Dependency-Directed Localization of Software Bugs by Kuper, Ron I.

“…Software bugs are violated specifications. Debugging is the process that culminates in repairing a program so that it satisfies its specification. …”
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APPLICATION OF EXPLAINABLE ARTIFICIAL INTELLIGENCE IN SOFTWARE BUG CLASSIFICATION by Łukasz Chmielowski, Michał Kucharzak, Robert Burduk

Subjects: “…software bug assignment…”
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A highly configurable software bug tracking system by Tait, Calista (Calista Elizabeth), 1975-

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Hyperparameter Optimization for Software Bug Prediction Using Ensemble Learning by Dimah Al-Fraihat, Yousef Sharrab, Abdel-Rahman Al-Ghuwairi, Hamzeh Alshishani, Abdulmohsen Algarni

Subjects: “…Software bug prediction…”
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Automatic Assignment Method for Software Bug Based on Multivariate Features of Developers by DONG Xia-lei, XIANG Zheng-long, WU Hong-run, WANG Ding-wen, LI Yuan-xiang

“…Software bug repair is a problem that cannot be ignored in the process of software life.How to efficiently assign software bugs automatically is a very important research direction.Now,the existing research methods mainly focus on the bugreport’s text content or the low-level information of the developers’ tossing network,while ignoring the high-level topology information in the tossing network.Therefore,this paper proposes a software bug automatic assignment model MFD-GCN based on the developers’ multivariate features.Model fully considers the high-level topological features in the developers’ tossing network,and uses the powerful network feature extraction capabilities of graph convolution network to fully mine the multivariate features that represent developers’ deep cooperation relationship and fixing preferences,and train the classifier together with the bug text features.The proposed method is evaluated on two large open-source software projects,i.e.,Eclipse and Mozilla.Expe-rimental results show that compared with the mainstream bug-assignment methods proposed in recent years,the MFD-GCN mo-del has achieved state-of-art results in recommending the top <i>K</i> developers.The accuracy rate of top-1 recommendation on the Eclipse and Mozilla project reaches 69.8% and 59.7%,respectively.…”
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Using textual bug reports to predict the fault category of software bugs by Thomas Hirsch, Birgit Hofer

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Classification and intuitionistic fuzzy set based software bug triaging techniques by Rama Ranjan Panda, Naresh Kumar Nagwani

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Machine learning techniques for software bug prediction: a systematic review by Saharudin, Syahana Nur’Ain, Koh, Tieng Wei, Kew, Si Na

“…The goal of software bug prediction is to identify the software modules that will have the likelihood to get bugs by using some fundamental project resources before the real testing starts. …”
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Development of partial least squares regression with discriminant analysis for software bug prediction by Róbert Rajkó, István Siket, Péter Hegedűs, Rudolf Ferenc

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Automated Classification of Unstructured Bilingual Software Bug Reports: An Industrial Case Study Research by Ömer Köksal, Bedir Tekinerdogan

Subjects: “…software bug classification…”
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ProRE: An ACO- based programmer recommendation model to precisely manage software bugs by Ashima Kukkar, Umesh Kumar Lilhore, Jaroslav Frnda, Jasminder Kaur Sandhu, Rashmi Prava Das, Nitin Goyal, Arun Kumar, Kamalakanta Muduli, Filip Rezac

“…This research article presents an Ant colony optimization-based programmer recommendation model (ProRE) to manage software bugs precisely. The proposed ProRE model performs four operations: data pre-processing, i.e., data Pre-processing, extraction, feature selection, and programmer recommendation process. …”
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An artificial intelligence framework on software bug triaging, technological evolution, and future challenges: A review by Naresh Kumar Nagwani, Jasjit S. Suri

Subjects: “…Software bug triaging…”
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Research and Progress on Bug Report-oriented Bug Localization Techniques by NI Zhen, LI Bin, SUN Xiao-bing, LI Bi-xin, ZHU Cheng

Subjects: “…software bug localization|software bug report|localization model|information retrieval|deep learning…”
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Novel method of building train and test sets for evaluation of machine learning models related to software bugs assignment by Lukasz Chmielowski, Michal Kucharzak, Robert Burduk

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Notes on fiber length measurements: A case study in the underbelly of open source neuroscience by Claude J Bajada, Robert E Smith, Svenja Caspers

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Highlighting bugs in software development codes using SDPET for enhancing security by N.A. Bhaskaran, M. Durairaj

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DP-CCL: A Supervised Contrastive Learning Approach Using CodeBERT Model in Software Defect Prediction by Sadia Sahar, Muhammad Younas, Muhammad Murad Khan, Muhammad Umer Sarwar

Subjects: “…Software bug prediction…”
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A Comparative Study of Contemporary Learning Paradigms in Bug Report Priority Detection by Eyup Halit Yilmaz, Ismail Hakki Toroslu, Omer Koksal

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A hybrid deep learning approach with genetic and coral reefs metaheuristics for enhanced defect detection in software by Kajal Tameswar, Geerish Suddul, Kumar Dookhitram

Subjects: “…Software bug prediction…”
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Software Defect Prediction Based on Machine Learning and Deep Learning Techniques: An Empirical Approach by Waleed Albattah, Musaad Alzahrani

“…Software bug prediction is a software maintenance technique used to predict the occurrences of bugs in the early stages of the software development process. …”
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