Verlag: LAP LAMBERT Academic Publishing Jan 2017, 2017
ISBN 10: 3330029056 ISBN 13: 9783330029057
Sprache: Englisch
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In den WarenkorbTaschenbuch. Zustand: Neu. Neuware -Automatically comprehending novice programs with the aim of giving useful feedback has been an Artificial Intelligence problem for over four decades. Solving this problem basically entails manipulating the underlying program plans; i.e. extracting and comparing the novice's plan to the expert's plan and inferring where the novice's bug is from. The bugs of interest in this domain are often semantic bugs as all syntactic bugs are handled by automatic debuggers ¿ built in most compilers. Hence, a program that debugs like the human expert should understand the problem and know the expected solution(s) in order to detect semantic bugs. This book proposes a new approach to comprehending novice programs using: regular expressions for the recognition of plans in the program text, finite automata for defining the space of program plan variations, and automata-based algorithms for the detection of semantic bugs. The new approach is tested with a repository of novice programs with known semantic bugs and specific bugs were detected. As a proof of concept, the theories presented in this book are further implemented in software prototypes.Books on Demand GmbH, Überseering 33, 22297 Hamburg 188 pp. Englisch.
Verlag: LAP LAMBERT Academic Publishing, 2017
ISBN 10: 3330029056 ISBN 13: 9783330029057
Sprache: Englisch
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In den WarenkorbPaperback. Zustand: Brand New. 188 pages. 8.66x5.91x0.43 inches. In Stock.
Verlag: LAP LAMBERT Academic Publishing, 2017
ISBN 10: 3330029056 ISBN 13: 9783330029057
Sprache: Englisch
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In den WarenkorbZustand: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Ade-Ibijola AbejideDr. Abejide Ade-Ibijola holds a Ph.D. in Computer Science (specializing in Program Comprehension) from the University of the Witwatersrand, Johannesburg, South Africa in 2016. He is currently a Senior Lecturer in t.
Verlag: LAP LAMBERT Academic Publishing Jan 2017, 2017
ISBN 10: 3330029056 ISBN 13: 9783330029057
Sprache: Englisch
Anbieter: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Deutschland
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In den WarenkorbTaschenbuch. Zustand: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Automatically comprehending novice programs with the aim of giving useful feedback has been an Artificial Intelligence problem for over four decades. Solving this problem basically entails manipulating the underlying program plans; i.e. extracting and comparing the novice's plan to the expert's plan and inferring where the novice's bug is from. The bugs of interest in this domain are often semantic bugs as all syntactic bugs are handled by automatic debuggers - built in most compilers. Hence, a program that debugs like the human expert should understand the problem and know the expected solution(s) in order to detect semantic bugs. This book proposes a new approach to comprehending novice programs using: regular expressions for the recognition of plans in the program text, finite automata for defining the space of program plan variations, and automata-based algorithms for the detection of semantic bugs. The new approach is tested with a repository of novice programs with known semantic bugs and specific bugs were detected. As a proof of concept, the theories presented in this book are further implemented in software prototypes. 188 pp. Englisch.
Verlag: LAP LAMBERT Academic Publishing, 2017
ISBN 10: 3330029056 ISBN 13: 9783330029057
Sprache: Englisch
Anbieter: AHA-BUCH GmbH, Einbeck, Deutschland
EUR 64,90
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In den WarenkorbTaschenbuch. Zustand: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Automatically comprehending novice programs with the aim of giving useful feedback has been an Artificial Intelligence problem for over four decades. Solving this problem basically entails manipulating the underlying program plans; i.e. extracting and comparing the novice's plan to the expert's plan and inferring where the novice's bug is from. The bugs of interest in this domain are often semantic bugs as all syntactic bugs are handled by automatic debuggers - built in most compilers. Hence, a program that debugs like the human expert should understand the problem and know the expected solution(s) in order to detect semantic bugs. This book proposes a new approach to comprehending novice programs using: regular expressions for the recognition of plans in the program text, finite automata for defining the space of program plan variations, and automata-based algorithms for the detection of semantic bugs. The new approach is tested with a repository of novice programs with known semantic bugs and specific bugs were detected. As a proof of concept, the theories presented in this book are further implemented in software prototypes.