Modeling Features at Runtime

Denker, Marcus; Ressia, Jorge; Greevy, Orla; Nierstrasz, Oscar (2010). Modeling Features at Runtime. In: Petriu, Dorina C.; Rouquette, Nicolas; Haugen, Øystein (eds.) Model Driven Engineering Languages and Systems. 13th International Conference, MODELS 2010, Oslo, Norway, October 3-8, 2010, Proceedings, Part II. Lecture Notes in Computer Science: Vol. 6395 (pp. 138-152). Heidelberg: Springer Verlag 10.1007/978-3-642-16129-2_11

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A feature represents a functional requirement fulfilled by a system. Since many maintenance tasks are expressed in terms of features, it is important to establish the correspondence between a feature and its implementation in source code. Traditional approaches to establish this correspondence exercise features to generate a trace of runtime events, which is then processed by post-mortem analysis. These approaches typically generate large amounts of data to analyze. Due to their static nature, these approaches do not support incremental and interactive analysis of features. We propose a radically different approach called live feature analysis, which provides a model at runtime of features. Our approach analyzes features on a running system and also makes it possible to grow feature representations by exercising different scenarios of the same feature, and identifies execution elements even to the sub-method level. We describe how live feature analysis is implemented effectively by annotating structural representations of code based on abstract syntax trees. We illustrate our live analysis with a case study where we achieve a more complete feature representation by exercising and merging variants of feature behavior and demonstrate the efficiency or our technique with benchmarks.

Item Type: Book Section (Book Chapter)
Division/Institute: 08 Faculty of Science > Institute of Computer Science (INF)
UniBE Contributor: Ressia, Jorge Luis and Nierstrasz, Oscar Marius
Series: Lecture Notes in Computer Science
Publisher: Springer Verlag
Language: English
Submitter: Factscience Import
Date Deposited: 04 Oct 2013 14:17
Last Modified: 04 May 2014 23:07
Publisher DOI: 10.1007/978-3-642-16129-2_11
Web of Science ID: 000288720200011
URI: (FactScience: 209617)

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