Sinossi
Companies often develop a set of software variants that share some features and differ in other ones to meet specific requirements. To exploit existing software variants and build a Software Product Line (SPL), a Feature Model (FM) of this SPL must be built as a first step. To do so, it is necessary to mine optional and mandatory features in addition to associating the FM with its documentation. This book presents an approach for feature location and documentation in a collection of software product variants. Three techniques are used to do so: Formal Concept Analysis, Latent Semantic Indexing and analysis of structural code dependencies. These techniques exploit commonalities and variable parts across software variants, at source code level. The second contribution consists in documenting a mined feature by providing a name and description. It exploits both the source code of the feature and use-cases, which contains the logical organization of external functionalities together with textual descriptions of these functionalities. Relational Concept Analysis completes the same three techniques used previously as it can group entities according to their relations.
Le informazioni nella sezione "Riassunto" possono far riferimento a edizioni diverse di questo titolo.
L'autore
Ra’Fat Al-Msie’Deen received Bachelor of computer science in September 17, 2007 from Al - Hussein Bin Talal University in Jordan, and he received a Master of Science (Information Technology) in March 28, 2009 from University Utara Malaysia. His research interest includes Software Product Line Engineering and Formal Concept Analysis.
Le informazioni nella sezione "Su questo libro" possono far riferimento a edizioni diverse di questo titolo.
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Feature Location in a Collection of Software Product Variants
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LAP LAMBERT Academic Publishing Mai 2014, 2014
ISBN 10: 3659547441
ISBN 13: 9783659547447
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Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Companies often develop a set of software variants that share some features and differ in other ones to meet specific requirements. To exploit existing software variants and build a Software Product Line (SPL), a Feature Model (FM) of this SPL must be built as a first step. To do so, it is necessary to mine optional and mandatory features in addition to associating the FM with its documentation. This book presents an approach for feature location and documentation in a collection of software product variants. Three techniques are used to do so: Formal Concept Analysis, Latent Semantic Indexing and analysis of structural code dependencies. These techniques exploit commonalities and variable parts across software variants, at source code level. The second contribution consists in documenting a mined feature by providing a name and description. It exploits both the source code of the feature and use-cases, which contains the logical organization of external functionalities together with textual descriptions of these functionalities. Relational Concept Analysis completes the same three techniques used previously as it can group entities according to their relations. 148 pp. Englisch. Codice articolo 9783659547447
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Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Companies often develop a set of software variants that share some features and differ in other ones to meet specific requirements. To exploit existing software variants and build a Software Product Line (SPL), a Feature Model (FM) of this SPL must be built as a first step. To do so, it is necessary to mine optional and mandatory features in addition to associating the FM with its documentation. This book presents an approach for feature location and documentation in a collection of software product variants. Three techniques are used to do so: Formal Concept Analysis, Latent Semantic Indexing and analysis of structural code dependencies. These techniques exploit commonalities and variable parts across software variants, at source code level. The second contribution consists in documenting a mined feature by providing a name and description. It exploits both the source code of the feature and use-cases, which contains the logical organization of external functionalities together with textual descriptions of these functionalities. Relational Concept Analysis completes the same three techniques used previously as it can group entities according to their relations.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 148 pp. Englisch. Codice articolo 9783659547447
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Taschenbuch. Condizione: Neu. Feature Location in a Collection of Software Product Variants | Ra'Fat AL-Msie'Deen | Taschenbuch | 148 S. | Englisch | 2014 | LAP LAMBERT Academic Publishing | EAN 9783659547447 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu. Codice articolo 105250114
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Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Companies often develop a set of software variants that share some features and differ in other ones to meet specific requirements. To exploit existing software variants and build a Software Product Line (SPL), a Feature Model (FM) of this SPL must be built as a first step. To do so, it is necessary to mine optional and mandatory features in addition to associating the FM with its documentation. This book presents an approach for feature location and documentation in a collection of software product variants. Three techniques are used to do so: Formal Concept Analysis, Latent Semantic Indexing and analysis of structural code dependencies. These techniques exploit commonalities and variable parts across software variants, at source code level. The second contribution consists in documenting a mined feature by providing a name and description. It exploits both the source code of the feature and use-cases, which contains the logical organization of external functionalities together with textual descriptions of these functionalities. Relational Concept Analysis completes the same three techniques used previously as it can group entities according to their relations. Codice articolo 9783659547447
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