Introduction Regression Testing Empirical Evaluation Conclusion An Empirical Study of Incorporating Cost into Test Suite Reduction and Prioritization ‡Adam M. Smith and † Gregory M. Kapfhammer ‡Department of Computer Science University of Pittsburgh †Department of Computer Science Allegheny College ACM Symposium on Applied Computing March 8 - 12, 2009 Featuring an image from www.campusbicycle.com 1 / 20 An Empirical Study of Incorporating Cost into Test Suite Reduction and Prioritization
Introduction Regression Testing Empirical Evaluation Conclusion Important Contributions Program Analysis Technique Test Suite Reduction Prioritization Regression Testing Techniques Prioritization Technique Execution Time (ms) 0 20 40 60 80 100 2OPT DGR GRD HGS JD Detailed Empirical Results Implement and empirically evaluate the efficiency and effectiveness of cost-aware greedy methods for regression test suite reduction and prioritization 2 / 20 An Empirical Study of Incorporating Cost into Test Suite Reduction and Prioritization
Introduction Regression Testing Empirical Evaluation Conclusion Important Contributions Program Analysis Technique Test Suite Reduction Prioritization Regression Testing Techniques Prioritization Technique Execution Time (ms) 0 20 40 60 80 100 2OPT DGR GRD HGS JD Detailed Empirical Results Implement and empirically evaluate the efficiency and effectiveness of cost-aware greedy methods for regression test suite reduction and prioritization 2 / 20 An Empirical Study of Incorporating Cost into Test Suite Reduction and Prioritization
Introduction Regression Testing Empirical Evaluation Conclusion Important Contributions Program Analysis Technique Test Suite Reduction Prioritization Regression Testing Techniques Prioritization Technique Execution Time (ms) 0 20 40 60 80 100 2OPT DGR GRD HGS JD Detailed Empirical Results Implement and empirically evaluate the efficiency and effectiveness of cost-aware greedy methods for regression test suite reduction and prioritization 2 / 20 An Empirical Study of Incorporating Cost into Test Suite Reduction and Prioritization
Introduction Regression Testing Empirical Evaluation Conclusion Important Contributions Program Analysis Technique Test Suite Reduction Prioritization Regression Testing Techniques Prioritization Technique Execution Time (ms) 0 20 40 60 80 100 2OPT DGR GRD HGS JD Detailed Empirical Results Implement and empirically evaluate the efficiency and effectiveness of cost-aware greedy methods for regression test suite reduction and prioritization 2 / 20 An Empirical Study of Incorporating Cost into Test Suite Reduction and Prioritization
Introduction Regression Testing Empirical Evaluation Conclusion Regression Testing and Bicycles Efficiency: Low wind resistance and time to destination 3 / 20 An Empirical Study of Incorporating Cost into Test Suite Reduction and Prioritization
Introduction Regression Testing Empirical Evaluation Conclusion Regression Testing and Bicycles Effectiveness: Transports all required materials and no break downs 3 / 20 An Empirical Study of Incorporating Cost into Test Suite Reduction and Prioritization
Introduction Regression Testing Empirical Evaluation Conclusion Regression Testing and Bicycles Cost: Frame material and components cause price to vary considerably 3 / 20 An Empirical Study of Incorporating Cost into Test Suite Reduction and Prioritization
Introduction Regression Testing Empirical Evaluation Conclusion Regression Testing Techniques Before After Reduction Prunes the Test Suite Before After Prioritization Reorders the Tests It is expensive to run a test suite T = T1, . . . , Tn . Reduction discards some of the n tests in an attempt to decrease testing time while still preserving objectives like coverage or fault detection. 4 / 20 An Empirical Study of Incorporating Cost into Test Suite Reduction and Prioritization
Introduction Regression Testing Empirical Evaluation Conclusion Regression Testing Techniques Before After Reduction Prunes the Test Suite Before After Prioritization Reorders the Tests It is expensive to run a test suite T = T1, . . . , Tn . Reduction discards some of the n tests in an attempt to decrease testing time while still preserving objectives like coverage or fault detection. 4 / 20 An Empirical Study of Incorporating Cost into Test Suite Reduction and Prioritization
Introduction Regression Testing Empirical Evaluation Conclusion Regression Testing Techniques Before After Reduction Prunes the Test Suite Before After Prioritization Reorders the Tests It is expensive to run a test suite T = T1, . . . , Tn . Reduction discards some of the n tests in an attempt to decrease testing time while still preserving objectives like coverage or fault detection. 4 / 20 An Empirical Study of Incorporating Cost into Test Suite Reduction and Prioritization
Introduction Regression Testing Empirical Evaluation Conclusion Regression Testing Techniques Before After Reduction Prunes the Test Suite Before After Prioritization Reorders the Tests It is expensive to run a test suite T = T1, . . . , Tn . Reduction discards some of the n tests in an attempt to decrease testing time while still preserving objectives like coverage or fault detection. 4 / 20 An Empirical Study of Incorporating Cost into Test Suite Reduction and Prioritization
Introduction Regression Testing Empirical Evaluation Conclusion Regression Testing Techniques Before After Reduction Prunes the Test Suite Before After Prioritization Reorders the Tests It is expensive to run a test suite T = T1, . . . , Tn . Prioritization searches through the n! = n × n − 1 × . . . × 1 orderings for those that maximize an objective function like coverage or fault detection. 4 / 20 An Empirical Study of Incorporating Cost into Test Suite Reduction and Prioritization
Introduction Regression Testing Empirical Evaluation Conclusion Finding the Overlap in Coverage T2 T3 T6 T9 R R1 R2 T4 T8 T11 R3 T12 R4 T1 R4 R4 R4 T5 R4 R4 T10 R4 T11 R5 T5 R5 R6 R6 T10 R7 R7 T7 R7 T10 Rj → Ti means that requirement Rj is covered by test Ti Test suite reduction discards the test cases that redundantly cover the test requirements T = T2, T3, T6, T9 covers all of the test requirements 5 / 20 An Empirical Study of Incorporating Cost into Test Suite Reduction and Prioritization
Introduction Regression Testing Empirical Evaluation Conclusion Finding the Overlap in Coverage T2 T3 T6 T9 R R1 R2 T4 T8 T11 R3 T12 R4 T1 R4 R4 R4 T5 R4 R4 T10 R4 T11 R5 T5 R5 R6 R6 T10 R7 R7 T7 R7 T10 Rj → Ti means that requirement Rj is covered by test Ti Test suite reduction discards the test cases that redundantly cover the test requirements T = T2, T3, T6, T9 covers all of the test requirements 5 / 20 An Empirical Study of Incorporating Cost into Test Suite Reduction and Prioritization
Introduction Regression Testing Empirical Evaluation Conclusion Finding the Overlap in Coverage T2 T3 T6 T9 R R1 R2 T4 T8 T11 R3 T12 R4 T1 R4 R4 R4 T5 R4 R4 T10 R4 T11 R5 T5 R5 R6 R6 T10 R7 R7 T7 R7 T10 Rj → Ti means that requirement Rj is covered by test Ti Test suite reduction discards the test cases that redundantly cover the test requirements T = T2, T3, T6, T9 covers all of the test requirements 5 / 20 An Empirical Study of Incorporating Cost into Test Suite Reduction and Prioritization
Introduction Regression Testing Empirical Evaluation Conclusion Greedy Approaches to Regression Testing Original Test Suite First Output First Residual Second Output Prioritized Test Suite Reduction Technique ts T4 T3 T2 T1 T4 T1 T3 T2 T3 T2 T3 T3 T3 T3 T2 T2 T2 T2 T4 T4 T4 T1 T1 T1 Harrold, Gupta, Soffa (HGS) Delayed Greedy (DGR) Traditional Greedy (GRD) 2-Optimal Greedy (2OPT) Hypothesis: Using the exe- cution time of a test case can improve the reduced and pri- oritized test suites Compare (i) greedy choices (cost, coverage, and ratio) and (ii) algorithms 6 / 20 An Empirical Study of Incorporating Cost into Test Suite Reduction and Prioritization
Introduction Regression Testing Empirical Evaluation Conclusion Greedy Approaches to Regression Testing Original Test Suite First Output First Residual Second Output Prioritized Test Suite Reduction Technique ts T4 T3 T2 T1 T4 T1 T3 T2 T3 T2 T3 T3 T3 T3 T2 T2 T2 T2 T4 T4 T4 T1 T1 T1 Harrold, Gupta, Soffa (HGS) Delayed Greedy (DGR) Traditional Greedy (GRD) 2-Optimal Greedy (2OPT) Hypothesis: Using the exe- cution time of a test case can improve the reduced and pri- oritized test suites Compare (i) greedy choices (cost, coverage, and ratio) and (ii) algorithms 6 / 20 An Empirical Study of Incorporating Cost into Test Suite Reduction and Prioritization
Introduction Regression Testing Empirical Evaluation Conclusion Greedy Approaches to Regression Testing Original Test Suite First Output First Residual Second Output Prioritized Test Suite Reduction Technique ts T4 T3 T2 T1 T4 T1 T3 T2 T3 T2 T3 T3 T3 T3 T2 T2 T2 T2 T4 T4 T4 T1 T1 T1 Harrold, Gupta, Soffa (HGS) Delayed Greedy (DGR) Traditional Greedy (GRD) 2-Optimal Greedy (2OPT) Hypothesis: Using the exe- cution time of a test case can improve the reduced and pri- oritized test suites Compare (i) greedy choices (cost, coverage, and ratio) and (ii) algorithms 6 / 20 An Empirical Study of Incorporating Cost into Test Suite Reduction and Prioritization
Introduction Regression Testing Empirical Evaluation Conclusion Greedy Approaches to Regression Testing Original Test Suite First Output First Residual Second Output Prioritized Test Suite Reduction Technique ts T4 T3 T2 T1 T4 T1 T3 T2 T3 T2 T3 T3 T3 T3 T2 T2 T2 T2 T4 T4 T4 T1 T1 T1 Harrold, Gupta, Soffa (HGS) Delayed Greedy (DGR) Traditional Greedy (GRD) 2-Optimal Greedy (2OPT) Hypothesis: Using the exe- cution time of a test case can improve the reduced and pri- oritized test suites Compare (i) greedy choices (cost, coverage, and ratio) and (ii) algorithms 6 / 20 An Empirical Study of Incorporating Cost into Test Suite Reduction and Prioritization
Introduction Regression Testing Empirical Evaluation Conclusion Evaluating Test Suite Prioritizers Testing Time . . . Covered Test Reqs acements T1 Done Tn−1 Done Tn Done Cover R(T1 ) Cover n−1 i=1 R(Ti ) Cover R(T) Area t(n) 0 C(T , t) C(T , t) (t) Prioritize to increase the CE of a test suite CE = Actual Ideal ∈ [0 , 1] 7 / 20 An Empirical Study of Incorporating Cost into Test Suite Reduction and Prioritization
Introduction Regression Testing Empirical Evaluation Conclusion Evaluating Test Suite Prioritizers Testing Time . . . Covered Test Reqs acements T1 Done Tn−1 Done Tn Done Cover R(T1 ) Cover n−1 i=1 R(Ti ) Cover R(T) Area t(n) 0 C(T , t) C(T , t) (t) Prioritize to increase the CE of a test suite CE = Actual Ideal ∈ [0 , 1] 7 / 20 An Empirical Study of Incorporating Cost into Test Suite Reduction and Prioritization
Introduction Regression Testing Empirical Evaluation Conclusion Evaluating Test Suite Reducers Reduction Factor for Size (RFFS): How small is the reduced test suite? 8 / 20 An Empirical Study of Incorporating Cost into Test Suite Reduction and Prioritization
Introduction Regression Testing Empirical Evaluation Conclusion Evaluating Test Suite Reducers Reduction Factor for Time (RFFT): How fast is the reduced test suite? 8 / 20 An Empirical Study of Incorporating Cost into Test Suite Reduction and Prioritization
Introduction Regression Testing Empirical Evaluation Conclusion Case Study Applications Name |T| |R(T)| CCN NCSS DS 110 40 1.35 1243.00 GB 51 88 2.60 1455.00 JD 54 783 1.64 2716.00 LF 13 6 1.40 215.00 RM 13 19 2.13 569.00 SK 27 117 2.00 628.00 TM 27 46 2.21 748.00 RP 76 221 2.65 6822.00 Questions: Do the greedy reducers and prioritizers efficiently identify test suites that improve effectiveness? What are the fundamental trade-offs? 10 / 20 An Empirical Study of Incorporating Cost into Test Suite Reduction and Prioritization
Introduction Regression Testing Empirical Evaluation Conclusion Overview of RFFT Trends | metric: cost alg: 2OPT,GRD 0.2101 0.4946 0.4889 Reduction Factor for Time (RFFT) The myopic focus on cost leads to low RFFT values for 2OPT and GRD 11 / 20 An Empirical Study of Incorporating Cost into Test Suite Reduction and Prioritization
Introduction Regression Testing Empirical Evaluation Conclusion Overview of RFFT Trends | metric: cost alg: 2OPT,GRD 0.2101 0.4946 0.4889 Reduction Factor for Time (RFFT) The myopic focus on cost leads to low RFFT values for 2OPT and GRD 11 / 20 An Empirical Study of Incorporating Cost into Test Suite Reduction and Prioritization
Introduction Regression Testing Empirical Evaluation Conclusion Overview of RFFS Trends | alg: 2OPT,GRD metric: cost metric: coverage 0.1130 0.5967 0.4959 0.6136 Reduction Factor for Size (RFFS) DGR and HGS are the best at creating test suites that improve RFFS 12 / 20 An Empirical Study of Incorporating Cost into Test Suite Reduction and Prioritization
Introduction Regression Testing Empirical Evaluation Conclusion Overview of RFFS Trends | alg: 2OPT,GRD metric: cost metric: coverage 0.1130 0.5967 0.4959 0.6136 Reduction Factor for Size (RFFS) DGR and HGS are the best at creating test suites that improve RFFS 12 / 20 An Empirical Study of Incorporating Cost into Test Suite Reduction and Prioritization
Introduction Regression Testing Empirical Evaluation Conclusion Overview of CE Trends | alg: HGS metric: coverage alg: DGR 0.7520 0.8231 0.8344 0.9388 Coverage Effectiveness (CE) Using ratio and cost improves the CE of the prioritized test suite 13 / 20 An Empirical Study of Incorporating Cost into Test Suite Reduction and Prioritization
Introduction Regression Testing Empirical Evaluation Conclusion Overview of CE Trends | alg: HGS metric: coverage alg: DGR 0.7520 0.8231 0.8344 0.9388 Coverage Effectiveness (CE) Using ratio and cost improves the CE of the prioritized test suite 13 / 20 An Empirical Study of Incorporating Cost into Test Suite Reduction and Prioritization
Introduction Regression Testing Empirical Evaluation Conclusion Reduction Factor for Time - SK Reduction Technique Reduction Factor for Time (RFFT) 0.0 0.1 0.2 0.3 0.4 2OPT DGR GRD HGS SK cost coverage ratio For 2OPT and GRD, ratio and coverage create the best test suites 14 / 20 An Empirical Study of Incorporating Cost into Test Suite Reduction and Prioritization
Introduction Regression Testing Empirical Evaluation Conclusion Reduction Factor for Time - SK Reduction Technique Reduction Factor for Time (RFFT) 0.0 0.1 0.2 0.3 0.4 2OPT DGR GRD HGS SK cost coverage ratio For 2OPT and GRD, ratio and coverage create the best test suites 14 / 20 An Empirical Study of Incorporating Cost into Test Suite Reduction and Prioritization
Introduction Regression Testing Empirical Evaluation Conclusion Reduction Factor for Size - SK Reduction Technique Reduction Factor for Size (RFFS) 0.0 0.1 0.2 0.3 0.4 0.5 0.6 2OPT DGR GRD HGS SK cost coverage ratio It is often easy to construct test suites with high RFFS values 15 / 20 An Empirical Study of Incorporating Cost into Test Suite Reduction and Prioritization
Introduction Regression Testing Empirical Evaluation Conclusion Reduction Factor for Size - SK Reduction Technique Reduction Factor for Size (RFFS) 0.0 0.1 0.2 0.3 0.4 0.5 0.6 2OPT DGR GRD HGS SK cost coverage ratio It is often easy to construct test suites with high RFFS values 15 / 20 An Empirical Study of Incorporating Cost into Test Suite Reduction and Prioritization
Introduction Regression Testing Empirical Evaluation Conclusion Coverage Effectiveness Results - RP Prioritization Technique Coverage Effectiveness (CE) 0.4 0.5 0.6 0.7 0.8 0.9 2OPT DGR GRD HGS SK cost coverage ratio DGR and HGS exhibit lackluster performance when reordering 16 / 20 An Empirical Study of Incorporating Cost into Test Suite Reduction and Prioritization
Introduction Regression Testing Empirical Evaluation Conclusion Coverage Effectiveness Results - RP Prioritization Technique Coverage Effectiveness (CE) 0.4 0.5 0.6 0.7 0.8 0.9 2OPT DGR GRD HGS SK cost coverage ratio DGR and HGS exhibit lackluster performance when reordering 16 / 20 An Empirical Study of Incorporating Cost into Test Suite Reduction and Prioritization
Introduction Regression Testing Empirical Evaluation Conclusion Efficiency Measurements Prioritization Technique Execution Time (ms) 0 20 40 60 80 100 2OPT DGR GRD HGS JD For the chosen case study applications, the techniques are efficient 17 / 20 An Empirical Study of Incorporating Cost into Test Suite Reduction and Prioritization
Introduction Regression Testing Empirical Evaluation Conclusion Efficiency Measurements Prioritization Technique Execution Time (ms) 0 20 40 60 80 100 2OPT DGR GRD HGS JD For the chosen case study applications, the techniques are efficient 17 / 20 An Empirical Study of Incorporating Cost into Test Suite Reduction and Prioritization
Introduction Regression Testing Empirical Evaluation Conclusion Alternative Evaluation Metrics Like APFD Mutation Faults Real Faults Use mutation and real faults to support the calculation of fault detection effectiveness (FDE) and average percentage of faults detected (APFD). Consider search-based testing methods. 18 / 20 An Empirical Study of Incorporating Cost into Test Suite Reduction and Prioritization
Introduction Regression Testing Empirical Evaluation Conclusion RAISE - Reduce And prIortize SuitEs http://raise.googlecode.com/ provides tools, data sets, and resources 19 / 20 An Empirical Study of Incorporating Cost into Test Suite Reduction and Prioritization
Introduction Regression Testing Empirical Evaluation Conclusion Concluding Remarks Program Analysis Technique Test Suite Reduction Prioritization Regression Testing Techniques Prioritization Technique Execution Time (ms) 0 20 40 60 80 100 2OPT DGR GRD HGS JD Detailed Empirical Results Implementation and empirical evaluation of methods for test suite reduction and prioritization Freely available data sets and free/open source tools http://www.cs.allegheny.edu/~gkapfham/research/kanonizo/ 20 / 20 An Empirical Study of Incorporating Cost into Test Suite Reduction and Prioritization
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