Efﬁcient Generation of Mutants for Testing Execution Time
Abstract: In this thesis, we specifically focus on testing non-functional proprieties. We target the Worst-Case Execution Time (WCET), which is very important for real-time tasks. This thesis applies the concept of targeted mutation, where the mutations are applied to the parts of the code that are most likely to signiﬁcantly affect the execution time. Moreover, program slicing is used to direct the mutations to the code parts that are likely to have the strongest inﬂuence on execution time. The main contribution of the thesis is to implement the method for the experimental evaluation of the targeted mutation testing. This thesis confirms the relevance of the concept of targeted mutation by showing that targeted mutation enables the design of effective test suites for WCET estimation and improves the efficiency of this process by reducing the number of mutants. To experiment the method, we used two C benchmarks from Mälardalen University benchmarks, The first benchmark is Janne-complex code, it consists of 20 line of code and 10 test cases, This benchmark contains two loops, where the inner loop max number of iterations depends on the outer loop current iterations. The results correspond to something Janne flow-analysis should produce. Where the second benchmark is Ludcmp, it consists of 50 lines of code and 9 test cases. This benchmark is a simultaneous linear equation by LU decomposition; it contains two arrays for input and one array for output. However, the number of equations determined by the variable (n). However, both benchmarks LOC decreased after slicing, and each test case applied ten times against each mutant to eliminate the effect of cache and other applications currently running since our experiments depend on estimation of the WCET. The thesis confirms the relevance of the concept of targeted mutation by showing that targeted mutation (i) encourages the design of effective test suites for WCET estimation and (ii) improves the efficiency of this process by reducing the number of mutants.
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