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Artificial Intelligence in Software Engineering: Current Developments and Future Prospects

Artificial Intelligence in Software Engineering: Current Developments and Future Prospects

Farid Meziane, Sunil Vadera
Copyright: © 2012 |Pages: 22
ISBN13: 9781609608187|ISBN10: 1609608186|EISBN13: 9781609608194
DOI: 10.4018/978-1-60960-818-7.ch504
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MLA

Meziane, Farid, and Sunil Vadera. "Artificial Intelligence in Software Engineering: Current Developments and Future Prospects." Machine Learning: Concepts, Methodologies, Tools and Applications, edited by Information Resources Management Association, IGI Global, 2012, pp. 1215-1236. https://doi.org/10.4018/978-1-60960-818-7.ch504

APA

Meziane, F. & Vadera, S. (2012). Artificial Intelligence in Software Engineering: Current Developments and Future Prospects. In I. Management Association (Ed.), Machine Learning: Concepts, Methodologies, Tools and Applications (pp. 1215-1236). IGI Global. https://doi.org/10.4018/978-1-60960-818-7.ch504

Chicago

Meziane, Farid, and Sunil Vadera. "Artificial Intelligence in Software Engineering: Current Developments and Future Prospects." In Machine Learning: Concepts, Methodologies, Tools and Applications, edited by Information Resources Management Association, 1215-1236. Hershey, PA: IGI Global, 2012. https://doi.org/10.4018/978-1-60960-818-7.ch504

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Abstract

Artificial intelligences techniques such as knowledge based systems, neural networks, fuzzy logic and data mining have been advocated by many researchers and developers as the way to improve many of the software development activities. As with many other disciplines, software development quality improves with the experience, knowledge of the developers, past projects and expertise. Software also evolves as it operates in changing and volatile environments. Hence, there is significant potential for using AI for improving all phases of the software development life cycle. This chapter provides a survey on the use of AI for software engineering that covers the main software development phases and AI methods such as natural language processing techniques, neural networks, genetic algorithms, fuzzy logic, ant colony optimization, and planning methods.

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