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Juan Murillo-Morera, Carlos Castro-Herrera, Javier Arroyo, Ruben Fuentes-Fernandez
Pág. 114 - 137
Today, it is common for software projects to collect measurement data through development processes. With these data, defect prediction software can try to estimate the defect proneness of a software module, with the objective of assisting and guiding so...
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Haoxiang Shi, Jun Ai, Jingyu Liu and Jiaxi Xu
Software defect prediction is a popular method for optimizing software testing and improving software quality and reliability. However, software defect datasets usually have quality problems, such as class imbalance and data noise. Oversampling by genera...
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Amani Alqarni and Hamoud Aljamaan
Software defect prediction is an active research area. Researchers have proposed many approaches to overcome the imbalanced defect problem and build highly effective machine learning models that are not biased towards the majority class. Generative adver...
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Mahesha Pandit, Deepali Gupta, Divya Anand, Nitin Goyal, Hani Moaiteq Aljahdali, Arturo Ortega Mansilla, Seifedine Kadry and Arun Kumar
DePaaS has the potential to be used as a global, shared platform for availing software defects prediction services by choosing appropriate base project, defect prediction model and prediction granularity. Over time, DePaaS can potentially become a rich s...
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Arvind Kumar Gangwar, Sandeep Kumar and Alok Mishra
The early and accurate prediction of defects helps in testing software and therefore leads to an overall higher-quality product. Due to drift in software defect data, prediction model performances may degrade over time. Very few earlier works have invest...
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Yu Zhao, Yi Zhu, Qiao Yu and Xiaoying Chen
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. However, in the practical realm of software developme...
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Junhua Ren and Feng Liu
Power law describes a common behavior in which a few factors play decisive roles in one thing. Most software defects occur in very few instances. In this study, we proposed a novel approach that adopts power law function characteristics for software defe...
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Can Cui, Bin Liu, Peng Xiao and Shihai Wang
It is popular to use software defect prediction (SDP) techniques to predict bugs in software in the past 20 years. Before conducting software testing (ST), the result of SDP assists on resource allocation for ST. However, DP usually works on fine-level t...
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Kaiyuan Jiang, Yutong Zhang, Haibin Wu, Aili Wang and Yuji Iwahori
Software systems are now ubiquitous and are used every day for automation purposes in personal and enterprise applications; they are also essential to many safety-critical and mission-critical systems, e.g., air traffic control systems, autonomous cars, ...
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Abdullateef Oluwagbemiga Balogun, Shuib Basri, Said Jadid Abdulkadir and Ahmad Sobri Hashim
Software Defect Prediction (SDP) models are built using software metrics derived from software systems. The quality of SDP models depends largely on the quality of software metrics (dataset) used to build the SDP models. High dimensionality is one of the...
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