An Optimal Hybrid Regression Testing Approach Based on Code Path Pruning

2018 ◽  
pp. 265-286
Author(s):  
Varun Gupta
Keyword(s):  
Fault Detection ◽  
Detection Rate ◽  
Source Code ◽  
Hybrid Approach ◽  
Regression Testing ◽  
Test Suite ◽  
Test Cases ◽  
Hybrid Approaches ◽  
Testing Approach ◽  
Better Than

Hybrid regression testing approaches involve the combinations of test suite selections, prioritizations, and minimizations. The hybrid approaches must reduce size of test suite to minimal level and enhance fault detection rate. The chapter proposes a new hybrid regression testing approach that reduces the number of test cases by reducing the paths of source code on the basis of the dependency between the statements and the changes. The proposed technique is evaluated to be better than the existing hybrid approach in terms of percentage savings in test cases and fault detection rate.

Hybrid Regression Testing Based on Path Pruning

2015 ◽  
Vol 5 (1) ◽  
pp. 35-55 ◽  
Author(s):  
Varun Gupta ◽  
Durg Singh Chauhan ◽  
Kamlesh Dutta
Keyword(s):  
Fault Detection ◽  
Regression Testing ◽  
Test Suite ◽  
Test Case ◽  
Test Cases ◽  
Testing Time ◽  
Ripple Effect ◽  
Web Based ◽  
Testing Approach ◽  
Globally Distributed

Regression testing has been studied by various researchers for developing and testing the quality of software. Regression testing aims at re-execution of evolved software code to ensure that no new errors had been introduced during the process of modification. Since re-execution of all test cases is not feasible, selecting manageable number of test cases to execute modified code with good fault detection rate is a problem. In past few years, various hybrid based regression testing approaches have been proposed and successfully employed for software testing, aiming at reduction in the number of test cases and higher fault detection capabilities. These techniques are based on sequence of selections, prioritizations and minimization of test suite. However, these techniques suffer from major drawbacks like improper consideration of control dependencies, neglection of unaffected fragments of code for testing purpose. Further, these techniques have been employed on hypothetical or simple programs with test suites of smaller size. Present paper proposes hybrid regression testing, a combination of test case selections, test case prioritizations and test suite minimization. The technique works at statement level and is based on finding the paths containing statements that affects or gets affected by the addition/deletion or modification (both control and data dependency) of variables in statements. The modification in the code may cause ripple effect thereby resulting into faulty execution of the code. The hybrid regression testing approach is aimed at detecting such faults with lesser number of test cases. Reduction in number of test cases is possible because of the decreased number of paths to be tested. A web based framework to automate and parallelize this testing technique to maximum extend, making it well suited for globally distributed environments is also proposed in the present paper. Framework when implemented as a tool can handle large pool of test cases and will make use of parallel MIMD architectures like multicore systems. Technique is applied on prototype live system and results are compared with recently proposed hybrid regression testing approach against parameters of interest. Obtained optimized results are indicators of effectiveness of approach in terms of reduction in effort, cost as well as testing time in general and increment delivery time in particular.

scholarly journals Efficiency Enhancement in Regression Test Case Prioritization Technique

2019 ◽  
Vol 8 (12) ◽  
pp. 5445-5451
Keyword(s):  
Fault Detection ◽  
Software Quality ◽  
Detection Rate ◽  
Regression Testing ◽  
Test Case ◽  
Test Cases ◽  
Efficiency Enhancement ◽  
Average Percentage ◽  
Regression Test ◽  
Expensive Process

Regression testing is an important, but expensive, process that has a powerful impact on software quality. Unfortunately all the test cases, existing and newly added, cannot be re-executed due to insufficient resources. In this scenario, prioritization of test case helps in improving the efficacy of regression testing by arranging the test cases in such a way that the most beneficial (that has the potential to detect the more number of faults) are executed first. Previous work and existing prioritization techniques, though detects faults, but there is a need of improved techniques to enhance the process of regression testing by improving the fault detection rate. The new technique, proposed in this paper, gives improved result than the existing ones. The comparison of the effectiveness of the proposed approach is done with other prioritization and non-prioritization orderings. The result of the proposed approach shows higher average percentage of faults detected (APFD) values. Also, the performance is evaluated and it is observed that the capability of the proposed method outperforms other algorithms by enhancing the fault detection rate.

A Hybrid Technique for Selection and Minimization of Test Cases in Regression Testing

2019 ◽  
Vol 12 ◽  
Author(s):  
Leena Singh ◽  
Shailendra Narayan Singh ◽  
Sudhir Dawra
Keyword(s):  
Execution Time ◽  
Firefly Algorithm ◽  
Hybrid Approach ◽  
Regression Testing ◽  
Test Suite ◽  
Test Cases ◽  
Hybrid Technique ◽  
Time Saving ◽  
Superior Result ◽  
Software Practitioners

Background: In today’s era, modifications in a software is a common requirement by customers. When changes are made to existing software, re-testing of all the test cases is required to ensure that the newly introduced changes do not have any unwanted effect on the behavior of the software. However, re-testing of all the test cases would not only be time consuming but also expensive. Therefore, there is a need for a technique that reduces the number of tests to be performed. Regression testing is one of the ways to reduce the number of test cases. Selection technique is one such method which seeks to identify the test cases that are relevant to some set of recent changes. Objective: It is evident that most of the studies have used different selection techniques and have focused only on one parameter for achieving reduced test suite size without compromising the performance of regression testing. However, to the best of our knowledge, no study has taken two or more parameters of coverage, and/or execution time in a single testing. This paper presents a hybrid technique that combines both regression test selection using slicing technique and minimization of test cases using modified firefly algorithm with combination of parameters coverage and execution time in a single testing. Methods: A hybrid technique has been described that combines both selection and minimization. Selection of test cases is based upon slicing technique while minimization is done using firefly algorithm. Hybrid technique selects and minimizes the test suite using information on statement coverage and execution time. Results: The proposed technique gives 43.33% much superior result as compared to the other hybrid approach in terms of significantly reduced number of test cases. It shows that the resultant test cases were effective enough to cover 100% of the statements, for all the programs. The proposed technique was also tested on four different programs namely Quadratic, Triangle, Next day, Commission respectively for test suite selection and minimization which gave comparatively superior result in terms of reduction (%) in number of test cases required for testing. Conclusion: The combination of parameters used in slicing based approach, reduces the number of test cases making software testing an economical, feasible and time saving option without any fault in the source code. This proposed technique can be used by software practitioners/experts to reduce time, efforts and resources for selection and minimization of test cases.

Test Suite Minimization in Regression Testing Using Hybrid Approach of ACO and GA

2021 ◽  
pp. 133-150
Author(s):  
Abhishek Pandey ◽  
Soumya Banerjee
Keyword(s):  
Hybrid Approach ◽  
Regression Testing ◽  
Minimum Time ◽  
Test Suite ◽  
Test Case ◽  
Test Cases ◽  
Test Case Prioritization ◽  
Ant Colony Optimization Algorithm ◽  
Test Case Selection

This article describes about the application of search-based techniques in regression testing and compares the performance of various search-based techniques for software testing. Test cases tend to increase exponentially as the software is modified. It is essential to remove redundant test cases from the existing test suite. Regression testing is very costly and must be performed in restricted ways to ensure the validity of the existing software. There exist different methods to improve the quality of test cases in terms of the number of faults covered, opposed to the number of statements covered in a minimum time. Different methods exist for this purpose, such as minimization, test case selection, and test case prioritization. In this article, search-based methods are applied to improve the quality of the test suite in order to select a minimum set of test cases which covers all the statements in a minimum time. The whole approach is named search based regression testing. In this paper, the performance of different metaheuristics for test suite minimization problem is also compared with a hybrid approach of ant colony optimization algorithm and genetic algorithm.

scholarly journals Framework for Optimizing Test Cases in Regression Testing

2018 ◽  
Vol 7 (3.12) ◽  
pp. 444
Author(s):  
R P Mahapatra ◽  
Aparna Ranjith ◽  
A Kulothungan
Keyword(s):  
Fault Detection ◽  
Detection Rate ◽  
Selection Process ◽  
Regression Testing ◽  
Test Case ◽  
Test Cases ◽  
Test Case Selection ◽  
Case Selection ◽  
Efficient Test ◽  
Software Engineers

Software once developed is subject to continuous changes. Software Regression Testing thus can be used to reduce the efforts of testing the software by selecting only the required number of test cases and ordering them to test the software after changes have been made to it. In order to improve the fault detection rate, the selection of efficient test cases and order of execution of these tests is important. Here is when the test case selection comes into picture where in, the fault detection rate during the working of any software has to be improved. The test case selection process will find the most efficient test cases which can fully functionally test the software that has been modified. This indeed will contribute to an improved fault detection rate which can provide faster feedback on the system under test and let software engineers begin correcting faults as early as possible. In this paper, an approach for test case selection is proposed which takes into consideration the effect of three parameters History, Coverage and Requirement all together in order to improve the selection process. This will also ensure that the rejection of some efficient test cases is reduced when compared to the selection process in conventional methods, most of them making use of a single parameter for test case selection. These Test cases are further optimized using Genetic Algorithm. Results indicate that the proposed technique is much more efficient in terms of selecting the test cases when compared to conventional techniques, thereby improving fault detection rate.  

Test Suite Minimization in Regression Testing Using Hybrid Approach of ACO and GA

2018 ◽  
Vol 9 (3) ◽  
pp. 88-104
Author(s):  
Abhishek Pandey ◽  
Soumya Banerjee
Keyword(s):  
Hybrid Approach ◽  
Regression Testing ◽  
Minimum Time ◽  
Test Suite ◽  
Test Case ◽  
Test Cases ◽  
Ant Colony Optimization Algorithm ◽  
Test Case Selection ◽  
Case Selection

This article describes about the application of search-based techniques in regression testing and compares the performance of various search-based techniques for software testing. Test cases tend to increase exponentially as the software is modified. It is essential to remove redundant test cases from the existing test suite. Regression testing is very costly and must be performed in restricted ways to ensure the validity of the existing software. There exist different methods to improve the quality of test cases in terms of the number of faults covered, opposed to the number of statements covered in a minimum time. Different methods exist for this purpose, such as minimization, test case selection, and test case prioritization. In this article, search-based methods are applied to improve the quality of the test suite in order to select a minimum set of test cases which covers all the statements in a minimum time. The whole approach is named search based regression testing. In this paper, the performance of different metaheuristics for test suite minimization problem is also compared with a hybrid approach of ant colony optimization algorithm and genetic algorithm.

scholarly journals A Study of Regression Testing for Trade me Website

2021 ◽  
Author(s):  
Kenil Manishkumar Patel ◽  
Shahid Ali
Keyword(s):  
New Zealand ◽  
Fault Detection ◽  
Software Development ◽  
Critical Role ◽  
Regression Testing ◽  
Test Suite ◽  
Test Cases ◽  
Regression Test ◽  
Manual Testing ◽  
Research Analysis

Regression testing plays a critical role to verify the functionality testing of a product. Trade Me is New Zealand based website. It is one of the major websites in New Zealand dealing in buying and selling online. The aim of this research is to find out the functionalities of Trade Me website after injecting new features. Automation regression suite is used to execute test scripts which helped the company to save time and cost compared to manual testing. Automation regression test suite also helped to prioritize test cases are designed in such a way that it can maximize the fault detection. For research analysis scrum methodology is used to meet the ultimate desires of software development companies and to increase the client satisfaction.

Refinement & Reduction of Cases for Regression Testing to Measure Software Reliability

2015 ◽  
Vol 8 (2) ◽  
Author(s):  
Dr. Rajat Sheel Jain ◽  
Dr. Amit Gupta
Keyword(s):  
Fault Detection ◽  
Software Quality ◽  
Software Reliability ◽  
Execution Time ◽  
Regression Testing ◽  
Test Suite ◽  
Test Cases ◽  
Detection Capability ◽  
Software Application ◽  
System Under Test

Requirements are very important features for the designing of any software application. Test suite creation is a big and hectic task for the Software Quality Analyst. We propose to develop a technique for analysis of Covered Requirement and its impact on the designed Test suite. The requirement associated with the test cases accepts specification like execution time, costing for minimization of test suite. The specification analyser compares the information about the techniques like Precision, Efficiency, Inclusiveness and Generality. By reducing the test suite size, we can reduce the execution cost and time, validation and management of the test cases from the suite for future releases of the software and able to maintain the fault detection capability by reusing the refined test cases. The requirement coverage will increase time-effectiveness in sorting the features of the application and reduces the duplicacy. An improved rate of testing activity will provide faster feedback of the system under test.

Comparison of Multi-Objective Evolutionary Algorithms to Prioritize Regression Test Cases

2021 ◽  
Vol 9 (12) ◽  
pp. 1445-1454
Keyword(s):  
Fault Detection ◽  
Evolutionary Algorithms ◽  
Fitness Function ◽  
Optimal Solution ◽  
Test Suite ◽  
Test Case ◽  
Test Cases ◽  
Nsga Ii ◽  
Multi Objective ◽  
Regression Test

Regression testing is one of the most critical testing activities among software product verification activities. Nevertheless, resources and time constraints could inhibit the execution of a full regression test suite, hence leaving us in confusion on what test cases to run to preserve the high quality of software products. Different techniques can be applied to prioritize test cases in resource-constrained environments, such as manual selection, automated selection, or hybrid approaches. Different Multi-Objective Evolutionary Algorithms (MOEAs) have been used in this domain to find an optimal solution to minimize the cost of executing a regression test suite while obtaining maximum fault detection coverage as if the entire test suite was executed. MOEAs achieve this by selecting set of test cases and determining the order of their execution. In this paper, three Multi Objective Evolutionary Algorithms, namely, NSGA-II, IBEA and MoCell are used to solve test case prioritization problems using the fault detection rate and branch coverage of each test case. The paper intends to find out what’s the most effective algorithm to be used in test cases prioritization problems, and which algorithm is the most efficient one, and finally we examined if changing the fitness function would impose a change in results. Our experiment revealed that NSGA-II is the most effective and efficient MOEA; moreover, we found that changing the fitness function caused a significant reduction in evolution time, although it did not affect the coverage metric.

Adapting Test-Driven Development to Build Robust Web Services

2013 ◽  
pp. 218-237
Author(s):  
Nuno Laranjeiro ◽  
Marco Vieira
Keyword(s):  
Web Services ◽  
Software Development ◽  
Source Code ◽  
Test Cases ◽  
Services Research ◽  
Test Driven Development ◽  
Robustness Testing ◽  
Open Source Code ◽  
Testing Approach ◽  
Software Services

Web services are increasingly being used in business critical environments as a mean to provide a service or integrate distinct software services. Research indicates that, in many cases, services are deployed with robustness issues (i.e., displaying unexpected behaviors when in presence of invalid input conditions). Recently, Test-Driven Development (TDD) emerged as software development technique based on test cases that are defined before development, as a way to validate functionalities. However, programmers typically disregard the verification of limit conditions, such as the ones targeted by robustness testing. Moreover, in TDD, tests are created before developing the functionality, conflicting with the typical robustness testing approach. This chapter discusses the integration of robustness testing in TDD for improving the robustness of web services during development. The authors requested three programmers to create a set of services based on open-source code and to implement different versions of the services specified by TPC-App, using both TDD and the approach presented in this chapter. Results indicate that TDD with robustness testing is an effective way to create more robust services.

Sign in / Sign up

Export Citation Format

Share Document