Finding Proneness of software is necessary to identify fault prone and change prone classes at earlier stages of development, so that those classes can be given special attention, also to improve the quality and reliability of the software. For corrective and adaptive maintenance we require to make changes during the software evolution. It is important to analyze the frequency of changes in individual classes and also to identify and show related changes in multiple classes. Early detection of fault prone and change prone classes can enables the developers and experts to spend their valuable time and resources on these areas of software. Prediction of change-prone and fault prone classes of a software is an active research topic in the area of software engineering; most researchers are working on this topic. Such prediction can be used to predict changes to different classes of a system from one release of software to the next release. Identifying the change-prone and fault prone classes in advance can helps to focus attention on these classes.
"synopsis" may belong to another edition of this title.
Dr. Akhil Khare, PhD(CSE) MTech(IT) BE(IT), is working at MVSR Engineering College, Hyderabad as a Professor in Department of Computer Science & Engineering. His areas of interest are Software Engineering and Multimedia System. He has more than seventy research publications in various international/national journals and conferences.
"About this title" may belong to another edition of this title.
Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germany
Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Finding Proneness of software is necessary to identify fault prone and change prone classes at earlier stages of development, so that those classes can be given special attention, also to improve the quality and reliability of the software. For corrective and adaptive maintenance we require to make changes during the software evolution. It is important to analyze the frequency of changes in individual classes and also to identify and show related changes in multiple classes. Early detection of fault prone and change prone classes can enables the developers and experts to spend their valuable time and resources on these areas of software. Prediction of change-prone and fault prone classes of a software is an active research topic in the area of software engineering; most researchers are working on this topic. Such prediction can be used to predict changes to different classes of a system from one release of software to the next release. Identifying the change-prone and fault prone classes in advance can helps to focus attention on these classes. 68 pp. Englisch. Seller Inventory # 9783659788185
Seller: moluna, Greven, Germany
Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Khare AkhilDr. Akhil Khare, PhD(CSE) MTech(IT) BE(IT), is working at MVSR Engineering College, Hyderabad as a Professor in Department of Computer Science & Engineering. His areas of interest are Software Engineering and Multimedia Sy. Seller Inventory # 158605481
Quantity: Over 20 available
Seller: buchversandmimpf2000, Emtmannsberg, BAYE, Germany
Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Finding Proneness of software is necessary to identify fault prone and change prone classes at earlier stages of development, so that those classes can be given special attention, also to improve the quality and reliability of the software. For corrective and adaptive maintenance we require to make changes during the software evolution. It is important to analyze the frequency of changes in individual classes and also to identify and show related changes in multiple classes. Early detection of fault prone and change prone classes can enables the developers and experts to spend their valuable time and resources on these areas of software. Prediction of change-prone and fault prone classes of a software is an active research topic in the area of software engineering; most researchers are working on this topic. Such prediction can be used to predict changes to different classes of a system from one release of software to the next release. Identifying the change-prone and fault prone classes in advance can helps to focus attention on these classes.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 68 pp. Englisch. Seller Inventory # 9783659788185
Seller: AHA-BUCH GmbH, Einbeck, Germany
Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Finding Proneness of software is necessary to identify fault prone and change prone classes at earlier stages of development, so that those classes can be given special attention, also to improve the quality and reliability of the software. For corrective and adaptive maintenance we require to make changes during the software evolution. It is important to analyze the frequency of changes in individual classes and also to identify and show related changes in multiple classes. Early detection of fault prone and change prone classes can enables the developers and experts to spend their valuable time and resources on these areas of software. Prediction of change-prone and fault prone classes of a software is an active research topic in the area of software engineering; most researchers are working on this topic. Such prediction can be used to predict changes to different classes of a system from one release of software to the next release. Identifying the change-prone and fault prone classes in advance can helps to focus attention on these classes. Seller Inventory # 9783659788185
Seller: preigu, Osnabrück, Germany
Taschenbuch. Condition: Neu. Algorithmic analysis of Proneness in Object-Oriented Software | Akhil Khare (u. a.) | Taschenbuch | 68 S. | Englisch | 2015 | LAP LAMBERT Academic Publishing | EAN 9783659788185 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu. Seller Inventory # 104156062