Abstract

Equivalent mutants (EM) issue is a key challenge in mutation testing. Many methods were applied for detecting and reducing the equivalent mutants. These methods are classified into four classes: equivalent mutant detection, avoiding the generation of equivalent mutants, higher-order equivalent mutants, and suggesting equivalent mutants. Higher-order mutation testing (HOMT) is considered the strongest employed technique in avoiding the generation of equivalent mutants and reduction of their number. In this paper, a combination of HOMT especially second-order mutation testing (SOMT) and dynamic symbolic execution (DSE) techniques are applied for the automatic detection and reduction of the equivalent second-order mutants. First, SOMT is used to reduce the number of equivalent mutants. Second, DSE technique is applied to classify the SOMs and detect EM. To assess the efficiency of the proposed technique, it is applied to some subject programs and the results of this technique are compared to the manual results and those of related works. The results showed that the proposed algorithm is more effective in detecting and reducing the number of EM. It detects 94% from the equivalent mutants that have manually analyzed. This percentage is a high percentage comparing with previous studies. Besides, the DEM-DSE technique detects 100% of equivalent mutants for 9 of the 14 subject programs.

Highlights

  • Mutation testing (MT) depends on the idea of generating one or more mutated versions for the source program to use them in estimating the quality of the test suite

  • EXPERIMENTAL SETUP AND RESULTS This section gives the details of the conducted experiment to assess the proposed DEM-dynamic symbolic execution (DSE) technique for detecting equivalent first and second-order mutants (EFOMs and ESOMs)

  • Our technique classifies the 5577 SOMs mutants into 224 equivalent mutants, 98 strong mutants, 2187 normal mutants, and 3068 naïve mutants (Table 9). 4) EVALUATE THE EFFECTIVENESS oF OUR Detecting Equivalent Mutants using Dynamic Symbolic Execution (DEM-DSE) TECHNIQUE In this stage, we evaluate our technique based on the manual results and the previous results [21]

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Summary

INTRODUCTION

Mutation testing (MT) depends on the idea of generating one or more mutated versions for the source program to use them in estimating the quality of the test suite. Bearing these ideas in mind, the current study aims to solve the EM problem through detecting and reducing the number of second-order EM For this reason, this paper proposes a new technique using the SOM testing techniques [18] and the DSE techniques [19], [20]. Detecting equivalent mutants in this work depends on executing the source code and its mutants concretely and symbolically at the same time (which called DSE) and compare between them through the information that collected about them during that execution. This technique considers the mutant surely ‘‘Killed’’ when the information is different and the mutant is reached.

RELATED WORK
EXPERIMENTAL SETUP AND RESULTS
THREATS TO VALIDITY
Findings
CONCLUSION
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