Results 211 to 220 of about 16,855 (255)

Cross-project smell-based defect prediction

Soft Computing, 2021
Defect prediction is a technique introduced to optimize the testing phase of the software development pipeline by predicting which components in the software may contain defects. Its methodology trains a classifier with data regarding a set of features measured on each component from the target software project to predict whether the component may be ...
Bruno Sotto-Mayor, Meir Kalech
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A Framework for Homogeneous Cross-Project Defect Prediction

International Journal of Software Innovation, 2021
Often, the prior defect data of the same project is unavailable; researchers thought whether the defect data of the other projects can be used for prediction. This made cross project defect prediction an open research issue. In this approach, the training data often suffers from class imbalance problem.
Lipika Goel, Mayank Sharma, Sunil Kumar Khatri, D. Damodaran   +3 more
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Local modeling approach for cross-project defect prediction

Intelligent Decision Technologies, 2022
Prediction approaches used for cross-project defect prediction (CPDP) are usually impractical because of high false alarms, or low detection rate. Instance based data filter techniques that improve the CPDP performance are time-consuming and each time a new test set arrives for prediction the entire filter procedure is repeated. We propose to use local
Nayeem Ahmad Bhat, Sheikh Umar Farooq
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Multi-objective Cross-Project Defect Prediction

2013 IEEE Sixth International Conference on Software Testing, Verification and Validation, 2013
Cross-project defect prediction is very appealing because (i) it allows predicting defects in projects for which the availability of data is limited, and (ii) it allows producing generalizable prediction models. However, existing research suggests that cross-project prediction is particularly challenging and, due to heterogeneity of projects ...
Gerardo Canfora, Andrea De Lucia, Massimiliano Di Penta, Rocco Oliveto, Annibale Panichella, Sebastiano Panichella   +5 more
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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 0001, Iman Keivanloo, Ying Zou 0001   +2 more
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Using Bandit Algorithms for Project Selection in Cross-Project Defect Prediction

2021 IEEE International Conference on Software Maintenance and Evolution (ICSME), 2021
Background: defect prediction model is built using historical data from previous versions/releases of the same project. However, such historical data may not exist in case of newly developed projects. Alternatively, one can train a model using data obtained from external projects. This approach is known as cross-project defect prediction (CPDP).
Asano, Takuya, Tsunoda, Masateru, Toda, Koji, Tahir, Amjed, Bennin, Kwabena Ebo, Nakasai, Keitaro, Monden, Akito, Matsumoto, Kenichi   +7 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 T. Devanbu   +2 more
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WIFLF: An approach independent of the target project for cross‐project defect prediction

Journal of Software: Evolution and Process, 2022
AbstractCross‐project defect prediction (CPDP) is used to build defect prediction models when data from the target project are not enough. There has been several approaches to improve the performance of CPDP, such as feature transformation and instance selection methods.
Can Cui, Bin Liu 0032, Shihai Wang
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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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