Results 11 to 20 of about 198,133 (331)
Software defect association mining and defect correction effort prediction
IEEE Transactions on Software Engineering, 2006 Much current software defect prediction work focuses on the number of defects remaining in a software system. In this paper, we present association rule mining based methods to predict defect associations and defect correction effort. This is to help developers detect software defects and assist project managers in allocating testing resources more ...
Qinbao Song +2 more
exaly +3 more sources
On the Costs and Profit of Software Defect Prediction [PDF]
IEEE Transactions on Software Engineering, 2021 Under Review (minor revision)
Herbold, Steffen
openaire +4 more sources
Software defect prediction using learning to rank approach [PDF]
Sci Rep, 2023 Software defect prediction (SDP) plays a significant role in detecting the most likely defective software modules and optimizing the allocation of testing resources. In practice, though, project managers must not only identify defective modules, but also
Ali Bou Nassif +6 more
semanticscholar +2 more sources
Enhancing software defect prediction: a framework with improved feature selection and ensemble machine learning [PDF]
PeerJ Comput SciEffective software defect prediction is a crucial aspect of software quality assurance, enabling the identification of defective modules before the testing phase.
Misbah Ali +5 more
semanticscholar +2 more sources
Explainable Comparison of Software Defect Prediction Models [PDF]
Jisuanji kexue, 2023 Software defect prediction has become an important research direction in software testing.The comprehensiveness of defect prediction directly affects the efficiency of testing and program operation.However,the existing defect prediction is based on ...
LI Huilai, YANG Bin, YU Xiuli, TANG Xiaomei
doaj +2 more sources
A trustworthy hybrid model for transparent software defect prediction: SPAM-XAI [PDF]
PLoS OneMaintaining quality in software development projects is becoming very difficult because the complexity of modules in the software is growing exponentially.
Mohd. Mustaqeem +5 more
semanticscholar +2 more sources
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
doaj +2 more sources
Attention based GRU-LSTM for software defect prediction. [PDF]
PLoS ONE, 2021 Software defect prediction (SDP) can be used to produce reliable, high-quality software. The current SDP is practiced on program granular components (such as file level, class level, or function level), which cannot accurately predict failures.
Hafiz Shahbaz Munir +4 more
doaj +2 more sources
IEEE AccessDeep Q-Network (DQN) is a popular deep reinforcement learning algorithm that has demonstrated promising results across a variety of domains. DQN presents a promising solution to the challenge of lowering false positives in software defect prediction ...
Ahmad Muhaimin Ismail +3 more
doaj +2 more sources
A novel generative oversampling for software defect prediction [PDF]
Scientific ReportsSoftware defect prediction is one of the highly active research areas as it allows to focus the testing efforts on the defective modules and reduce the cost of development.
Somya R. Goyal
doaj +2 more sources