Automation Architecture for Bayesian Network Based Test Case Prioritization and Execution

Ufuktepe, Ekincan; Tuğlular, Tuğkan

doi:10.1109/compsac.2016.71

Cited by 4 publications

(3 citation statements)

References 9 publications

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“…In order to quantify and calculate the probability of a method being impacted, we need to numerically represent changes as well. Code Change Sniffer [5] and previous studies [16], [17], [18] have numerically represented the amount of change based on the number of changed bytecode instructions in a method/class and the total number of bytecode instructions in a method/class. Code Change Sniffer works in a methodlevel granularity, therefore, our proposed TCP algorithm is also based on method-level information.…”

Section: A Call Graph Information Extractionmentioning

confidence: 99%

“…For instance, if a test case covers a set of program elements, the probability of selecting other test cases that cover the same elements will be lowered. In addition, Ufuktepe et al [18] extended the work of [16] by providing a fully automated test case prioritization and execution architecture by using different tools. All these studies have used Bayesian Network and focused on the class-level test case prioritization, by using change information, but they do not include information on data dependency.…”

Section: Related Workmentioning

confidence: 99%

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Application of the Law of Minimum and Dissimilarity Analysis to Regression Test Case Prioritization

Ufuktepe

Tuğlular

2023

IEEE Access

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Regression testing is one of the most expensive processes in testing. Prioritizing test cases in regression testing is critical for the goal of detecting the faults sooner within a large set of test cases. We propose a test case prioritization (TCP) technique for regression testing called LoM-Score inspired by the Law of Minimum (LoM) from biology. This technique calculates the impact probabilities of methods calculated by change impact analysis with forward slicing and orders test cases according to LoM. However, this ordering doesn't consider the possibility that consecutive test cases may be covering the same methods repeatedly. Thereby, such ordering can delay the time of revealing faults that exist in other methods.To solve this problem, we enhance the LoM-Score TCP technique with an adaptive approach, namely with a dissimilarity-based coordinate analysis approach. The dissimilarity-based coordinate analysis uses Jaccard Similarity for calculating the similarity coefficients between test cases in terms of covered methods and the enhanced technique called Dissimilarity-LoM-Score (Dis-LoM-Score) applies a penalty with respective on the ordered test cases. We performed our case study on 10 open-source Java projects from Defects4J, which is a dataset of real bugs and an infrastructure for controlled experiments provided for software engineering researchers. Then, we hand-seeded multiple mutants generated by Major, which is a mutation testing tool. Then we compared our TCP techniques LoM-Score and Dis-LoM-Score with the four traditional TCP techniques based on their Average Percentage of Faults Detected (APFD) results.INDEX TERMS Change impact analysis, regression testing, software testing, test case prioritization.

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Section: A Call Graph Information Extractionmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Application of the Law of Minimum and Dissimilarity Analysis to Regression Test Case Prioritization

Ufuktepe

Tuğlular

2023

IEEE Access

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“…The researchers indicated that the CBN approach outperformed both the BN and BNA approaches, with recorded APFD achievements of 86.9, 81.2 and 83.7 respectively. Ufuktepe and Tuglular [19] also suggested an automated platform and tool for implementing the first BN-based framework which was introduced by Mirarab and Tahvildari [15].…”

Section: A Bn-based Frameworkmentioning

confidence: 99%

Regression Test Case Prioritization Frameworks: Challenges and Future Directions

Ba-Quttayyan*,

Mohd,

Yusof

2019

IJRTE

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Regression testing is a necessary maintenance activity in the software industry where modified software programs are revalidated to make sure that changes do not adversely affect their behavior. Test case prioritization (TCP) is one of the most effective methods in regression testing whereby test cases are rescheduled in an appropriate order for execution to increase test effectiveness in meeting some performance goals such as increasing the rate of fault detection. This paper explores efforts that have been carried out in relation to TCP frameworks. Through the review of related literature, ten existing frameworks were identified, classified and reviewed whereby two are Bayesian network-based, five are multi-objective, while the rest are varied in terms of aspects and purposes. Accordingly, this study analyzes those frameworks based on their proposed year, TCP factors, number of test cases used, evaluations metric and criteria as well as experimental subjects. The results showed that the stated frameworks are not integrated with nature-inspired algorithms as enhancing optimization techniques while several others were insufficiently evaluated according to stated evaluation criteria and metrics for the effective and practical testing process. There is also a scarcity of frameworks that focus on regression test efficiency. This study indicates the need for further research into the topic to enhance TCP frameworks that focus on several directions for practical considerations in this field such as evaluation issues, specific knowledge dependency, and objective deviation. At the end of this study, several future directions such as nature-inspired algorithms assistance are proposed, and a number of limitations are identified and highlighted.

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Efficient Test Case Prioritization Using Bayesian Networks: A Probabilistic Approach for Improved Software Testing

Rawat,

Somani,

Tripathi

2024

2024 International Conference on Computing and Data Science (ICCDS)

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Automation Architecture for Bayesian Network Based Test Case Prioritization and Execution

Cited by 4 publications

References 9 publications

Application of the Law of Minimum and Dissimilarity Analysis to Regression Test Case Prioritization

Application of the Law of Minimum and Dissimilarity Analysis to Regression Test Case Prioritization

Regression Test Case Prioritization Frameworks: Challenges and Future Directions

Efficient Test Case Prioritization Using Bayesian Networks: A Probabilistic Approach for Improved Software Testing

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