Using Semantic Metrics to Predict Mutation Equivalence
Document Type
Conference Proceeding
Publication Date
1-1-2019
Abstract
Equivalent mutants are a major nuisance in mutation testing because they introduce a significant amount of bias. But weeding them out is difficult because it requires a detailed analysis of the source code of the base program and the mutant. In this paper we argue that for most applications, it is not necessary to identify equivalent mutants individually; rather it suffices to estimate their number. Also, we explore how we can estimate their number by a cursory/automatable analysis of the base program and the mutant generation policy.
Identifier
85071673364 (Scopus)
ISBN
[9783030291563]
Publication Title
Communications in Computer and Information Science
External Full Text Location
https://doi.org/10.1007/978-3-030-29157-0_1
e-ISSN
18650937
ISSN
18650929
First Page
3
Last Page
27
Volume
1077
Grant
DGE 1565478
Fund Ref
National Science Foundation
Recommended Citation
Ayad, Amani; Marsit, Imen; Mohamed Omri, Nazih; Loh, Ji Meng; and Mili, Ali, "Using Semantic Metrics to Predict Mutation Equivalence" (2019). Faculty Publications. 7959.
https://digitalcommons.njit.edu/fac_pubs/7959
