An Empirical analysis of Open Source Software Defects data through Software Reliability Growth Models [PDF]
, 2013 The purpose of this study is to analyze the reliability growth of Open Source Software (OSS) using Software Reliability Growth Models (SRGM). This study uses defects data of twenty five different releases of five OSS projects.
Najeeb Ullah +3 more
core +1 more source
On the Cost and Profit of Software Defect Prediction
, 2021 The article "On the cost and profit of software defect prediction" published in the IEEE Transactions on Software Engineering in 2019 propose a cost model to enable the estimation of the expected profit when using machine learning models for defect ...
Herbold, Steffen
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Cross-Project Defect Prediction Method Based on Manifold Feature Transformation
Future Internet, 2021 Traditional research methods in software defect prediction use part of the data in the same project to train the defect prediction model and predict the defect label of the remaining part of the data.
Yu Zhao, Yi Zhu, Qiao Yu, Xiaoying Chen
doaj +1 more source
Prediction of Defective Software Modules Using Class Imbalance Learning
Applied Computational Intelligence and Soft Computing, 2016 Software defect predictors are useful to maintain the high quality of software products effectively. The early prediction of defective software modules can help the software developers to allocate the available resources to deliver high quality software ...
Divya Tomar, Sonali Agarwal
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Hybrid Defect Prediction Model Based on Counterfactual Feature Optimization
Human-Centric Intelligent Systems, 2023 Software defect prediction is critical to ensuring software quality. Researchers have worked on building various defect prediction models to improve the performance of defect prediction.
Wei Zheng +5 more
doaj +1 more source
Investigating Automatic Static Analysis Results to Identify Quality Problems: an Inductive Study [PDF]
, 2012 Background: Automatic static analysis (ASA) tools examine source code to discover "issues", i.e. code patterns that are symptoms of bad programming practices and that can lead to defective behavior.
Nico Zazworka +13 more
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An empirical study on the effectiveness of data resampling approaches for cross-project software defect prediction [PDF]
, 2022 Cross-project defect prediction (CPDP), where data from different software projects are used to predict defects, has been proposed as a way to provide data for software projects that lack historical data.
MacDonell SG +3 more
core +1 more source
Bottlenecks in Software Defect Prediction Implementation in Industrial Projects
Foundations of Computing and Decision Sciences, 2015 Case studies focused on software defect prediction in real, industrial software development projects are extremely rare. We report on dedicated R&D project established in cooperation between Wroclaw University of Technology and one of the leading ...
Hryszko Jarosław, Madeyski Lech
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Cross-Project Defect Prediction Method Based on Instance Filtering and Transfer [PDF]
Jisuanji gongcheng, 2020 In cross-project software defect prediction,original datasets collected and labeled by humans are often corrupted by noisy,and large distribution differences exist between data of the source project and target project.To address the problem,this paper ...
FAN Guisheng, DIAO Xuyang, YU Huiqun, CHEN Liqiong
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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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