Experiments of the effectiveness of dataflow- and controlflow-based test adequacy criteria
ICSE '94 Proceedings of the 16th international conference on Software engineering
Incorporating varying test costs and fault severities into test case prioritization
ICSE '01 Proceedings of the 23rd International Conference on Software Engineering
Prioritizing Test Cases For Regression Testing
IEEE Transactions on Software Engineering
Test Case Prioritization: A Family of Empirical Studies
IEEE Transactions on Software Engineering
Effectively prioritizing tests in development environment
ISSTA '02 Proceedings of the 2002 ACM SIGSOFT international symposium on Software testing and analysis
Computers and Intractability: A Guide to the Theory of NP-Completeness
Computers and Intractability: A Guide to the Theory of NP-Completeness
Core Problems in Knapsack Algorithms
Operations Research
DART: A Framework for Regression Testing "Nightly/daily Builds" of GUI Applications
ICSM '03 Proceedings of the International Conference on Software Maintenance
TimeAware test suite prioritization
Proceedings of the 2006 international symposium on Software testing and analysis
Discrete Mathematics with Proof
Discrete Mathematics with Proof
Time-aware test-case prioritization using integer linear programming
Proceedings of the eighteenth international symposium on Software testing and analysis
Test case prioritization using ant colony optimization
ACM SIGSOFT Software Engineering Notes
An effective fault aware test case prioritization by incorporating a fault localization technique
Proceedings of the 2010 ACM-IEEE International Symposium on Empirical Software Engineering and Measurement
An empirical study on the effectiveness of time-aware test case prioritization techniques
Proceedings of the 2011 ACM Symposium on Applied Computing
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Regression testing is frequently performed in a time constrained environment. This paper explains how 0/1 knapsack solvers (e.g., greedy, dynamic programming, and the core algorithm) can identify a test suite reordering that rapidly covers the test requirements and always terminates within a specified testing time limit. We conducted experiments that reveal fundamental trade-offs in the (i) time and space costs that are associated with creating a reordered test suite and (ii) quality of the resulting prioritization. We find knapsack-based prioritizers that ignore the overlap in test case coverage incur a low time overhead and a moderate to high space overhead while creating prioritizations exhibiting a minor to modest decrease in effectiveness. We also find that the most sophisticated 0/1 knapsack solvers do not always identify the most effective prioritization, suggesting that overlap-aware prioritizers with a higher time overhead are useful in certain testing contexts.