Applications of Text Mining in Software Repository Analysis
A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Computing and Artificial Intelligence".
Deadline for manuscript submissions: closed (30 June 2024) | Viewed by 4954
Special Issue Editors
Interests: software engineering; software security; software reliability; software quality; mathematical modelling; of computer systems; artificial intelligence for software engineering; expert systems
Interests: energy optimization; energy packet networks; neural computation; random neural networks; G-networks; networked systems; physical and biological networks; probability models; natural computation
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Special Issue Information
Dear Colleagues,
Modern software repositories comprise a large volume of textual information, ranging from the natural language description of their functional and non-functional requirements to the textual representation of their actual source code. This information can be leveraged for extracting useful insights about the associated software repositories and their overall development process, as well as for building intelligent models for aiding their design and development and improving their quality. To this end, text mining techniques have been utilized extensively in the literature in order to extract interesting patterns and gain relevant knowledge from software repositories (e.g., bug patterns, vulnerability patterns, developer activity trends, etc.). In addition to this, text mining-related information has been also used for enhancing software engineering tasks, including: requirements elicitation, verification, and validation; bug/vulnerability prediction, detection, and localization; code clone detection; and automatic code generation, among others. Although a lot of work has been conducted during the past years on the aforementioned topics, many challenges remain unresolved and require further research.
The aim of this Special Issue is to bring together academics and practitioners to exchange and discuss the latest innovations and applications of text mining techniques in analyzing software repositories. Particularly, we are seeking for review papers, empirical studies, and technical papers describing novel solutions and methodologies on the topic of text mining techniques for software repository analysis. Papers that utilize text mining for addressing, but not limited to, the following topics will be considered for publication:
- Requirements elicitation;
- Requirements verification and validation;
- Requirements classification;
- Natural language processing of source code;
- Bug and vulnerability pattern identification;
- Bug and vulnerability prediction;
- Bug and vulnerability detection;
- Bug and vulnerability localization;
- Bug and vulnerability severity evaluation;
- Automatic test case generation;
- Software repository tagging;
- Software repository knowledge discovery;
- Source code summarization;
- Source code recommendation;
- Automatic source code generation;
- Code clone detection;
- Automatic feature identification;
- Automatic technology identification.
Dr. Miltiadis G. Siavvas
Dr. Erol Gelenbe
Guest Editors
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Keywords
- software engineering
- mining software repositories
- text mining
- natural language processing
- artificial intelligence
- deep learning
- requirements verification, and validation
- bug and vulnerability prediction
- bug and vulnerability detection
- code clone detection
- automatic code generation
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