Abstract | ||
---|---|---|
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.
|
Year | DOI | Venue |
---|---|---|
2010 | 10.1007/978-3-642-16129-2_11 | Model Driven Engineering Languages and Systems |
Keywords | DocType | Volume |
complete feature representation,live analysis,models at runtime,interactive analysis,behavioral reflection,feature annota- tions,feature behavior,software maintenance,feature analysis,dynamic analysis,live feature analysis,feature growing.,post-mortem analysis,feature representation,different approach,approach analyzes feature,correspondence exercise feature,functional requirement,abstract syntax tree,source code | Conference | 6395 |
ISSN | ISBN | Citations |
0302-9743 | 3-642-16128-6 | 3 |
PageRank | References | Authors |
0.41 | 17 | 4 |
Name | Order | Citations | PageRank |
---|---|---|---|
Marcus Denker | 1 | 285 | 23.94 |
Jorge Ressia | 2 | 43 | 4.74 |
Orla Greevy | 3 | 215 | 14.22 |
Oscar Nierstrasz | 4 | 2404 | 346.86 |