Enriching Reverse Engineering with Annotations

Brühlmann, Andrea; Gîrba, Tudor; Greevy, Orla; Nierstrasz, Oscar (2008). Enriching Reverse Engineering with Annotations. In: Czarnecki, Krzysztof; Ober, Ileana; Bruel, Jean-Michel; Uhl, Axel; Völter, Markus (eds.) Model Driven Engineering Languages and Systems. 11th International Conference, MoDELS 2008, Toulouse, France, September 28 - October 3, 2008. Proceedings. Lecture Notes in Computer Science: Vol. 5301 (pp. 660-674). Heidelberg: Springer Verlag 10.1007/978-3-540-87875-9_46

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Much of the knowledge about software systems is implicit, and therefore difficult to recover by purely automated techniques. Architectural layers and the externally visible features of software systems are two examples of information that can be difficult to detect from source code alone, and that would benefit from additional human knowledge. Typical approaches to reasoning about data involve encoding an explicit meta-model and expressing analyses at that level. Due to its informal nature, however, human knowledge can be difficult to characterize up-front and integrate into such a meta-model. We propose a generic, annotation-based approach to capture such knowledge during the reverse engineering process. Annotation types can be iteratively defined, refined and transformed, without requiring a fixed meta-model to be defined in advance. We show how our approach supports reverse engineering by implementing it in a tool called Metanool and by applying it to (i) analyzing architectural layering, (ii) tracking reengineering tasks, (iii) detecting design flaws, and (iv) analyzing features.

Item Type: Book Section (Book Chapter)
Division/Institute: 08 Faculty of Science > Institute of Computer Science (INF)
UniBE Contributor: Girba, Tudor Adrian; Greevy, Orla and Nierstrasz, Oscar Marius
Series: Lecture Notes in Computer Science
Publisher: Springer Verlag
Language: English
Submitter: Factscience Import
Date Deposited: 04 Oct 2013 15:22
Last Modified: 04 May 2014 23:27
Publisher DOI: 10.1007/978-3-540-87875-9_46
Web of Science ID: 000261373900046
URI: http://boris.unibe.ch/id/eprint/37134 (FactScience: 206792)

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