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Systematic Mapping: Artificial Intelligence Techniques in Software Engineering
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DOI：10.1109/ACCESS.2022.3174115.png)
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Abstract
En 中文
Artificial Intelligence (AI) has become a core feature of today's real-world applications, making it a trending topic within the software engineering (SE) community. The rise in the availability of AI techniques encompasses the capability to make rapid, automated, impactful decisions and predictions, leading to the adoption of AI techniques in SE. With industry revolution 4.0, the role of software engineering has become critical for developing productive, efficient, and quality software. Thus, there is a major need for AI techniques to be applied to enhance and improve the critical activities within the software engineering phases. Software is developed through intelligent software engineering phases. This paper concerns a systematic mapping study that aimed to characterize the publication landscape of AI techniques in software engineering. Gaps are identified and discussed by mapping these AI techniques against the SE phases to which they contributed. Many systematic mapping review papers have been produced only for a specific AI technique or a specific SE phase or activity. Hence, to our best of knowledge within the last decade, there is no systematic mapping review that has fully explored the overall trends in AI techniques and their application to all SE phases.
Keywords:
Artificial intelligence
Software
Systematics
Software engineering
Data mining
Predictive models
Training
Artificial intelligence
machine learning
deep learning
data mining
software engineering
requirements engineering
analysis and design
software development
software testing
software maintenance
software deployment
Journal
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3.6
Papers:
9.8W
Citations:
29.4W
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