The Impact of Task Granularity on Co-evolution Analyses

Keisuke Miura, Shane McIntosh, Yasutaka Kamei, Ahmed E. Hassan, Naoyasu Ubayashi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

Background: Substantial research in the software evolution field aims to recover knowledge about development from the project history that is archived in repositories, such as a Version Control System (VCS). However, the data that is archived in these repositories can be analyzed at different levels of granularity. Although software evolution is a well-studied phenomenon at the revision-level, revisions may be too fine-grained to accurately represent development tasks. Aim: In this paper, we set out to understand the impact that the revision granularity has on co-change analyses. Method: We conduct an empirical study of 14 open source systems that are developed by the Apache Software Foundation. To understand the impact that the revision granularity may have on co-change activity, we study work items, i.e., logical groups of revisions that address a single issue. Results: We find that work item grouping has the potential to impact co-change activity, since 29% of work items consist of 2 or more revisions in 7 of the 14 studied systems. Deeper quantitative analysis shows that, in 7 of the 14 studied systems: (1) 11% of largest work items are entirely composed of small revisions, and would be missed by traditional approaches to filter or analyze large changes, (2) 83% of revisions that co-change under a single work item cannot be grouped using the typical configuration of the sliding time window technique and (3) 48% of work items that involve multiple developers cannot be grouped at the revision-level. Conclusions: Since the work item granularity is the natural means that practitioners use to separate development tasks, future software evolution studies, especially co-change analyses, should be conducted at the work item level.

Original languageEnglish
Title of host publication10th ACM/IEEE International Symposium on Empirical Software Engineering and Measurement, ESEM 2016
PublisherIEEE Computer Society
Volume08-09-September-2016
ISBN (Electronic)9781450344272
DOIs
Publication statusPublished - Sep 8 2016
Event10th ACM/IEEE International Symposium on Empirical Software Engineering and Measurement, ESEM 2016 - Ciudad Real, Spain
Duration: Sep 8 2016Sep 9 2016

Other

Other10th ACM/IEEE International Symposium on Empirical Software Engineering and Measurement, ESEM 2016
CountrySpain
CityCiudad Real
Period9/8/169/9/16

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Control systems
Chemical analysis

All Science Journal Classification (ASJC) codes

  • Computer Science Applications
  • Software

Cite this

Miura, K., McIntosh, S., Kamei, Y., Hassan, A. E., & Ubayashi, N. (2016). The Impact of Task Granularity on Co-evolution Analyses. In 10th ACM/IEEE International Symposium on Empirical Software Engineering and Measurement, ESEM 2016 (Vol. 08-09-September-2016). [a47] IEEE Computer Society. https://doi.org/10.1145/2961111.2962607

The Impact of Task Granularity on Co-evolution Analyses. / Miura, Keisuke; McIntosh, Shane; Kamei, Yasutaka; Hassan, Ahmed E.; Ubayashi, Naoyasu.

10th ACM/IEEE International Symposium on Empirical Software Engineering and Measurement, ESEM 2016. Vol. 08-09-September-2016 IEEE Computer Society, 2016. a47.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Miura, K, McIntosh, S, Kamei, Y, Hassan, AE & Ubayashi, N 2016, The Impact of Task Granularity on Co-evolution Analyses. in 10th ACM/IEEE International Symposium on Empirical Software Engineering and Measurement, ESEM 2016. vol. 08-09-September-2016, a47, IEEE Computer Society, 10th ACM/IEEE International Symposium on Empirical Software Engineering and Measurement, ESEM 2016, Ciudad Real, Spain, 9/8/16. https://doi.org/10.1145/2961111.2962607
Miura K, McIntosh S, Kamei Y, Hassan AE, Ubayashi N. The Impact of Task Granularity on Co-evolution Analyses. In 10th ACM/IEEE International Symposium on Empirical Software Engineering and Measurement, ESEM 2016. Vol. 08-09-September-2016. IEEE Computer Society. 2016. a47 https://doi.org/10.1145/2961111.2962607
Miura, Keisuke ; McIntosh, Shane ; Kamei, Yasutaka ; Hassan, Ahmed E. ; Ubayashi, Naoyasu. / The Impact of Task Granularity on Co-evolution Analyses. 10th ACM/IEEE International Symposium on Empirical Software Engineering and Measurement, ESEM 2016. Vol. 08-09-September-2016 IEEE Computer Society, 2016.
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abstract = "Background: Substantial research in the software evolution field aims to recover knowledge about development from the project history that is archived in repositories, such as a Version Control System (VCS). However, the data that is archived in these repositories can be analyzed at different levels of granularity. Although software evolution is a well-studied phenomenon at the revision-level, revisions may be too fine-grained to accurately represent development tasks. Aim: In this paper, we set out to understand the impact that the revision granularity has on co-change analyses. Method: We conduct an empirical study of 14 open source systems that are developed by the Apache Software Foundation. To understand the impact that the revision granularity may have on co-change activity, we study work items, i.e., logical groups of revisions that address a single issue. Results: We find that work item grouping has the potential to impact co-change activity, since 29{\%} of work items consist of 2 or more revisions in 7 of the 14 studied systems. Deeper quantitative analysis shows that, in 7 of the 14 studied systems: (1) 11{\%} of largest work items are entirely composed of small revisions, and would be missed by traditional approaches to filter or analyze large changes, (2) 83{\%} of revisions that co-change under a single work item cannot be grouped using the typical configuration of the sliding time window technique and (3) 48{\%} of work items that involve multiple developers cannot be grouped at the revision-level. Conclusions: Since the work item granularity is the natural means that practitioners use to separate development tasks, future software evolution studies, especially co-change analyses, should be conducted at the work item level.",
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N2 - Background: Substantial research in the software evolution field aims to recover knowledge about development from the project history that is archived in repositories, such as a Version Control System (VCS). However, the data that is archived in these repositories can be analyzed at different levels of granularity. Although software evolution is a well-studied phenomenon at the revision-level, revisions may be too fine-grained to accurately represent development tasks. Aim: In this paper, we set out to understand the impact that the revision granularity has on co-change analyses. Method: We conduct an empirical study of 14 open source systems that are developed by the Apache Software Foundation. To understand the impact that the revision granularity may have on co-change activity, we study work items, i.e., logical groups of revisions that address a single issue. Results: We find that work item grouping has the potential to impact co-change activity, since 29% of work items consist of 2 or more revisions in 7 of the 14 studied systems. Deeper quantitative analysis shows that, in 7 of the 14 studied systems: (1) 11% of largest work items are entirely composed of small revisions, and would be missed by traditional approaches to filter or analyze large changes, (2) 83% of revisions that co-change under a single work item cannot be grouped using the typical configuration of the sliding time window technique and (3) 48% of work items that involve multiple developers cannot be grouped at the revision-level. Conclusions: Since the work item granularity is the natural means that practitioners use to separate development tasks, future software evolution studies, especially co-change analyses, should be conducted at the work item level.

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