Identifying characteristics of Java methods that may influence branch coverage: An exploratory study on open source projects

Castro, Camila Faria de; Oliveira, Decio de Souza; Eler, Marcelo Medeiros

doi:10.1109/sccc.2016.7835998

Cited by 4 publications

(2 citation statements)

References 18 publications

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“…• WMC: write more simple methods and invest in refactoring to get complex methods more simple. Experienced developers and testers know that methods and classes with complex logic are more difficult to test, and recent studies have been conducted to quantify the influence of characteristics of programs on the testing activity (de Castro et al, 2016). The more complex the method, the less lines of code are covered.…”

Section: Discussion and Recommendationsmentioning

confidence: 99%

An Empirical Analysis of the Correlation between CK Metrics, Test Coverage and Mutation Score

Cruz

Eler

2017

Proceedings of the 19th International Conference on Enterprise Information Systems

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In this paper we investigate the correlation between test coverage, mutation score and object-oriented systems metrics. First we conducted a literature review to obtain an initial model of testability and existing object-oriented metrics related to testability. Thus we selected four open source system whose test cases were available and calculated the correlation between the metrics collected and the line coverage, branches coverage and mutation score. Preliminary results show that some CK metrics, which are strongly related to system's design, influence mainly line coverage and mutation score, thus they can influence systems testability.

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Section: Discussion and Recommendationsmentioning

confidence: 99%

An Empirical Analysis of the Correlation between CK Metrics, Test Coverage and Mutation Score

Cruz

Eler

2017

Proceedings of the 19th International Conference on Enterprise Information Systems

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“…Control flows reflect the interactive type and strength between components. Analysis based on control flow, such as complexity measurement [11], branch coverage testing [12] and defect prediction [13], manifests the performance of uncovering potential implications in software specification mining. Thus, more essence of software dynamic behaviors will be seen through more insights emerging in control patterns of software executions.…”

Section: Introductionmentioning

confidence: 99%

Mining of Probabilistic Controlling Behavior Model From Dynamic Software Execution Trace

Ren

Zhao

et al. 2019

IEEE Access

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Complex functional integration leads to intricate logical control flows which in turn presents a great challenge to construct software behavior models. In this paper, we propose a probabilistic software behavior model by mining the execution traces using control flow analysis. To describe the interactions between software components, a semantic characterization method is developed. A tracing mechanism is designed to collect execution logs, based on which algorithms are developed to recognize detailed control relations. Moreover, dynamic behavioral frequencies are statistically estimated which provide quantitative data for behavior prediction. Finally, a multi-label enhanced software complex network model, which holds single or composite call relations and calling probabilities, is constructed with the purpose of profiling systematically and structurally. An illustrative example shows that the modeling approach can discover interactive patterns correctly and characterize software behavior scientifically. The method has been used in seven real-world projects, and results show that the proposed model is effective on discovering the complexities of software behavior and hence help to detect defects in software design and to improve performance.INDEX TERMS Dynamic software modeling, control flow, complex network, software behavior.

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Using a cluster analysis method for grouping classes according to their inferred testability: An investigation of CK metrics, code coverage and mutation score

Cruz

Eler

2017

2017 36th International Conference of the Chilean Computer Science Society (SCCC)

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Identifying characteristics of Java methods that may influence branch coverage: An exploratory study on open source projects

Cited by 4 publications

References 18 publications

An Empirical Analysis of the Correlation between CK Metrics, Test Coverage and Mutation Score

An Empirical Analysis of the Correlation between CK Metrics, Test Coverage and Mutation Score

Mining of Probabilistic Controlling Behavior Model From Dynamic Software Execution Trace

Using a cluster analysis method for grouping classes according to their inferred testability: An investigation of CK metrics, code coverage and mutation score

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