Research at the intersection of artificial intelligence and software engineering is important to both AI researchers and software engineers. For AI, programming is a challenging domain that stimulates fundamental research in knowledge representation and automated reasoning. In software engineering, AI techniques can be applied to programming tools with potential for dramatic improvements in programmer productivity. This volume, edited by two research scientists at the Artificial Intelligence Laboratory of MIT, collects thirty-four important papers covering a wide spectrum of work in this area. Major topics include automatic programming, theorem-proving approaches, transformational approaches, specification techniques, intelligent assistants, knowledge representation, and artificial intelligence programming. The editors have provided an introductory survey of the field and issues, introductions to each group of papers, and an extensive bibliography.
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Research at the intersection of artificial intelligence and software engineering is important to both AI researchers and software engineers. For AI, programming is a challenging domain that stimulates fundamental research in knowledge representation and automated reasoning. In software engineering, AI techniques can be applied to programming tools with potential for dramatic improvements in programmer productivity. This volume, edited by two research scientists at the Artificial Intelligence Laboratory of MIT, collects thirty-four important papers covering a wide spectrum of work in this area. Major topics include automatic programming, theorem-proving approaches, transformational approaches, specification techniques, intelligent assistants, knowledge representation, and artificial intelligence programming. The editors have provided an introductory survey of the field and issues, introductions to each group of papers, and an extensive bibliography.
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