Can we predict useful comments in source codes? - Analysis of findings from Information Retrieval in Software Engineering Track @ FIRE 2022

Majumdar, Srijoni; Bandyopadhyay, Ayan; Das, Partha Pratim; Clough, Paul; Chattopadhyay, Samiran; Majumder, Prasenjit

doi:10.1145/3574318.3574329

Cited by 4 publications

(3 citation statements)

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“…The academic community started to research and inject new AI-based approaches to provide solutions to traditional software engineering problems [5] and critical activities [6]. Examples include software testing [7], maintenance [8], requirements extraction [9], ambiguity resolution [10], software vulnerability detection [11], and software engineering education [12]. Despite the increasing prevalence of AI use in software engineering, a comprehensive and holistic understanding of the current status, possible target applications, practical software engineering usage scenarios, and unavoidable limitations, ethical concerns, and challenges remain unclear [6].…”

Section: Introductionmentioning

confidence: 99%

The Use of AI in Software Engineering: Synthetic Knowledge Synthesis of Recent Research Literature

Kokol

2024

Preprint

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Artificial intelligence (AI) has witnessed an exponential increase in its use in various applications. Recently, the academic community started to research and inject new AI-based approaches to provide solutions to traditional software engineering problems. However, a comprehensive and holistic understanding of the current status is missing. To close the above gap, synthetic knowledge synthesis was used to induce a research landscape of the contemporary research literature on the use of AI in software engineering. The synthesis resulted in 15 research categories and five themes, namely natural language processing in software engineering, use of artificial intelligence in the management of software development life cycle, use of machine learning in fault/defect prediction and effort estimation, employment of deep learning in intelligent software engineering and code management, and mining software repositories to improve software quality. The most productive country was China (n=2042), followed by the United States (n=1193), India (n=934), Germany (n=445), and Canada (n=381). A high percentage (n=47.4%) of papers were funded, showing a strong interest in this research topic. The convergence of AI and software engineering can significantly reduce needed resources, improve quality, increase user experience, and improve the well-being of software developers.

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Section: Introductionmentioning

confidence: 99%

The Use of AI in Software Engineering: Synthetic Knowledge Synthesis of Recent Research Literature

Kokol

2024

Preprint

View full text Add to dashboard Cite

show abstract

“…The academic community started to research and inject new AI-based approaches to provide solutions to traditional software-engineering (SE) problems [5] and critical activities [6]. Examples include software testing [7], maintenance [8], requirements extraction [9], ambiguity resolution [10], software vulnerability detection [11], and software-engineering education [11]. Due to the increasing prevalence of AI use in software engineering, some reviews on the use of AI in software engineering have already been performed.…”

Section: Introductionmentioning

confidence: 99%

“…Due to the increasing prevalence of AI use in software engineering, some reviews on the use of AI in software engineering have already been performed. Cao et al [12] and Mohammadkhani et al [13] synthetized the problem of explainability due to using black box AI methodologies in SE; Bano et al and Ozkaya [14] explored the opportunities and challenges of large language models' employment in SE [15]; and Majumdar overviewed the research on generative AI use in analyzing software metadata [8]. The above reviews did not provide a complete and general landscape of AI use in SE.…”

Section: Introductionmentioning

confidence: 99%

The Use of AI in Software Engineering: A Synthetic Knowledge Synthesis of the Recent Research Literature

Kokol

2024

Information

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Artificial intelligence (AI) has witnessed an exponential increase in use in various applications. Recently, the academic community started to research and inject new AI-based approaches to provide solutions to traditional software-engineering problems. However, a comprehensive and holistic understanding of the current status needs to be included. To close the above gap, synthetic knowledge synthesis was used to induce the research landscape of the contemporary research literature on the use of AI in software engineering. The synthesis resulted in 15 research categories and 5 themes—namely, natural language processing in software engineering, use of artificial intelligence in the management of the software development life cycle, use of machine learning in fault/defect prediction and effort estimation, employment of deep learning in intelligent software engineering and code management, and mining software repositories to improve software quality. The most productive country was China (n = 2042), followed by the United States (n = 1193), India (n = 934), Germany (n = 445), and Canada (n = 381). A high percentage (n = 47.4%) of papers were funded, showing the strong interest in this research topic. The convergence of AI and software engineering can significantly reduce the required resources, improve the quality, enhance the user experience, and improve the well-being of software developers.

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Towards development of an effective AI-based system for relevant comment generation

Kumari,

Das

2023

Proceedings of the 15th Annual Meeting of the Forum for Information Retrieval Evaluation

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Can we predict useful comments in source codes? - Analysis of findings from Information Retrieval in Software Engineering Track @ FIRE 2022

Cited by 4 publications

References 1 publication

The Use of AI in Software Engineering: Synthetic Knowledge Synthesis of Recent Research Literature

The Use of AI in Software Engineering: Synthetic Knowledge Synthesis of Recent Research Literature

The Use of AI in Software Engineering: A Synthetic Knowledge Synthesis of the Recent Research Literature

Towards development of an effective AI-based system for relevant comment generation

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