Results 281 to 290 of about 198,133 (331)

A Comprehensive Investigation of the Impact of Class Overlap on Software Defect Prediction

IEEE Transactions on Software Engineering, 2023
Software Defect Prediction (SDP) is one of the most vital and cost-efficient operations to ensure the software quality. However, there exists the phenomenon of class overlap in the SDP datasets (i.e., defective and non-defective modules are similar in ...
Lina Gong, Haoxiang Zhang, Jingxuan Zhang, Mingqiang Wei, Zhiqiu Huang   +4 more
semanticscholar   +1 more source

Predicting Defect of Software System

2017
Any particular study on software quality with all desirable attributes of software products can be treated as complete and perfect provided it is defective. Defects continue to be an emerging problem that leads to failure and unexpected behaviour of the system.
Soumi Ghosh, Ajay Rana, Vineet Kansal
openaire   +1 more source

Comprehensive Bibliographic Survey and Forward-Looking Recommendations for Software Defect Prediction: Datasets, Validation Methodologies, Prediction Approaches, and Tools

IEEE Access
The development of reliable software depends heavily on the effective collaboration between teams responsible for development and testing. Despite ongoing efforts, many software programs still contain bugs that can lead to financial losses and business ...
Mohd. Mustaqeem, Mahfooz Alam, Suhel Mustajab, Faisal Alshanketi, Shadab Alam, Mohammed Shuaib   +5 more
semanticscholar   +1 more source

A Learning-to-Rank Approach to Software Defect Prediction

IEEE Transactions on Reliability, 2015
Software defect prediction can help to allocate testing resources efficiently through ranking software modules according to their defects. Existing software defect prediction models that are optimized to predict explicitly the number of defects in a ...
Xiaoxing Yang, Ke Tang, Xin Yao
exaly   +2 more sources

A Software Defect Prediction Method Using a Multivariate Heterogeneous Hybrid Deep Learning Algorithm

Comput. Mater. Continua
Software defect prediction plays a critical role in software development and quality assurance processes. Effective defect prediction enables testers to accurately prioritize testing efforts and enhance defect detection efficiency.
Guisheng Yin, Qi Fei, Zhian Sun, Hao Hu
semanticscholar   +1 more source

A critique of software defect prediction models

IEEE Transactions on Software Engineering, 1999
Many organizations want to predict the number of defects (faults) in software systems, before they are deployed, to gauge the likely delivered quality and maintenance effort. To help in this numerous software metrics and statistical models have been developed, with a correspondingly large literature.
Norman E. Fenton, Martin Neil
openaire   +1 more source

Defect prediction and software risk

Proceedings of the 10th International Conference on Predictive Models in Software Engineering, 2014
Defect prediction has always fascinated researchers and practitioners. The promise of being able to predict the future and act to improve it is hard to resist. However, the operational data used in predictions are treacherous and the prediction is usually done outside the context of the actual development project, making it impossible to employ it for ...
openaire   +1 more source

Prediction and control of ADA software defects

Journal of Systems and Software, 1990
Abstract A study of two Ada projects shows that software defects can be predicted in the development phase. Of all metrics tested, measures of package size proved to be the best predictors of defect densities. The prediction function derived suggests that defect density is very high for small Ada packages, decreases rapidly to reach a minimum for ...
B. Terry Compton, Carol Withrow
openaire   +1 more source

Deep Learning for Software Defect Prediction

Proceedings of the IEEE/ACM 42nd International Conference on Software Engineering Workshops, 2020
Software fault prediction is an important and beneficial practice for improving software quality and reliability. The ability to predict which components in a large software system are most likely to contain the largest numbers of faults in the next release helps to better manage projects, including early estimation of possible release delays, and ...
Safa Omri, Carsten Sinz
openaire   +2 more sources

Unsupervised methods for Software Defect Prediction

Proceedings of the Tenth International Symposium on Information and Communication Technology - SoICT 2019, 2019
Software Defect Prediction (SDP) aims to assess software quality by using machine learning techniques. Recently, by proposing the connectivity-based unsupervised learning method, Zhang et al. have been proven that unsupervised classification has great potential to apply to this problem.
Duy-An Ha, Ting-Hsuan Chen, Shyan-Ming Yuan   +2 more
openaire   +1 more source