Paper Info
Title
Sampling Program Inputs with Mutation Analysis: Going Beyond Combinatorial Interaction Testing
Abstract
Modern systems tend to be highly configurable. Testing such systems requires selecting test cases from a large input space. Thus, there is a need to systematically sample program inputs in order to reduce the testing effort. In such cases, testing the interactions between program parameters has been identified as an effective way to deal with this problem. In these lines, Combinatorial Interaction Testing (CIT) models the program input interactions and uses this model to select test cases. Going a step further, we apply mutation analysis on the CIT input model to select program test cases. Mutation operates by injecting defects to the program input model and measures the number of defects found by the selected test cases. Experiments performed on four real programs show that measuring the number of model-based defects gives a stronger correlation to code-level faults than measuring the number of the exercised interactions. Therefore, the proposed mutation analysis approach forms a valid and more effective alternative to CIT.
Year
DOI
Venue
2014
10.1109/ICST.2014.11
Software Testing, Verification and Validation
Keywords
Field
DocType
combinatorial mathematics,program testing,CIT input model,code-level faults,combinatorial interaction testing,model-based defects,mutation analysis approach,program input interactions,program input sampling,program parameters,program test cases,Combinatorial Interaction Testing,Fault Detection,Mutation Analysis
Combinatorial interaction testing,Orthogonal array testing,Fault detection and isolation,Mutation testing,Computer science,Algorithm,All-pairs testing,Test case,Sampling (statistics)
Conference
Citations 
PageRank 
References 
22
0.59
22
Authors
3
Name
Order
Citations
PageRank
Mike Papadakis1111452.77
Christopher Henard238310.88
Le Traon, Y.316012.50