Title
Priority Integration for Weighted Combinatorial Testing
Abstract
Priorities (weights) for parameter values can improve the effectiveness of combinatorial testing. Previous approaches have employed weights to derive high-priority test cases either earlier or more frequently. Our approach integrates these order-focused and frequency-focused prioritizations. We show that our priority integration realizes a small test suite providing high-priority test cases early and frequently in a good balance. We also propose two algorithms that apply our priority integration to existing combinatorial test generation algorithms. Experimental results using numerous test models show that our approach improves the existing approaches w.r.t. Order-focused and frequency-focused metrics, while overheads in the size and generation time of test suites are small.
Year
DOI
Venue
2015
10.1109/COMPSAC.2015.113
2015 IEEE 39th Annual Computer Software and Applications Conference
Keywords
Field
DocType
Combinatorial testing,Pairwise testing,Prioritized Testing,Priority weight,Weight coverage,KL divergence
Test suite,Generation time,Data mining,Mathematical optimization,Algorithm design,Computer science,All-pairs testing,Real-time computing,Test case,Benchmark (computing),Kullback–Leibler divergence,Overhead (business)
Conference
Volume
ISSN
Citations 
2
0730-3157
4
PageRank 
References 
Authors
0.44
6
5
Name
Order
Citations
PageRank
Eun-Hye Choi1394.00
Takashi Kitamura2516.97
Cyrille Artho358844.46
Akihisa Yamada 00024347.11
Yutaka Oiwa5415.75