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Code coverage analysis in practice for large systems

Published: 21 May 2011 Publication History

Abstract

Large systems generate immense quantities of code coverage data. A user faced with the task of analyzing this data, for example, to decide on test areas to improve, faces a 'needle in a haystack' problem.
In earlier studies we introduced substring hole analysis, a technique for presenting large quantities of coverage data in a succinct way. Here we demonstrate the successful use of substring hole analysis on large scale data from industrial software systems. For this end we augment substring hole analysis by introducing a work flow and tool support for practical code coverage analysis.
We conduct real data experiments indicating that augmented substring hole analysis enables code coverage analysis where it was previously impractical, correctly identifies functionality that is missing from existing tests, and can increase the probability of finding bugs. These facilitate cost-effective code coverage analysis.

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  • (2024)Efficient Incremental Code Coverage Analysis for Regression Test SuitesProceedings of the 39th IEEE/ACM International Conference on Automated Software Engineering10.1145/3691620.3695551(1882-1894)Online publication date: 27-Oct-2024
  • (2024)Integrating Mutation Testing Into Developer Workflow: An Industrial Case StudyProceedings of the 39th IEEE/ACM International Conference on Automated Software Engineering10.1145/3691620.3695273(2110-2120)Online publication date: 27-Oct-2024
  • (2023)Input and Output Coverage Needed in File System TestingProceedings of the 15th ACM Workshop on Hot Topics in Storage and File Systems10.1145/3599691.3603405(93-101)Online publication date: 9-Jul-2023
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cover image ACM Conferences
ICSE '11: Proceedings of the 33rd International Conference on Software Engineering
May 2011
1258 pages
ISBN:9781450304450
DOI:10.1145/1985793
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 21 May 2011

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Author Tags

  1. code coverage analysis
  2. substring hole analysis
  3. system test

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  • Research-article

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ICSE11
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ICSE11: International Conference on Software Engineering
May 21 - 28, 2011
HI, Waikiki, Honolulu, USA

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

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Cited By

View all
  • (2024)Efficient Incremental Code Coverage Analysis for Regression Test SuitesProceedings of the 39th IEEE/ACM International Conference on Automated Software Engineering10.1145/3691620.3695551(1882-1894)Online publication date: 27-Oct-2024
  • (2024)Integrating Mutation Testing Into Developer Workflow: An Industrial Case StudyProceedings of the 39th IEEE/ACM International Conference on Automated Software Engineering10.1145/3691620.3695273(2110-2120)Online publication date: 27-Oct-2024
  • (2023)Input and Output Coverage Needed in File System TestingProceedings of the 15th ACM Workshop on Hot Topics in Storage and File Systems10.1145/3599691.3603405(93-101)Online publication date: 9-Jul-2023
  • (2019)Code coverage at GoogleProceedings of the 2019 27th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering10.1145/3338906.3340459(955-963)Online publication date: 12-Aug-2019
  • (2018)An automated approach to estimating code coverage measures via execution logsProceedings of the 33rd ACM/IEEE International Conference on Automated Software Engineering10.1145/3238147.3238214(305-316)Online publication date: 3-Sep-2018
  • (2017)Automated test input generation for AndroidProceedings of the 39th International Conference on Software Engineering: Software Engineering in Practice Track10.1109/ICSE-SEIP.2017.32(253-262)Online publication date: 20-May-2017
  • (2017)Boosted decision trees for behaviour mining of concurrent programmesConcurrency and Computation: Practice and Experience10.1002/cpe.426829:21Online publication date: 31-Aug-2017
  • (2014)CodeCoverACM SIGSOFT Software Engineering Notes10.1145/2557833.255785039:1(1-4)Online publication date: 11-Feb-2014

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