Regression testing is the process of validating modified software to detect errors that have been... more Regression testing is the process of validating modified software to detect errors that have been introduced into previously tested code. As the software is modified, the size of the test suite grows and the cost of regression testing increases. In this situation, test case prioritization aims to improve the effectiveness of regression testing by ordering the test cases so that most beneficial test cases are executed first. In this research paper, a new genetic algorithm is introduced that will prioritize regression test suite within a time constrained environment on the basis of total fault coverage. The proposed algorithm has been automated and the results are analysed. The results representing the effectiveness of algorithm are presented with the help of Average Percentage of Faults Detected (APFD).
Evolutionary Computation (EC) is a vibrant area of investigation which has been enormously succes... more Evolutionary Computation (EC) is a vibrant area of investigation which has been enormously successful with more than hundreds of publications within a decade. Some of the widely known approaches being Ant Colony Optimization, Particle Swarm Optimization, Bees Algorithm and Genetic Algorithm. All of these can be used to solve a variety of problems. In fact there are so many papers, that it is sometimes difficult to understand the pros, cons and applicability of each one of them. This paper makes an attempt to compare the basic idea, applicability, limitations and effectiveness of the four effective approaches.
Regression testing is a testing technique which is used to validate the modified software. The re... more Regression testing is a testing technique which is used to validate the modified software. The regression test suite is typically large and needs an intelligent method to choose those test cases which will detect maximum or all faults at the earliest. Many existing prioritization techniques arrange the test cases on the basis of code coverage with respect to older version of the modified software. In this approach, a new Genetic Algorithm to prioritize the regression test suite is introduced that will prioritize test cases on the basis of complete code coverage. The genetic algorithm would also automate the process of test case prioritization. The results representing the effectiveness of algorithms are presented with the help of an Average Percentage of Code Covered (APCC) metric.
Regression testing is the process of validating modified software to detect errors that have been... more Regression testing is the process of validating modified software to detect errors that have been introduced into previously tested code. As the software is modified, the size of the test suite grows and the cost of regression testing increases. In this situation, test case prioritization aims to improve the effectiveness of regression testing by ordering the test cases so that most beneficial test cases are executed first. In this research paper, a new genetic algorithm is introduced that will prioritize regression test suite within a time constrained environment on the basis of total fault coverage. The proposed algorithm has been automated and the results are analysed. The results representing the effectiveness of algorithm are presented with the help of Average Percentage of Faults Detected (APFD).
Evolutionary Computation (EC) is a vibrant area of investigation which has been enormously succes... more Evolutionary Computation (EC) is a vibrant area of investigation which has been enormously successful with more than hundreds of publications within a decade. Some of the widely known approaches being Ant Colony Optimization, Particle Swarm Optimization, Bees Algorithm and Genetic Algorithm. All of these can be used to solve a variety of problems. In fact there are so many papers, that it is sometimes difficult to understand the pros, cons and applicability of each one of them. This paper makes an attempt to compare the basic idea, applicability, limitations and effectiveness of the four effective approaches.
Evolutionary Computation (EC) is a vibrant area of investigation which has been enormously succes... more Evolutionary Computation (EC) is a vibrant area of investigation which has been enormously successful with more than hundreds of publications within a decade. Some of the widely known approaches being Ant Colony Optimization, Particle Swarm Optimization, Bees Algorithm and Genetic Algorithm. All of these can be used to solve a variety of problems. In fact there are so many papers, that it is sometimes difficult to understand the pros, cons and applicability of each one of them. This paper makes an attempt to compare the basic idea, applicability, limitations and effectiveness of the four effective approaches.
Evolutionary Computation (EC) is a vibrant area of investigation which has been enormously succes... more Evolutionary Computation (EC) is a vibrant area of investigation which has been enormously successful with more than hundreds of publications within a decade. Some of the widely known approaches being Ant Colony Optimization, Particle Swarm Optimization, Bees Algorithm and Genetic Algorithm. All of these can be used to solve a variety of problems. In fact there are so many papers, that it is sometimes difficult to understand the pros, cons and applicability of each one of them. This paper makes an attempt to compare the basic idea, applicability, limitations and effectiveness of the four effective approaches.
Regression testing is the process of validating modified software to detect errors that have been... more Regression testing is the process of validating modified software to detect errors that have been introduced into previously tested code. As the software is modified, the size of the test suite grows and the cost of regression testing increases. In this situation, test case prioritization aims to improve the effectiveness of regression testing by ordering the test cases so that most beneficial test cases are executed first. In this research paper, a new genetic algorithm is introduced that will prioritize regression test suite within a time constrained environment on the basis of total fault coverage. The proposed algorithm has been automated and the results are analysed. The results representing the effectiveness of algorithm are presented with the help of Average Percentage of Faults Detected (APFD).
International Journal on Computer Science and …, Jan 1, 2011
Regression testing is a testing technique which is used to validate the modified software. The re... more Regression testing is a testing technique which is used to validate the modified software. The regression test suite is typically large and needs an intelligent method to choose those test cases which will detect maximum or all faults at the earliest. Many existing prioritization techniques arrange the test cases on the basis of code coverage with respect to older version of the modified software. In this approach, a new Genetic Algorithm to prioritize the regression test suite is introduced that will prioritize test cases on the basis of complete code coverage. The genetic algorithm would also automate the process of test case prioritization. The results representing the effectiveness of algorithms are presented with the help of an Average Percentage of Code Covered (APCC) metric.
Regression testing is the process of validating modified software to detect errors that have been... more Regression testing is the process of validating modified software to detect errors that have been introduced into previously tested code. As the software is modified, the size of the test suite grows and the cost of regression testing increases. In this situation, test case prioritization aims to improve the effectiveness of regression testing by ordering the test cases so that most beneficial test cases are executed first. In this research paper, a new genetic algorithm is introduced that will prioritize regression test suite within a time constrained environment on the basis of total fault coverage. The proposed algorithm has been automated and the results are analysed. The results representing the effectiveness of algorithm are presented with the help of Average Percentage of Faults Detected (APFD).
Evolutionary Computation (EC) is a vibrant area of investigation which has been enormously succes... more Evolutionary Computation (EC) is a vibrant area of investigation which has been enormously successful with more than hundreds of publications within a decade. Some of the widely known approaches being Ant Colony Optimization, Particle Swarm Optimization, Bees Algorithm and Genetic Algorithm. All of these can be used to solve a variety of problems. In fact there are so many papers, that it is sometimes difficult to understand the pros, cons and applicability of each one of them. This paper makes an attempt to compare the basic idea, applicability, limitations and effectiveness of the four effective approaches.
Regression testing is a testing technique which is used to validate the modified software. The re... more Regression testing is a testing technique which is used to validate the modified software. The regression test suite is typically large and needs an intelligent method to choose those test cases which will detect maximum or all faults at the earliest. Many existing prioritization techniques arrange the test cases on the basis of code coverage with respect to older version of the modified software. In this approach, a new Genetic Algorithm to prioritize the regression test suite is introduced that will prioritize test cases on the basis of complete code coverage. The genetic algorithm would also automate the process of test case prioritization. The results representing the effectiveness of algorithms are presented with the help of an Average Percentage of Code Covered (APCC) metric.
Regression testing is the process of validating modified software to detect errors that have been... more Regression testing is the process of validating modified software to detect errors that have been introduced into previously tested code. As the software is modified, the size of the test suite grows and the cost of regression testing increases. In this situation, test case prioritization aims to improve the effectiveness of regression testing by ordering the test cases so that most beneficial test cases are executed first. In this research paper, a new genetic algorithm is introduced that will prioritize regression test suite within a time constrained environment on the basis of total fault coverage. The proposed algorithm has been automated and the results are analysed. The results representing the effectiveness of algorithm are presented with the help of Average Percentage of Faults Detected (APFD).
Evolutionary Computation (EC) is a vibrant area of investigation which has been enormously succes... more Evolutionary Computation (EC) is a vibrant area of investigation which has been enormously successful with more than hundreds of publications within a decade. Some of the widely known approaches being Ant Colony Optimization, Particle Swarm Optimization, Bees Algorithm and Genetic Algorithm. All of these can be used to solve a variety of problems. In fact there are so many papers, that it is sometimes difficult to understand the pros, cons and applicability of each one of them. This paper makes an attempt to compare the basic idea, applicability, limitations and effectiveness of the four effective approaches.
Evolutionary Computation (EC) is a vibrant area of investigation which has been enormously succes... more Evolutionary Computation (EC) is a vibrant area of investigation which has been enormously successful with more than hundreds of publications within a decade. Some of the widely known approaches being Ant Colony Optimization, Particle Swarm Optimization, Bees Algorithm and Genetic Algorithm. All of these can be used to solve a variety of problems. In fact there are so many papers, that it is sometimes difficult to understand the pros, cons and applicability of each one of them. This paper makes an attempt to compare the basic idea, applicability, limitations and effectiveness of the four effective approaches.
Evolutionary Computation (EC) is a vibrant area of investigation which has been enormously succes... more Evolutionary Computation (EC) is a vibrant area of investigation which has been enormously successful with more than hundreds of publications within a decade. Some of the widely known approaches being Ant Colony Optimization, Particle Swarm Optimization, Bees Algorithm and Genetic Algorithm. All of these can be used to solve a variety of problems. In fact there are so many papers, that it is sometimes difficult to understand the pros, cons and applicability of each one of them. This paper makes an attempt to compare the basic idea, applicability, limitations and effectiveness of the four effective approaches.
Regression testing is the process of validating modified software to detect errors that have been... more Regression testing is the process of validating modified software to detect errors that have been introduced into previously tested code. As the software is modified, the size of the test suite grows and the cost of regression testing increases. In this situation, test case prioritization aims to improve the effectiveness of regression testing by ordering the test cases so that most beneficial test cases are executed first. In this research paper, a new genetic algorithm is introduced that will prioritize regression test suite within a time constrained environment on the basis of total fault coverage. The proposed algorithm has been automated and the results are analysed. The results representing the effectiveness of algorithm are presented with the help of Average Percentage of Faults Detected (APFD).
International Journal on Computer Science and …, Jan 1, 2011
Regression testing is a testing technique which is used to validate the modified software. The re... more Regression testing is a testing technique which is used to validate the modified software. The regression test suite is typically large and needs an intelligent method to choose those test cases which will detect maximum or all faults at the earliest. Many existing prioritization techniques arrange the test cases on the basis of code coverage with respect to older version of the modified software. In this approach, a new Genetic Algorithm to prioritize the regression test suite is introduced that will prioritize test cases on the basis of complete code coverage. The genetic algorithm would also automate the process of test case prioritization. The results representing the effectiveness of algorithms are presented with the help of an Average Percentage of Code Covered (APCC) metric.
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