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Investigation and Automation of Cost Reduction Techniques for Mutation Testing

Grant number: 16/21251-0
Support Opportunities:Scholarships abroad - Research
Effective date (Start): October 01, 2017
Effective date (End): September 30, 2018
Field of knowledge:Physical Sciences and Mathematics - Computer Science - Computing Methodologies and Techniques
Principal Investigator:Fabiano Cutigi Ferrari
Grantee:Fabiano Cutigi Ferrari
Host Investigator: Andrew Jefferson Offutt
Host Institution: Centro de Ciências Exatas e de Tecnologia (CCET). Universidade Federal de São Carlos (UFSCAR). São Carlos , SP, Brazil
Research place: George Mason University, United States  


Context: The Mutant Analysis test selection criterion, also known as mutation testing, is an important option for the evaluation of both software systems and test sets that are used to validate them. However, mutation testing imposes high application cost. Due to this, cost reduction techniques are on focus, aiming at reducing significantly the cost of this criterion, without compromising the quality of derived test sets.Problem Definition: Results yielded by such cost reduction techniques are valid only for restricted groups of programs, as highlighted in related research. The question that persists regards the usefulness of such results to be applied to untested programs.Goal: The general aim of this proposal is the definition of a strategy for the application of cost reduction techniques for mutation testing that reuses empirical knowledge gathered from previous studies.Method: Initially, we will characterise the state-of-the-art with respect to cost reduction techniques for mutation testing. We will rank the best techniques in order to define a strategy for their application. The intended strategy will tank into account the similarity between tested programs and programs to which cost reduction techniques will be applied. Results will be assessed with respect to the quality of the newly created tests.

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Scientific publications
(References retrieved automatically from Web of Science and SciELO through information on FAPESP grants and their corresponding numbers as mentioned in the publications by the authors)
PIZZOLETO, ALESSANDRO VIOLA; FERRARI, FABIANO CUTIGI; OFFUTT, JEFF; FERNANDES, LEO; RIBEIRO, MARCIO. A systematic literature review of techniques and metrics to reduce the cost of mutation testing. JOURNAL OF SYSTEMS AND SOFTWARE, v. 157, . (16/21251-0)
PINHEIRO, PEDRO; VIANA, JOSE CARLOS; RIBEIRO, MARCIO; FERNANDES, LEO; FERRARI, FABIANO; GHEYI, ROHIT; FONSECA, BALDOINO. Mutating code annotations: An empirical evaluation on Java and C# programs. SCIENCE OF COMPUTER PROGRAMMING, v. 191, . (16/21251-0)

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