Applying design of experiments to software testing: experience report
ICSE '97 Proceedings of the 19th international conference on Software engineering
The AETG System: An Approach to Testing Based on Combinatorial Design
IEEE Transactions on Software Engineering
Model-based testing in practice
Proceedings of the 21st international conference on Software engineering
Simplifying and Isolating Failure-Inducing Input
IEEE Transactions on Software Engineering
A Test Generation Strategy for Pairwise Testing
IEEE Transactions on Software Engineering
Constructing test suites for interaction testing
Proceedings of the 25th International Conference on Software Engineering
Bug isolation via remote program sampling
PLDI '03 Proceedings of the ACM SIGPLAN 2003 conference on Programming language design and implementation
Augmenting Simulated Annealing to Build Interaction Test Suites
ISSRE '03 Proceedings of the 14th International Symposium on Software Reliability Engineering
Software Fault Interactions and Implications for Software Testing
IEEE Transactions on Software Engineering
Skoll: Distributed Continuous Quality Assurance
Proceedings of the 26th International Conference on Software Engineering
Covering Arrays for Efficient Fault Characterization in Complex Configuration Spaces
IEEE Transactions on Software Engineering
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The increasing complexity of configurable software systems creates a need for more intelligent sampling mechanisms to detect and locate failure-inducing dependencies between configurations. Prior work shows that test schedules based on a mathematical object, called a covering array, can be used to detect and locate failures in combination with a classification tree analysis. This paper addresses limitations of the earlier approach. First, the previous work requires developers to choose the covering array's strength, even though there is no scientific or historical basis for doing so. Second, if a single covering array is insufficient to classify specific failures, the entire process must be rerun from scratch. To address these issues, our new approach incrementally and adaptively builds covering array schedules. It begins with a low strength, and continually increases this as resources allow, or poor classification results require. At each stage, previous tests are reused. This allows failures due to only one or two configurations settings to be found and classified as early as possible, and also limits duplication of work when multiple covering arrays must be used.