30 March 2014

  14. These are the handicap-* branches visible in the LISA open source repository

  15. This demonstration is part of the lisa-quickstart repository: https://bitbucket.org/sealuzh/lisa-quickstart/

  16. https://neo4j.com/, http://rdf4j.org/

  17. http://goo.gl/aWWCkN

  18. http://goo.gl/VftJUW

  19. OMG: KDM. http://www.omg.org/spec/KDM/1.3/. Accessed 6 October 2016

  20. OMG: ASTM. http://www.omg.org/spec/ASTM/1.0/. Accessed 6 October 2016

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Acknowledgements

We thank the reviewers for their valuable feedback. This research is partially supported by the Swiss National Science Foundation (Projects No. 149450 – “Whiteboard” and No. 166275 – “SURF-MobileAppsData”) and the Swiss Group for Original and Outside-the-box Software Engineering (CHOOSE).

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  1. Software Evolution and Architecture Lab - s.e.a.l., Binzmühlestrasse 14, CH-8050, Zürich, Switzerland

    Carol V. Alexandru, Sebastiano Panichella, Sebastian Proksch & Harald C. Gall

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  1. Carol V. Alexandru
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  2. Sebastiano Panichella
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  3. Sebastian Proksch
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Correspondence to Carol V. Alexandru.

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Alexandru, C.V., Panichella, S., Proksch, S. et al. Redundancy-free analysis of multi-revision software artifacts. Empir Software Eng 24, 332–380 (2019). https://doi.org/10.1007/s10664-018-9630-9

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