Compiler Equivalence
URL
Change Log
| When | What |
|---|---|
| December 14th, 2015 | Donated by George Mathew |
Reference
Studies who have been using the data (in any form) are required to include the following reference:
@inproceedings{Papadakis:2015:TCE:2818754.2818867,
author = {Papadakis, Mike and Jia, Yue and Harman, Mark and Le Traon, Yves},
title = {Trivial Compiler Equivalence: A Large Scale Empirical Study of a Simple, Fast and Effective Equivalent Mutant Detection Technique},
booktitle = {Proceedings of the 37th International Conference on Software Engineering - Volume 1},
series = {ICSE '15},
year = {2015},
isbn = {978-1-4799-1934-5},
location = {Florence, Italy},
pages = {936--946},
numpages = {11},
url = {https://dl.acm.org/citation.cfm?id=2818754.2818867},
acmid = {2818867},
publisher = {IEEE Press},
address = {Piscataway, NJ, USA},
}
About the Data
Overview of Data
The data is C code used to study “Equivalent Mutation Detection technique in Compilers”.
Paper Abstract
Identifying equivalent mutants remains the largest impediment to the widespread uptake of mutation testing. Despite being researched for more than three decades, the problem remains. We propose Trivial Compiler Equivalence (TCE) a technique that exploits the use of readily available compiler technology to address this long-standing challenge. TCE is directly applicable to real-world programs and can imbue existing tools with the ability to detect equivalent mutants and a special form of useless mutants called duplicated mutants. We present a thorough empirical study using 6 large open source programs, several orders of magnitude larger than those used in previous work, and 18 benchmark programs with hand-analysis equivalent mutants. Our results reveal that, on large real-world programs, TCE can discard more than 7% and 21% of all the mutants as being equivalent and duplicated mutants respectively. A human-based equivalence verification reveals that TCE has the ability to detect approximately 30% of all the existing equivalent mutants.