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Recommendation and Regression Test Suite Optimization Using Heuristic Algorithms

Published: 18 February 2015 Publication History

Abstract

In the Software Development Life Cycle, testing is an integral and important phase. It is estimated that close to 45% of project cost is marked for testing. Defect removal efficiency is directly proportional to the rigor of the testing and number of test cycles. Given this prelude, important optimization dual is to reduce the testing time and cost without compromising on the quality and coverage. We revisit this popular research and industry sought problem, in the historical data perspective. For this, it is important to follow an approach and minimize the available test suites and recommend N Test cases based on multiple heuristics. The heuristics can be derived based on Test Manager, Test Lead and/or Test Director requirements and inputs. The N test cases that are to be recommended will be derived upon executing evolutionary randomized algorithms such as Random Forest / Genetic Algorithm. These algorithms fed with historically derived inputs such as test case execution frequency, test case failure pattern, change feature pattern and bug fixes & associations. The recommended test suite is further optimized based on a 2 dimensional approach. Test case specific vertical constraints such as distribution of environments, distribution of features as well as Test suite composition parameters such as golden test cases, sanity test cases, that serves as horizontal parameters.

References

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Sriraman Tallam, Neelam Gupta - "A Concept Analysis Inspired Greedy Algorithm for Test Suite Minimization", ACM SIGPLAN-SIGSOFT Workshop on Program Analysis for Software Tools and Engineering (PASTE 2005), Lisbon, Portugal, Sep. 2005
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Farooq, U.; Lam, C.P., - "Evolving the Quality of a Model Based Test Suite", Software Testing, Verification and Validation Workshops, 2009. ICSTW '09. International Conference on, vol., no., pp. 141, 149, 1-4 April 2009
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Misha Denil, David Matheson, Nando de Freitas, University of Oxford, United Kingdom - "Narrowing the Gap: Random Forests In Theory and In Practice", Proceedings of the 31st International Conference on Machine Learning, Beijing, China, 2014. JMLR: W&CP Volume 32, October 2013.
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K. R. Walcott, walcott-GAprioritizations - "Prioritizing regression test suites for time-constrained execution using a genetic algorithm", CS05-11, Department of Computer Science, Allegheny College, Meadville, PA, 2005.
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Bharti Suri, Isha Mangal, Varun Srivastava - "Regression Test Suite Reduction using an Hybrid Technique Based on BCO And Genetic Algorithm", Special Issue of International Journal of Computer Science & Informatics (IJCSI), ISSN (PRINT): 2231--5292, Vol.- II, Issue-1, 2.
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Zeeshan Anwar, Ali Ahsan (2014) Exploration and analysis of regression test suite optimization ACM SIGSOFT Software Engineering Notes 39-1.

Cited By

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  • (2018)A Literature Survey of Applications of Meta-heuristic Techniques in Software TestingSoftware Engineering10.1007/978-981-10-8848-3_47(497-505)Online publication date: 13-Jun-2018
  • (2015)A novel dynamic analysis of test cases to improve testing efficiency in object-oriented systems2015 4th International Conference on Computer Science and Network Technology (ICCSNT)10.1109/ICCSNT.2015.7490789(457-461)Online publication date: Dec-2015

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ISEC '15: Proceedings of the 8th India Software Engineering Conference
February 2015
207 pages
ISBN:9781450334327
DOI:10.1145/2723742
Permission to make digital or hard copies of part or all 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 third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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  • iSOFT: iSOFT
  • ACM India: ACM India

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 18 February 2015

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Author Tags

  1. Greedy Algorithm
  2. Optimization
  3. Random Forest
  4. Regression Test
  5. Test coverage
  6. Test failure prediction

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ISEC '15
ISEC '15: 8th India Software Engineering Conference
February 18 - 20, 2015
Bangalore, India

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Overall Acceptance Rate 76 of 315 submissions, 24%

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Cited By

View all
  • (2018)A Literature Survey of Applications of Meta-heuristic Techniques in Software TestingSoftware Engineering10.1007/978-981-10-8848-3_47(497-505)Online publication date: 13-Jun-2018
  • (2015)A novel dynamic analysis of test cases to improve testing efficiency in object-oriented systems2015 4th International Conference on Computer Science and Network Technology (ICCSNT)10.1109/ICCSNT.2015.7490789(457-461)Online publication date: Dec-2015

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