Results 271 to 280 of about 111,109 (312)

A Three-Stage Defect Prediction Model for Cross-Project Defect Prediction

2017 International Conference on Dependable Systems and Their Applications (DSA), 2017
Aiming at dealing with the problems of the data deficiency, data high dimensionality in software defect prediction (SDP), this paper proposes a novel three-stage defect prediction model. First we introduced the information flow algorithm (IFA) to do the causality analysis to choose the most representative feature subset.
Song Huang, Yaning Wu, Haijin Ji, Chengzu Bai   +3 more
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Data Transformation in Cross-project Defect Prediction

Empirical Software Engineering, 2017
Software metrics rarely follow a normal distribution. Therefore, software metrics are usually transformed prior to building a defect prediction model. To the best of our knowledge, the impact that the transformation has on cross-project defect prediction models has not been thoroughly explored.
Feng Zhang, Iman Keivanloo, Ying Zou
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Cross Projects Defect Prediction Modeling

2019
Software defect prediction has been much studied in the field of research in Software Engineering. Within project Software defect prediction works well as there is sufficient amount of data available to train any model. But rarely local training data of the projects is available for predictions.
Lipika Goel, Sonam Gupta
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Heterogeneous Cross Project Defect Prediction – A Survey

2020
In the testing phase of Software Development Life Cycle (SDLC), Software Defect Prediction (SDP) is one of the pivotal task which finds the modules that are more vulnerable to defects and therefore need substantial testing for the early identification of these defects. A lot of work has been done on Cross - Project Defect Prediction (CPDP) that aims to
Rohit Vashisht, Syed Afzal Murtaza Rizvi
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Cross-Version Defect Prediction using Cross-Project Defect Prediction Approaches

Proceedings of the 14th International Conference on Predictive Models and Data Analytics in Software Engineering, 2018
Background: Specifying and removing defects before release deserve extra cost for the success of software projects. Long-running projects experience multiple releases, and it is a natural choice to adopt cross-version defect prediction (CVDP) that uses information from older versions. A past study shows that feeding multi older versions data may have a
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Analytical Approach to Cross Project Defect Prediction

2020
Ensuring software quality has been an issue since the very beginning of software industry. Now with the advancement in technology, tools and development cycles, new paradigms have emerged to tackle the challenges of software quality management. Software defect prediction (SDP) is one of those to help recognize the code blocks, classes, methods or files
Vikas Suhag, Anchal Garg, S. K. Dubey, B. K. Sharma   +3 more
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Recalling the "imprecision" of cross-project defect prediction

Proceedings of the ACM SIGSOFT 20th International Symposium on the Foundations of Software Engineering, 2012
There has been a great deal of interest in defect prediction: using prediction models trained on historical data to help focus quality-control resources in ongoing development. Since most new projects don't have historical data, there is interest in cross-project prediction: using data from one project to predict defects in another.
Foyzur Rahman, Daryl Posnett, Premkumar Devanbu   +2 more
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Cross-project defect prediction models: L'Union fait la force

2014 Software Evolution Week - IEEE Conference on Software Maintenance, Reengineering, and Reverse Engineering (CSMR-WCRE), 2014
Existing defect prediction models use product or process metrics and machine learning methods to identify defect-prone source code entities. Different classifiers (e.g., linear regression, logistic regression, or classification trees) have been investigated in the last decade.
A. Panichella, OLIVETO, Rocco, A. De Lucia   +2 more
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A literature review on cross project defect prediction

2017 4th IEEE Uttar Pradesh Section International Conference on Electrical, Computer and Electronics (UPCON), 2017
In the area of defect prediction most of the literature comprises of within project defect prediction. It is always not feasible to have the historical data of the similar projects for predictions. Therefore, CPDP (Cross Project Defect Prediction) as a subset of defect prediction in general has become a popular topic in research these days.
Lipika Goel, D. Damodaran, Sunil Kumar Khatri, Mayank Sharma   +3 more
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Manifold Learning for Cross-project Software Defect Prediction

2018 5th IEEE International Conference on Cloud Computing and Intelligence Systems (CCIS), 2018
Traditional software defect prediction studies usually built models using within-project data. However, there are not enough local data repositories for us to build the software defect prediction model in practice. Recently, cross-project software defect prediction (CSDP) has been proposed.
Jing Sun, Xiaoyuan Jing, Xiwei Dong
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