Regression testing is performed to provide confidence that changes in a part of software do not affect other parts of the software. An execution of all existing test cases is the best way to re-establish this confidence. However, regression testing is an expensive process---there might be insufficient resources (e.g., time, workforce) to allow for the re-execution of all test cases. Regression test prioritization techniques attempt to re-order a regression test suite based on some criteria so that highest priority test cases are executed earlier. In this study, we want to prioritize test cases for regression testing based on the dependency network of faults. In software testing, it is common that some faults are consequences of other faults (leading faults). Moreover, dependent faults can be removed if and only if the leading faults have been removed. Our goal is to prioritize test cases so that test cases that exposed leading faults (the most central faults in the fault dependency network) in the system testing phase, are executed first in regression testing. We present ComReg, a test case prioritization technique based on the dependency network of faults. We model a fault dependency network as a directed graph and identify leading faults to prioritize test cases for regression testing. We use a centrality aggregation technique which considers six network representative centrality metrics to identify leading faults in the fault dependency network. We also discuss the use of fault communities to select an arbitrary percentage of the test cases from a prioritized regression test suite. We conduct a case study that evaluates the effectiveness and applicability of the proposed method.
Researchers used a number of other criteria to prioritize test cases. prioritized test cases based on historical change records in @cite_48 . They proposed a methodology for determining the effect of a software feature change and then prioritized regression test cases by gathering software change records and analyzing them through singular value decomposition. @cite_28 introduced distribution-based filtering and prioritized test cases based on the distribution of the profiles of test cases in the multi-dimensional profile space. @cite_21 prioritized test cases for web applications. They prioritized test suites by test lengths, frequency of appearance of request sequences and systematic coverage of parameter-values and their interactions. @cite_50 introduced a prioritization technique based on data-flow analysis. They focused on the definition and use of program variables for the data-flow analysis. @cite_46 prioritized test cases using relevant slices. @cite_49 prioritized test cases in a black box environment.
@cite_28 @cite_48 @cite_21 @cite_50 @cite_49 @cite_46
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Test case prioritization techniques involve scheduling test cases for regression testing in an order that increases their effectiveness at meeting some performance goal. This is inefficient to re execute all the test cases in regression testing following the software modifications. Using information obtained from previous test case execution, prioritization techniques order the test cases for regression testing so that most beneficial are executed first thus allows an improved effectiveness of testing. One performance goal, rate of dependency detected among faults, measures how quickly dependency among faults are detected within the regression testing process. An improved rate of fault dependency can provide faster feedback on software and let developers start debugging on the severe faults that cause other faults to appear later. This paper presents the new metric for assessing rate of fault dependency detection and an algorithm to prioritize test cases. Using the new metric the effectiveness of this prioritization is shown comparing it with non-prioritized test case. Analysis proves that prioritized test cases are more effective in detecting dependency among faults. Test case prioritization techniques have been shown to be beneficial for improving regression-testing activities. With prioritization, the rate of fault detection is improved, thus allowing testers to detect faults earlier in the system-testing phase. Most of the prioritization techniques to date have been code coverage-based. These techniques may treat all faults equally. We build upon prior test case prioritization research with two main goals: (1) to improve user-perceived software quality in a cost effective way by considering potential defect severity and (2) to improve the rate of detection of severe faults during system-level testing of new code and regression testing of existing code. We present a value-driven approach to system-level test case prioritization called the prioritization of requirements for test (PORT). PORT prioritizes system test cases based upon four factors: requirements volatility, customer priority, implementation complexity, and fault proneness of the requirements. We conducted a PORT case study on four projects developed by students in advanced graduate software testing class. Our results show that PORT prioritization at the system level improves the rate of detection of severe faults. Additionally, customer priority was shown to be one of the most important prioritization factors contributing to the improved rate of fault detection. Regression test prioritization techniques re-order the execution of a test suite in an attempt to ensure that defects are revealed earlier in the test execution phase. In prior work, test suites were prioritized with respect to their ability to satisfy control flow-based and mutation-based test adequacy criteria. In this paper, we propose an approach to regression test prioritization that leverages the all-DUs test adequacy criterion that focuses on the definition and use of variables within the program under test. Our prioritization scheme is motivated by empirical studies that have shown that (i) tests fulfilling the all-DUs test adequacy criteria are more likely to reveal defects than those that meet the control flow-based criteria, (ii) there is an unclear relationship between all-DUs and mutation-based criteria, and (iii) mutation-based testing is significantly more expensive than testing that relies upon all-DUs.In support of our prioritization technique, we provide a formal statement of the algorithms and equations that we use to instrument the program under test, perform test suite coverage monitoring, and calculate test adequacy. Furthermore, we examine the architecture of a tool that implements our novel prioritization scheme and facilitates experimentation. The use of this tool in a preliminary experimental evaluation indicates that, for three case study applications, our prioritization can be performed with acceptable time and space overheads. Finally, these experiments also demonstrate that the prioritized test suite can have an improved potential to identify defects earlier during the process of test execution. Test case prioritization involves scheduling test cases in an order that increases the effectiveness in achieving some performance goals. One of the most important performance goals is the rate of fault detection. Test cases should run in an order that increases the possibility of fault detection and also that detects the most severe faults at the earliest in its testing life cycle. In this paper, we propose to put forth a model for system level test case prioritization (TCP) from software requirement specification to improve user satisfaction with quality software that can also be cost effective and to improve the rate of severe fault detection. The proposed model prioritizes the system test cases based on the six factors: customer priority, changes in requirement, implementation complexity, completeness, traceability and fault impact. The proposed prioritization technique is validated with two different validation techniques and is experimented in three phases with student projects and two sets of industrial projects and the results show convincingly that the proposed prioritization technique improves the rate of severe fault detection.