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Replaying development history to assess the effectiveness of change propagation tools

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Abstract

As developers modify software entities such as functions or variables to introduce new features, enhance old ones, or fix bugs, they must ensure that other entities in the software system are updated to be consistent with these new changes. Many hard to find bugs are introduced by developers who did not notice dependencies between entities, and failed to propagate changes correctly. Most modern development environments offer tools to assist developers in propagating changes. For example, dependency browsers show static code dependencies between source code entities. Other sources of information such as historical co-change or code layout information could be used by tools to support developers in propagating changes. We present the Development Replay (DR) approach which empirically assess and compares the effectiveness of several not-yet-existing change propagation tools by reenacting the changes stored in source control repositories using these tools. We present a case study of five large open source systems with a total of over 40 years of development history. Our empirical results show that historical co-change information recovered from source control repositories along with code layout information can guide developers in propagating changes better than simple static dependency information.

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Notes

  1. Using a parametric paired \(t\)-test and a non-parametric paired Wilcoxon signed rank test. The \(t\)-test is performed on the square root of the precision/recall for each change set to ensure that the data has a normal distribution, a requirement for the \(t\)-test. Due to the large number of change sets used in our analysis, the normality of the data is not a major concern as the \(t\)-test is a robust test. Nevertheless we ensure the normality to guarantee the validity of our results.

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Acknowledgments

The authors gratefully acknowledge the significant contributions from the members of the open source community who have given freely of their time to produce large software systems with rich and detailed source code repositories; and who assisted us in understanding and acquiring these valuable repositories. They also thank Lionel Briand for his very helpful comments and suggestions to improve the statistical analysis and presentation of our results.

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Authors and Affiliations

  1. Department of Electrical and Computer Engineering, University of Victoria, Victoria, Canada

    Ahmed E. Hassan

  2. School of Computer Science, University of Waterloo, Waterloo, Canada

    Richard C. Holt

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  1. Ahmed E. Hassan
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Correspondence to Ahmed E. Hassan.

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Hassan, A.E., Holt, R.C. Replaying development history to assess the effectiveness of change propagation tools. Empir Software Eng 11, 335–367 (2006). https://doi.org/10.1007/s10664-006-9006-4

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