Article

Integrated impact analysis for managing software changes

Authors:

Malcom Gethers,

Denys PoshyvanykAuthors Info & Claims

ICSE '12: Proceedings of the 34th International Conference on Software Engineering

Pages 430 - 440

Published: 02 June 2012 Publication History

Abstract

The paper presents an adaptive approach to perform impact analysis from a given change request to source code. Given a textual change request (e.g., a bug report), a single snapshot (release) of source code, indexed using Latent Semantic Indexing, is used to estimate the impact set. Should additional contextual information be available, the approach configures the best-fit combination to produce an improved impact set. Contextual information includes the execution trace and an initial source code entity verified for change. Combinations of information retrieval, dynamic analysis, and data mining of past source code commits are considered. The research hypothesis is that these combinations help counter the precision or recall deficit of individual techniques and improve the overall accuracy. The tandem operation of the three techniques sets it apart from other related solutions. Automation along with the effective utilization of two key sources of developer knowledge, which are often overlooked in impact analysis at the change request level, is achieved.

To validate our approach, we conducted an empirical evaluation on four open source software systems. A benchmark consisting of a number of maintenance issues, such as feature requests and bug fixes, and their associated source code changes was established by manual examination of these systems and their change history. Our results indicate that there are combinations formed from the augmented developer contextual information that show statistically significant improvement over stand-alone approaches.

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Cited By

Sharma ANasre RZhang DMøller A(2019)QADroid: regression event selection for Android applicationsProceedings of the 28th ACM SIGSOFT International Symposium on Software Testing and Analysis10.1145/3293882.3330550(66-77)Online publication date: 10-Jul-2019
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Zhou DWu YXiao LCai YPeng XFan JHuang LChen HGuéhéneuc YKhomh FSarro F(2019)Understanding evolutionary coupling by fine-grained co-change relationship analysisProceedings of the 27th International Conference on Program Comprehension10.1109/ICPC.2019.00046(271-282)Online publication date: 25-May-2019
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Wang WHe YLi TZhu JLiu J(2018)An Integrated Model for Information Retrieval Based Change Impact AnalysisScientific Programming10.1155/2018/59136342018(5)Online publication date: 1-Mar-2018
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Information & Contributors

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Published In

cover image ACM Conferences

ICSE '12: Proceedings of the 34th International Conference on Software Engineering

June 2012

1657 pages

ISBN:9781467310673

General Chair:
Martin Glinz,
Program Chairs:
Gail Murphy,
Mauro Pezzè

Sponsors

SIGSOFT: ACM Special Interest Group on Software Engineering

Publisher

IEEE Press

Publication History

Published: 02 June 2012

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ICSE '12

Sponsor:

SIGSOFT

ICSE '12: 34th International Conference on Software Engineering

June 2 - 9, 2012

Zurich, Switzerland

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Overall Acceptance Rate 276 of 1,856 submissions, 15%

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Cited By

Sharma ANasre RZhang DMøller A(2019)QADroid: regression event selection for Android applicationsProceedings of the 28th ACM SIGSOFT International Symposium on Software Testing and Analysis10.1145/3293882.3330550(66-77)Online publication date: 10-Jul-2019
https://dl.acm.org/doi/10.1145/3293882.3330550
Zhou DWu YXiao LCai YPeng XFan JHuang LChen HGuéhéneuc YKhomh FSarro F(2019)Understanding evolutionary coupling by fine-grained co-change relationship analysisProceedings of the 27th International Conference on Program Comprehension10.1109/ICPC.2019.00046(271-282)Online publication date: 25-May-2019
https://dl.acm.org/doi/10.1109/ICPC.2019.00046
Wang WHe YLi TZhu JLiu J(2018)An Integrated Model for Information Retrieval Based Change Impact AnalysisScientific Programming10.1155/2018/59136342018(5)Online publication date: 1-Mar-2018
https://dl.acm.org/doi/10.1155/2018/5913634
Wood ARodeghero PArmaly AMcMillan CLeavens GGarcia APăsăreanu C(2018)Detecting speech act types in developer question/answer conversations during bug repairProceedings of the 2018 26th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering10.1145/3236024.3236031(491-502)Online publication date: 26-Oct-2018
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Yang GJones JMoninger AChe MJulien CLewis GSegall I(2018)How do Android operating system updates impact apps?Proceedings of the 5th International Conference on Mobile Software Engineering and Systems10.1145/3197231.3197258(156-160)Online publication date: 27-May-2018
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Akbarinasaji S(2018)Prioritizing lingering bugsACM SIGSOFT Software Engineering Notes10.1145/3178315.317832643:1(1-6)Online publication date: 28-Mar-2018
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Azizi MDo HHaddad HWainwright RChbeir R(2018)A collaborative filtering recommender system for test case prioritization in web applicationsProceedings of the 33rd Annual ACM Symposium on Applied Computing10.1145/3167132.3167299(1560-1567)Online publication date: 9-Apr-2018
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Liu XHuang LEgyed AGe J(2018)Do code data sharing dependencies support an early prediction of software actual change impact set?Journal of Software: Evolution and Process10.1002/smr.196030:11Online publication date: 14-Nov-2018
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Tanveer BMendes ECounsell SPetersen K(2017)Guidelines for utilizing change impact analysis when estimating effort in agile software developmentProceedings of the 21st International Conference on Evaluation and Assessment in Software Engineering10.1145/3084226.3084284(252-257)Online publication date: 15-Jun-2017
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Kabeer SNayebi MRuhe GCarlson CChew FBener ATurhan BBiffl S(2017)Predicting the vector impact of changeProceedings of the 11th ACM/IEEE International Symposium on Empirical Software Engineering and Measurement10.1109/ESEM.2017.20(131-140)Online publication date: 9-Nov-2017
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