Results 51 to 60 of about 111,109 (312)
An Empirical Study on the Effectiveness of Feature Selection for Cross-Project Defect Prediction
IEEE Access, 2019 Software defect prediction has attracted much attention of researchers in software engineering. At present, feature selection approaches have been introduced into software defect prediction, which can improve the performance of traditional defect ...
Qiao Yu +4 more
doaj +1 more source
Revisiting Unsupervised Learning for Defect Prediction
, 2017 Collecting quality data from software projects can be time-consuming and expensive. Hence, some researchers explore "unsupervised" approaches to quality prediction that does not require labelled data.
Fu, Wei, Menzies, Tim
core +1 more source
Predicting Defects in Software Using Grammar-Guided Genetic Programming [PDF]
, 2008 The knowledge of the software quality can allow an organization to allocate the needed resources for the code maintenance. Maintaining the software is considered as a high cost factor for most organizations. Consequently, there is need to assess software
Dounias, Georgios, Tsakonas, Athanasios
core +2 more sources
FEBS Open Bio, EarlyView.Chemotherapy side effects significantly impact cancer survivors' quality of life. Using protein levels in blood samples from breast cancer patients before and after 12 weeks of taxane treatment, we detected treatment‐dependent changes in calcium signaling and aging pathways associated with cancer recurrence.
Saira Munshani +6 more
wiley +1 more source
Applied Sciences, 2022 Cross-project defect prediction (CPDP) is a practical approach for finding software defects in projects which have incomplete or fewer data. Improvements to the defect prediction accuracy of CPDP—such as the PROMISE repository, the correct classification
Sundas Noreen +3 more
doaj +1 more source
Bayesian Hierarchical Modelling for Tailoring Metric Thresholds
, 2018 Software is highly contextual. While there are cross-cutting `global' lessons, individual software projects exhibit many `local' properties. This data heterogeneity makes drawing local conclusions from global data dangerous.
Bettenburg N. +4 more
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FEBS Open Bio, EarlyView.UiO‐66(Zr) metal–organic frameworks are chemically stable, biocompatible, and highly tunable nanomaterials. Their modular structure enables controlled drug delivery, multimodal bioimaging, and light‐activated photodynamic therapy, supporting integrated diagnostic and therapeutic (theranostic) applications in cancer and biomedical research.
Veronika Huntošová +2 more
wiley +1 more source
HDA: Cross-Project Defect Prediction via Heterogeneous Domain Adaptation With Dictionary Learning
IEEE Access, 2018 Cross-Project Defect Prediction (CPDP) is an active topic for predicting defects on projects (target projects) with scarce-labeled data by reusing the classification models from other projects (source projects).
Zhou Xu +5 more
doaj +1 more source
Cross-Project Defect Prediction with Metrics Selection and Balancing Approach
Applied Computer Systems, 2022 In software development, defects influence the quality and cost in an undesirable way. Software defect prediction (SDP) is one of the techniques which improves the software quality and testing efficiency by early identification of defects(bug/fault/error)
Nevendra Meetesh, Singh Pradeep
doaj +1 more source
Towards Automated Performance Bug Identification in Python
, 2016 Context: Software performance is a critical non-functional requirement, appearing in many fields such as mission critical applications, financial, and real time systems.
Mazzawi, Elie +2 more
core +1 more source