Results 51 to 60 of about 16,545 (157)
Interpretable Software Defect Prediction from Project Effort and Static Code Metrics
ComputersSoftware defect prediction models enable test managers to predict defect-prone modules and assist with delivering quality products. A test manager would be willing to identify the attributes that can influence defect prediction and should be able to ...
Susmita Haldar, Luiz Fernando Capretz
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Dissimilarity Space Based Multi-Source Cross-Project Defect Prediction
Algorithms, 2019 Software defect prediction is an important means to guarantee software quality. Because there are no sufficient historical data within a project to train the classifier, cross-project defect prediction (CPDP) has been recognized as a fundamental approach.
Shengbing Ren +3 more
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Cross-Project Software Defect Prediction Based on Domain Adaptation and Feature Fusion
AlgorithmsWith the advancement of computer science, software has become increasingly prevalent across all facets of society, making software quality issues a focal point of industry concern.
Guanhua Guo, Yinglei Song, Peng Zhang
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Research and Appalication of Software Defect Predictionn based on BP-Migration learning
MATEC Web of Conferences, 2018 Software Defect Prediction has been an important part of Software engineering research since the 1970s. This technique is used to calculate and analyze the measurement and defect information of the historical software module to complete the defect ...
Zhang Jie +4 more
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Research on Software Defect Prediction Models Combining Static Analysis Warnings [PDF]
Jisuanji kexue yu tansuoStatic analysis warnings, as an important software quality metric, are widely used to identify potential violations in the source code. Recent studies have shown that static analysis warnings are applied in code smell detection and just-in-time defect ...
WU Haitao, MA Jingyue, GAO Jianhua
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Seml: A Semantic LSTM Model for Software Defect Prediction
IEEE Access, 2019 Software defect prediction can assist developers in finding potential bugs and reducing maintenance cost. Traditional approaches usually utilize software metrics (Lines of Code, Cyclomatic Complexity, etc.) as features to build classifiers and identify ...
Hongliang Liang +3 more
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An Adversarial Discriminative Convolutional Neural Network for Cross-Project Defect Prediction
IEEE Access, 2020 Cross-project defect prediction (CPDP) is a promising approach to help to allocate testing efforts efficiently and guarantee software reliability in the early software lifecycle.
Lei Sheng, Lu Lu, Junhao Lin
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A systematic mapping study on cross-project defect prediction
CoRR, 2017 Cross-Project-Defect Prediction as a sub-topic of defect prediction in general has become a popular topic in research. In this article, we present a systematic mapping study with the focus on CPDP, for which we found 50 publications. We summarize the approaches presented by each publication and discuss the case study setups and results. We discovered a
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ALTRA: Cross-Project Software Defect Prediction via Active Learning and Tradaboost
IEEE Access, 2020 Cross-project defect prediction (CPDP) methods can be used when the target project is a new project or lacks enough labeled program modules. In these new target projects, we can easily extract and then measure these modules with software measurement ...
Zhidan Yuan +3 more
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Integrated Approach to Software Defect Prediction
IEEE Access, 2017 Software defect prediction provides actionable outputs to software teams while contributing to industrial success. Empirical studies have been conducted on software defect prediction for both cross-project and within-project defect prediction.
Ebubeogu Amarachukwu Felix, Sai Peck Lee
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