DocumentCode :
3659891
Title :
Enhanced Genetic Algorithm for MC/DC test data generation
Author :
Ahmed El-Serafy;Ghada El-Sayed;Cherif Salama;Ayman Wahba
Author_Institution :
Computers and Systems Engineering Department, Ain-Shams University, Cairo, Egypt
fYear :
2015
Firstpage :
1
Lastpage :
8
Abstract :
Structural testing is concerned with the internal structures of the written software. The targeted structural coverage criteria are usually based on the criticality of the application. Modified Condition/Decision Coverage (MC/DC) is a structural coverage criterion that was introduced to the industry by NASA. Also, MC/DC comes either highly recommended or mandated by multiple standards, including ISO 26262 from the automotive industry and DO-178C from the aviation industry due to its efficiency in bug finding while maintaining a compact test suite. However, due to its complexity, huge amount of resources are dedicated to fulfilling it. Hence, automation efforts were directed to generate test data that satisfy MC/DC. Genetic Algorithms (GA) in particular showed promising results in achieving high coverage percentages. Our results show that coverage levels could be further improved using a batch of enhancements applied on the GA search.
Keywords :
"Genetic algorithms","Sociology","Statistics","Benchmark testing","Industries","Decision feedback equalizers"
Publisher :
ieee
Conference_Titel :
Innovations in Intelligent SysTems and Applications (INISTA), 2015 International Symposium on
Type :
conf
DOI :
10.1109/INISTA.2015.7276794
Filename :
7276794
Link To Document :
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