DocumentCode
1691430
Title
A Metric Extraction Framework Based on a High-Level Description Language
Author
Alikacem, E.-H. ; Sahraoui, Houari A.
Author_Institution
Centre de Rech. Inf. de Montreal, Montreal, QC, Canada
fYear
2009
Firstpage
159
Lastpage
167
Abstract
Nowadays, many tools are available for metric extraction. However, extending these tools with new metrics or modifying the calculation of existing ones is often difficult, sometimes impossible. Indeed, many of them are black box tools. Others can be extended only by modifying third-party code. Moreover, metric specifications often lack precision, which leads to implementations that do not correspond necessarily to userspsila expectations. In this paper, we propose a flexible approach for metric collection based on a metric description language that allows manipulating basic data extracted from the code. These data are mapped to a generic object-oriented meta-model that is language agnostic. This makes it easy to focus on the metric specification rather than language specific constructs. Metric specifications are interpreted automatically to extract their corresponding values for a target program.
Keywords
data models; formal specification; object-oriented programming; software metrics; specification languages; black box tool; flexible metric collection approach; generic language-agnostic object-oriented meta-model; high-level metric description language; language-specific construct; metric specification; object-oriented metric extraction framework; source code representation; third-party code; Automatic control; Computer languages; Costs; Data mining; Natural languages; Object oriented modeling; Process control; Programming; Software maintenance; Software quality; Metric extraction; meta-model.; object-oriented metrics; source code representation;
fLanguage
English
Publisher
ieee
Conference_Titel
Source Code Analysis and Manipulation, 2009. SCAM '09. Ninth IEEE International Working Conference on
Conference_Location
Edmonton, AB
Print_ISBN
978-0-7695-3793-1
Type
conf
DOI
10.1109/SCAM.2009.27
Filename
5279926
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