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Generating Mutants to Improve Test Suites: A Search-Based Approach

Barati, Babak | 2018

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  1. Type of Document: M.Sc. Thesis
  2. Language: Farsi
  3. Document No: 51214 (19)
  4. University: Sharif University of Technology
  5. Department: Computer Engineering
  6. Advisor(s): Mirian-Hosseinabadi, Hassan
  7. Abstract:
  8. Mutation testing is known to be one of the best strategies to improve the quality of test suites, consequently the quality of the software. However, some challenges make mutaton testing unpractical. One of the main challenges confronting mutation testing is that it demands exhustive computation and is time consuming because of the large number of mutants that need to be compiled and executed on the test cases of the test suite. Many researches have been conducted to reduce the number of mutants without losing the main characteristics of the all possible mutants. Most of these researches select the mutants without considering the characteristics of the test suite, therefore the reduced set of mutants may lack some of the mutants that could reveal the flaws of the test cases. In the approach offered by this research, considering the given test suite, using a search-based algorithm, a reduced set of mutations is selected which probably cannot be killed by the test cases or are killed by only by a few test cases. In this research we present the test-centered mutation reduction approach. In this approach, a fitness function is defined based on the characteristics of the execution of the test cases. A genetic algorithm uses this fitness function to find the best mutants that can challenge the test suite. The comparition between the test-centered and random approach indicates that our approach is successful on selecting mutants that are not killed or killed by less test cases
  9. Keywords:
  10. Software Testing ; Mutation Testing ; Genetic Algorithm ; Software Quality Assurance ; Search Based Testing

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