Current approaches to automatic software fault localization can be classified as either (1) statistics-based approaches, or (2) reasoning approaches. This distinction is based on the required amount of knowledge about the program's internal component structure and behavior. Statistics-based fault localization techniques such as Spectrum-based Fault Localization (SFL) use abstraction of program traces (also known as program spectra) to find a statistical relationship between source code locations and observed failures. Although SFL's modeling costs and computational complexity are minimal, its diagnostic accuracy is inherently limited since no reasoning is used. In contrast to SFL, model-based reasoning approaches use prior knowledge of the program, such as component interconnection and statement semantics, to build a model of the correct behavior of the system. On the one hand, model-based reasoning approaches deliver higher diagnostic accuracy, but on the other hand, they suffer from high computation complexity.
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Rui Abreu graduated in Systems and Computer Eng. from Univ. of Minho, and followed courses of the Software Tech Masters at Univ. of Utrecht. He was an intern at Philips Research Labs Oct'04-Jun'05. Received his Ph.D. from Delft Univ. of Tech, in Nov'09, and he is now an assistant professor at Univ. of Porto. He was a Visiting Faculty at CMU.
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Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Current approaches to automatic software fault localization can be classified as either (1) statistics-based approaches, or (2) reasoning approaches. This distinction is based on the required amount of knowledge about the program's internal component structure and behavior. Statistics-based fault localization techniques such as Spectrum-based Fault Localization (SFL) use abstraction of program traces (also known as program spectra) to find a statistical relationship between source code locations and observed failures. Although SFL's modeling costs and computational complexity are minimal, its diagnostic accuracy is inherently limited since no reasoning is used. In contrast to SFL, model-based reasoning approaches use prior knowledge of the program, such as component interconnection and statement semantics, to build a model of the correct behavior of the system. On the one hand, model-based reasoning approaches deliver higher diagnostic accuracy, but on the other hand, they suffer from high computation complexity. 208 pp. Englisch. N° de réf. du vendeur 9783844305289
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Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Abreu RuiRui Abreu graduated in Systems and Computer Eng. from Univ. of Minho, and followed courses of the Software Tech Masters at Univ. of Utrecht. He was an intern at Philips Research Labs Oct 04-Jun 05. Received his Ph.D. fro. N° de réf. du vendeur 5471022
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Taschenbuch. Etat : Neu. Lightweight Techniques for Automatic Software Fault Localization | Theory and Practice | Rui Abreu | Taschenbuch | 208 S. | Englisch | 2011 | LAP LAMBERT Academic Publishing | EAN 9783844305289 | Verantwortliche Person für die EU: BoD - Books on Demand, In de Tarpen 42, 22848 Norderstedt, info[at]bod[dot]de | Anbieter: preigu. N° de réf. du vendeur 107071634
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Taschenbuch. Etat : Neu. This item is printed on demand - Print on Demand Titel. Neuware -Current approaches to automatic software fault localization can be classified as either (1) statistics-based approaches, or (2) reasoning approaches. This distinction is based on the required amount of knowledge about the program''s internal component structure and behavior. Statistics-based fault localization techniques such as Spectrum-based Fault Localization (SFL) use abstraction of program traces (also known as program spectra) to find a statistical relationship between source code locations and observed failures. Although SFL''s modeling costs and computational complexity are minimal, its diagnostic accuracy is inherently limited since no reasoning is used. In contrast to SFL, model-based reasoning approaches use prior knowledge of the program, such as component interconnection and statement semantics, to build a model of the correct behavior of the system. On the one hand, model-based reasoning approaches deliver higher diagnostic accuracy, but on the other hand, they suffer from high computation complexity.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 208 pp. Englisch. N° de réf. du vendeur 9783844305289
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Taschenbuch. Etat : Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Current approaches to automatic software fault localization can be classified as either (1) statistics-based approaches, or (2) reasoning approaches. This distinction is based on the required amount of knowledge about the program's internal component structure and behavior. Statistics-based fault localization techniques such as Spectrum-based Fault Localization (SFL) use abstraction of program traces (also known as program spectra) to find a statistical relationship between source code locations and observed failures. Although SFL's modeling costs and computational complexity are minimal, its diagnostic accuracy is inherently limited since no reasoning is used. In contrast to SFL, model-based reasoning approaches use prior knowledge of the program, such as component interconnection and statement semantics, to build a model of the correct behavior of the system. On the one hand, model-based reasoning approaches deliver higher diagnostic accuracy, but on the other hand, they suffer from high computation complexity. N° de réf. du vendeur 9783844305289
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