Vui lòng dùng định danh này để trích dẫn hoặc liên kết đến tài liệu này: https://elib.vku.udn.vn/handle/123456789/1014
Nhan đề: Increasing Mutation Testing Effectiveness by Combining Lower Order Mutants to Construct Higher Order Mutants
Tác giả: Nguyen, Quang Vu
Từ khoá: Mutation testing
Limitations of mutation testing
Overcome
Reducing the cost
Harder to kill
Realistic faults
Năm xuất bản: 2020
Nhà xuất bản: Springer Publishing
Trích dẫn: https://link.springer.com/chapter/10.1007/978-3-030-63007-2_16
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 easyto-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” ordermutants 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.
Mô tả: Scientific Paper; Pages: 205-216
Định danh: http://elib.vku.udn.vn/handle/123456789/1014
ISBN: 978-3-030-63006-5
978-3-030-63007-2 (eBook)
ISSN: 0302-9743
1611-3349 (electronic)
Bộ sưu tập: 12th International Conference on Computational Collective Intelligence - ICCCI 2020

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