Design complexity measurement and testing
Communications of the ACM
A methodology for controlling the size of a test suite
ACM Transactions on Software Engineering and Methodology (TOSEM)
Prioritizing Test Cases For Regression Testing
IEEE Transactions on Software Engineering
Test Case Prioritization: A Family of Empirical Studies
IEEE Transactions on Software Engineering
Empirical Studies of Test Case Prioritization in a JUnit Testing Environment
ISSRE '04 Proceedings of the 15th International Symposium on Software Reliability Engineering
Demand-driven structural testing with dynamic instrumentation
Proceedings of the 27th international conference on Software engineering
Call Stack Coverage for Test Suite Reduction
ICSM '05 Proceedings of the 21st IEEE International Conference on Software Maintenance
Testing in resource constrained execution environments
Proceedings of the 20th IEEE/ACM international Conference on Automated software engineering
A concept analysis inspired greedy algorithm for test suite minimization
PASTE '05 Proceedings of the 6th ACM SIGPLAN-SIGSOFT workshop on Program analysis for software tools and engineering
Call Stack Coverage for GUI Test-Suite Reduction
ISSRE '06 Proceedings of the 17th International Symposium on Software Reliability Engineering
Search Algorithms for Regression Test Case Prioritization
IEEE Transactions on Software Engineering
Test suite reduction and prioritization with call trees
Proceedings of the twenty-second IEEE/ACM international conference on Automated software engineering
Database-aware test coverage monitoring
ISEC '08 Proceedings of the 1st India software engineering conference
Using coverage effectiveness to evaluate test suite prioritizations
Proceedings of the 1st ACM international workshop on Empirical assessment of software engineering languages and technologies: held in conjunction with the 22nd IEEE/ACM International Conference on Automated Software Engineering (ASE) 2007
The R Book
Design and analysis of GUI test-case prioritization using weight-based methods
Journal of Systems and Software
Designing better fitness functions for automated program repair
Proceedings of the 12th annual conference on Genetic and evolutionary computation
Empirically studying the role of selection operators duringsearch-based test suite prioritization
Proceedings of the 12th annual conference on Genetic and evolutionary computation
Using synthetic test suites to empirically compare search-based and greedy prioritizers
Proceedings of the 12th annual conference companion on Genetic and evolutionary computation
A diagnostic reasoning approach to defect prediction
IEA/AIE'11 Proceedings of the 24th international conference on Industrial engineering and other applications of applied intelligent systems conference on Modern approaches in applied intelligence - Volume Part II
Prioritizing tests for fault localization through ambiguity group reduction
ASE '11 Proceedings of the 2011 26th IEEE/ACM International Conference on Automated Software Engineering
Regression testing minimization, selection and prioritization: a survey
Software Testing, Verification & Reliability
Reducing test effort: A systematic mapping study on existing approaches
Information and Software Technology
Accelerated model-based robustness testing of state machine implementations
ACM SIGAPP Applied Computing Review
Post-compiler software optimization for reducing energy
Proceedings of the 19th international conference on Architectural support for programming languages and operating systems
| Hi-index | 0.00 |
Software developers use testing to gain and maintain confidence in the correctness of a software system. Automated reduction and prioritization techniques attempt to decrease the time required to detect faults during test suite execution. This paper uses the Harrold Gupta Soffa, delayed greedy, traditional greedy, and 2-optimal greedy algorithms for both test suite reduction and prioritization. Even though reducing and reordering a test suite is primarily done to ensure that testing is cost-effective, these algorithms are normally configured to make greedy choices with coverage information alone. This paper extends these algorithms to greedily reduce and prioritize the tests by using both test cost (e.g., execution time) and the ratio of code coverage to test cost. An empirical study with eight real world case study applications shows that the ratio greedy choice metric aids a test suite reduction method in identifying a smaller and faster test suite. The results also suggest that incorporating test cost during prioritization allows for an average increase of 17% and a maximum improvement of 141% for a time sensitive evaluation metric called coverage effectiveness.