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 Increasing mutation testing effectiveness by combining lower order mutants to construct higher order mutants
Tác giả hoặc Nhóm tác giả: Quang-Vu Nguyen
Nơi đăng: ICCCI 2020, Lecture Notes in Artificial Intelligence, Springer; Số: 19;Từ->đến trang: 100-112;Năm: 2020
Lĩnh vực: Công nghệ thông tin; Loại: Bài báo khoa học; Thể loại: Quốc tế
TÓM TẮT
Researching and proposing the solutions in the field of mutation testing in order to answer the question of how to improve the effectiveness of mutant testing is a problem that researchers, who study in the field of mutation testing, are interested. Limitations of mutation testing are really big problems that prevent its application in practice although this is a promising technique in assessing the quality of test data sets. The number of generated mutants is too large and easy-to-kill mutants are two of those problems. In this paper, we have studied and presented our solution, as well as analyzed the empirical results for the purpose of introducing a way to improve the effectiveness of mutant testing. Instead of constructing higher order mutants by using and combining first-order mutants as previous studies, we propose a method to use higher-order mutants for creating mutants. In other words, we have combined two “lower” order mutants to construct “higher” order mutants, i.e., use two second order mutants to construct a fourth order mutant, guided by our proposed objective and fitness functions. According to the experimental results, the number of generated is reduced and number of valuable mutants is fairly large, we have concluded that our approach seems to be a good way to overcome the main limitations of mutation testing.
ABSTRACT
Researching and proposing the solutions in the field of mutation testing in order to answer the question of how to improve the effectiveness of mutant testing is a problem that researchers, who study in the field of mutation testing, are interested. Limitations of mutation testing are really big problems that prevent its application in practice although this is a promising technique in assessing the quality of test data sets. The number of generated mutants is too large and easy-to-kill mutants are two of those problems. In this paper, we have studied and presented our solution, as well as analyzed the empirical results for the purpose of introducing a way to improve the effectiveness of mutant testing. Instead of constructing higher order mutants by using and combining first-order mutants as previous studies, we propose a method to use higher-order mutants for creating mutants. In other words, we have combined two “lower” order mutants to construct “higher” order mutants, i.e., use two second order mutants to construct a fourth order mutant, guided by our proposed objective and fitness functions. According to the experimental results, the number of generated is reduced and number of valuable mutants is fairly large, we have concluded that our approach seems to be a good way to overcome the main limitations of mutation testing.
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