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Artificial intelligence methods for software engineering[electronic resource] /

紀錄類型:	書目-電子資源 : Monograph/item
杜威分類號:	005.1
書名/作者:	Artificial intelligence methods for software engineering/ editors, Meir Kalech, Rui Abreu, Mark Last.
其他作者:	Kalech, Meir.
出版者:	Singapore : : World Scientific,, c2021.
面頁冊數:	1 online resource (456 p.)
標題:	Software engineering.
標題:	Artificial intelligence - Engineering applications.
ISBN:	9789811239922
ISBN:	9811239924
ISBN:	9789811239939
書目註:	Includes bibliographical references and index.
內容註:	Preface -- AI for software design. Interweaving ai and behavioral programming towards better programming environments -- AI techniques for software requirements prioritization -- Agent-based software programming. Social commitments for engineering interaction in distributed systems -- Intelligent agents are more complex: initial empirical findings -- AI for software development. Sequence-to-sequence learning for automated software artifact generation -- Machine learning to support code reviews in continuous integration -- Software fusion: deep design learning with deterministic Laplacian verification -- Using artificial intelligence for auto-generating software for cyber-physical applications -- AI for software testing. On the application of machine learning in software testing -- Creating test oracles using machine learning techniques -- Intelligent risk based analysis methodology -- A qualitative reasoning model for software testing, based on combinatorial geometry -- AI for software debugging. AI-based spreadsheet debugging -- Artificial intelligence methods for software debugging -- Index.
摘要、提要註:	"Artificial Intelligence (AI) is a growing field in computer science that has been proven effective in applying and developing AI techniques to address various SE challenges." "This unique compendium covers applications of state-of-the-art AI techniques to the key areas of SE (design, development, debugging, testing, etc)." "All the materials presented are up-to-date. This reference text will benefit researchers, academics, professionals, and postgraduate students in AI, machine learning and software engineering."--
電子資源:	https://www.worldscientific.com/worldscibooks/10.1142/12360#t=toc

Artificial intelligence methods for software engineering[electronic resource] /
Artificial intelligence methods for software engineering[electronic resource] /editors, Meir Kalech, Rui Abreu, Mark Last. - Singapore :World Scientific,c2021. - 1 online resource (456 p.)

Includes bibliographical references and index.

Preface -- AI for software design. Interweaving ai and behavioral programming towards better programming environments -- AI techniques for software requirements prioritization -- Agent-based software programming. Social commitments for engineering interaction in distributed systems -- Intelligent agents are more complex: initial empirical findings -- AI for software development. Sequence-to-sequence learning for automated software artifact generation -- Machine learning to support code reviews in continuous integration -- Software fusion: deep design learning with deterministic Laplacian verification -- Using artificial intelligence for auto-generating software for cyber-physical applications -- AI for software testing. On the application of machine learning in software testing -- Creating test oracles using machine learning techniques -- Intelligent risk based analysis methodology -- A qualitative reasoning model for software testing, based on combinatorial geometry -- AI for software debugging. AI-based spreadsheet debugging -- Artificial intelligence methods for software debugging -- Index.

"Artificial Intelligence (AI) is a growing field in computer science that has been proven effective in applying and developing AI techniques to address various SE challenges." "This unique compendium covers applications of state-of-the-art AI techniques to the key areas of SE (design, development, debugging, testing, etc)." "All the materials presented are up-to-date. This reference text will benefit researchers, academics, professionals, and postgraduate students in AI, machine learning and software engineering."--

Mode of access: World Wide Web.

ISBN: 9789811239922Subjects--Topical Terms:

217367
Software engineering.

LC Class. No.: QA76.758

Dewey Class. No.: 005.1

Artificial intelligence methods for software engineering[electronic resource] /
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245 0 0 $a Artificial intelligence methods for software engineering $h [electronic resource] / $c editors, Meir Kalech, Rui Abreu, Mark Last.
260 $a Singapore : $b World Scientific, $c c2021.
300 $a 1 online resource (456 p.)
504 $a Includes bibliographical references and index.
505 0 $a Preface -- AI for software design. Interweaving ai and behavioral programming towards better programming environments -- AI techniques for software requirements prioritization -- Agent-based software programming. Social commitments for engineering interaction in distributed systems -- Intelligent agents are more complex: initial empirical findings -- AI for software development. Sequence-to-sequence learning for automated software artifact generation -- Machine learning to support code reviews in continuous integration -- Software fusion: deep design learning with deterministic Laplacian verification -- Using artificial intelligence for auto-generating software for cyber-physical applications -- AI for software testing. On the application of machine learning in software testing -- Creating test oracles using machine learning techniques -- Intelligent risk based analysis methodology -- A qualitative reasoning model for software testing, based on combinatorial geometry -- AI for software debugging. AI-based spreadsheet debugging -- Artificial intelligence methods for software debugging -- Index.
520 $a "Artificial Intelligence (AI) is a growing field in computer science that has been proven effective in applying and developing AI techniques to address various SE challenges." "This unique compendium covers applications of state-of-the-art AI techniques to the key areas of SE (design, development, debugging, testing, etc)." "All the materials presented are up-to-date. This reference text will benefit researchers, academics, professionals, and postgraduate students in AI, machine learning and software engineering."-- $c Publisher's website.
538 $a Mode of access: World Wide Web.
538 $a System requirements: Adobe Acrobat reader.
588 $a Description based on print version record.
650 0 $a Software engineering. $3 217367
650 0 $a Artificial intelligence $x Engineering applications. $3 767512
700 1 $a Kalech, Meir. $3 767510
700 1 $a Abreu, Rui. $3 767511
700 1 $a Last, Mark. $3 709870
856 4 0 $u https://www.worldscientific.com/worldscibooks/10.1142/12360#t=toc