The effectiveness of software metrics in identifying error-prone classes in post-release software evolution process

Shatnawi, Raed; Wei, Li

doi:10.1016/j.jss.2007.12.794

Cited by 160 publications

(106 citation statements)

References 21 publications

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“…Software engineering researchers have additionally used OSS products to study general software engineering problems like evolution [211], cloning [114], and the use of metrics to identify error prone classes [170].…”

Section: Open Source Softwarementioning

confidence: 99%

Adoption of open source software in software-intensive organizations – A systematic literature review

Hauge¹,

Ayala²,

Conradi³

2010

Information and Software Technology

195

113

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Context: Open source software (OSS) is changing the way organizations develop, acquire, use, and commercialize software. Objective: This paper seeks to identify how organizations adopt OSS, classify the literature according to these ways of adopting OSS, and with a focus on software development evaluate the research on adoption of OSS in organizations. Method: Based on the systematic literature review method we reviewed publications from 24 journals and seven conference and workshop proceedings, published between 1998 and 2008. From a population of 24289 papers, we identified 112 papers which provide empirical evidence on how organizations actually adopt OSS. Results: We show that adopting OSS involves more than simply using OSS products. We moreover provide a classification framework consisting of six distinctly different ways in which organizations adopt OSS. This framework is used to illustrate some of the opportunities and challenges organizations meet when approaching OSS, to show that OSS can be adopted successfully in different ways, and to organize and review existing research. We find that this research does not sufficiently describe the context of the organizations studied. It is furthermore fragmented and fails to benefit fully from related research fields. Finally, we present directions for future research.

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Section: Open Source Softwarementioning

confidence: 99%

Adoption of open source software in software-intensive organizations – A systematic literature review

Hauge¹,

Ayala²,

Conradi³

2010

Information and Software Technology

195

113

View full text Add to dashboard Cite

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“…According to these results, the object-oriented software metrics and method-level metrics are complementary for software fault prediction problem. Additionally, obtained results of this study are competitive with the studies which use data-driven methods for make prediction (i.e., [5] (RF -AUC: 0.79); [7] (NB -AUC: 0.79), [8] (Bootstrap Aggregating -AUC: 0.82); [29] (Multi-nominal Multivariate Logistic Regression -AUC: 0.79)). As a result, FIS is a plausible solution method to be used for software fault prediction.…”

Section: Journal Of Softwarementioning

confidence: 75%

Software Fault Inference Based on Expert Opinion

Erturkr¹,

Sezer²

2015

JSW

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Software fault prediction is a process which predicts that the software modules are faulty or not by using the software metrics and some soft computing methods. Software metrics are divided into two main categories such as object-oriented and method-level metrics. While class relationships and dependencies are covered by object-oriented metrics, behaviors of the classes can be also measured by method-level metrics. Actually, the complementary relationship between these metric groups is focused in this study and different predictive models are built by using different parameter sets. Each parameter set includes some object-oriented and some method-level metrics. Furthermore, Mamdani style fuzzy inference system (FIS) is employed here to predict faultiness. In contrast to data-driven methods, FIS does not require historical or previous data for modeling. In fact, it is a rule-based approach and rules are extracted with the help of domain experts. In this study, the dataset which consists of the method-level and the class-level metrics' values that are collected from KC1 project of PROMISE repository is employed and most successful model whose performance is 0.8181 according to the evaluation criteria (the area under receiver operating characteristics (ROC) curve (AUC)) is built with the parameters of "coupling between object", "line of code" and, "cyclomatic complexity".

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“…Shatnawi, Raed, and Wei Li [12] examined three releases of the Eclipse project and discovered that however while some others metrics can still predict class error proneness in three errorseverity categories, the accuracy of the prediction decreased from release to release. Furthermore, they discovered that the prediction can't be used to construct a metrics model to recognize error-prone classes with acceptable accuracy.…”

Section: Literature Surveymentioning

confidence: 99%

A Study of Various Static and Dynamic Metrics for Open Source Software

Vesra¹,

Rahul²

2015

IJCA

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Software metrics is developed and utilized by the different software organizations for evaluating and assuring software code quality, operation, and maintenance. Software metrics measure various kinds of software complexity like size metrics, control flow metrics and data flow metrics. These software complexities must certainly be continuously calculated, followed, and controlled. Among the main objectives of software metrics is that pertains to a procedure and product metrics. It is definitely considered that high level of complexity in a component is bad compared to a low level of complexity in a module. Software metrics may be used in various phases of software development lifecycle. In this paper, a survey on various software metrics has been done. Moreover they are categorized into static and dynamic metrics. The paper ends with in conclusion and the near future scope to overcome some issues for the software metrics.

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The effectiveness of software metrics in identifying error-prone classes in post-release software evolution process

Cited by 160 publications

References 21 publications

Adoption of open source software in software-intensive organizations – A systematic literature review

Adoption of open source software in software-intensive organizations – A systematic literature review

Software Fault Inference Based on Expert Opinion

A Study of Various Static and Dynamic Metrics for Open Source Software

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