Abd-Elkawy, E.H.; Ahmed, R. Empirical Comparison of Higher-Order Mutation Testing and Data-Flow Testing of C# with the Aid of Genetic Algorithm. Appl. Sci.2023, 13, 9170.
Abd-Elkawy, E.H.; Ahmed, R. Empirical Comparison of Higher-Order Mutation Testing and Data-Flow Testing of C# with the Aid of Genetic Algorithm. Appl. Sci. 2023, 13, 9170.
Abd-Elkawy, E.H.; Ahmed, R. Empirical Comparison of Higher-Order Mutation Testing and Data-Flow Testing of C# with the Aid of Genetic Algorithm. Appl. Sci.2023, 13, 9170.
Abd-Elkawy, E.H.; Ahmed, R. Empirical Comparison of Higher-Order Mutation Testing and Data-Flow Testing of C# with the Aid of Genetic Algorithm. Appl. Sci. 2023, 13, 9170.
Abstract
Data-Flow and Higher-Order Mutation are white-box testing techniques. To our knowledge, no work has been proposed to compare data flow and higher-order mutation. This paper compares all def-uses data-flow and second-order mutation criteria. This compassion investigates the subsumption relation between these two criteria and evaluates the effectiveness of test data developed for each. To compare the two criteria, a set of test data satisfying each criterion is generated, which is used to explore whether one criterion subsumes the other criterion and assess the effectiveness of the test set that was developed for one methodology in terms of the other. The results showed that the mean mutation coverage ratio of the all du-pairs adequate test cover is 80.9%, and the mean data flow coverage ratio of the 2nd-order mutant adequate test cover is 98.7%. Consequently, 2nd-order mutation “ProbSubsumes” the all du-pairs data flow. The failure detection efficiency of the mutation (98%) is significantly better than the failure detection efficiency of data flow (86%). Consequently, 2nd-order mutation testing is “ProbBetter” than all du-pairs data flow testing. In contrast, the size of the test suite of 2nd-order mutation is more significant than the size of the test suite of all du-pairs.
Keywords
Data flow testing; higher-order mutation testing; “ProbSubsumes”; “ProbBetter”
Subject
Computer Science and Mathematics, Computer Science
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
