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Reliability prediction for fault-tolerant software architectures
Proceedings of the joint ACM SIGSOFT conference -- QoSA and ACM SIGSOFT symposium -- ISARCS on Quality of software architectures -- QoSA and architecting critical systems -- ISARCS, 2011Software fault tolerance mechanisms aim at improving the reliability of software systems. Their effectiveness (i.e., reliability impact) is highly application-specific and depends on the overall system architecture and usage profile. When examining multiple architecture configurations, such as in software product lines, it is a complex and error-prone ...
Franz Brosch +3 more
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Software Fault Prediction Process
2018Accurate detection and early removal of software faults during the software development can reduce the overall cost of software development and can result in the improved software quality product. These inherent advantages of software fault prediction have attracted many researchers to focus on the software fault prediction.
Sandeep Kumar, Santosh Singh Rathore
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Types of Software Fault Prediction
2018A large number of researchers have presented various fault prediction studies to predict the fault-proneness of the given software system. These fault prediction studies reported the results in term of different–different contexts. Depending upon the context of the results, a fault prediction model can classify a software module into faulty or non ...
Sandeep Kumar, Santosh Singh Rathore
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Mining software repositories for comprehensible software fault prediction models
Journal of Systems and Software, 2008Software managers are routinely confronted with software projects that contain errors or inconsistencies and exceed budget and time limits. By mining software repositories with comprehensible data mining techniques, predictive models can be induced that offer software managers the insights they need to tackle these quality and budgeting problems in an ...
Olivier Vandecruys +5 more
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An iterative semi-supervised approach to software fault prediction
Proceedings of the 7th International Conference on Predictive Models in Software Engineering, 2011Background: Many statistical and machine learning techniques have been implemented to build predictive fault models. Traditional methods are based on supervised learning. Software metrics for a module and corresponding fault information, available from previous projects, are used to train a fault prediction model.
Huihua Lu, Bojan Cukic, Mark Vere Culp
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Prediction models for software fault correction effort
Proceedings Fifth European Conference on Software Maintenance and Reengineering, 2002We have developed a model to explain and predict the effort associated with changes made to software to correct faults while it is undergoing development. Since the effort data available for this study is ordinal in nature, ordinal response models are used to explain the effort in terms of measures of fault locality and the characteristics of the ...
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Issue-Driven Features for Software Fault Prediction
SSRN Electronic Journal, 2022Amir Elmishali, Meir Kalech
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Improving Software Fault Prediction With Threshold Values
2018 26th International Conference on Software, Telecommunications and Computer Networks (SoftCOM), 2018Software fault prediction has been studied by many researchers to assess the quality of software and to predict where faults may appear in future. However, the performance of fault prediction degrades because of many reasons including unlabeled instances or data imbalance, i.e., modules that contain faults are minority.
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Sine-Cosine Algorithm for Software Fault Prediction
2021 IEEE International Conference on Software Maintenance and Evolution (ICSME), 2021Tamanna Sharma, Om Prakash Sangwan
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