BibTeX
@MISC{Shi07fromjava,
author = {Nija Shi},
title = {from Java Source Code},
year = {2007}
}
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Abstract
Computer Science Recovering design patterns can enhance existing source code analysis tools by bringing program understanding to the design level. This dissertation presents a new, fully au-tomated pattern detection approach based on our reclassification of the GoF patterns by their pattern intent. We argue that the GoF pattern catalog classifies design patterns in the forward-engineering sense; our reclassification is better suited for reverse engineering. Our approach uses lightweight static program analysis techniques to capture program in-tent. This dissertation also describes our tool, PINOT, that implements this new approach. PINOT detects all the GoF patterns that have concrete definitions driven by code struc-ture or system behavior. PINOT is faster, more accurate, and targets more patterns than existing pattern detection tools. PINOT has been tested against several benchmark applica-tions, including Apache Ant, Java AWT, JHotDraw, and Swing. Since PINOT has proven successful, we extend PINOT to recognize a broader range of design patterns. This disser-tation describes our pattern detection language, MUSCAT, that allows users to define and analyze their own design patterns using the PINOT engine. MUSCAT is a visual language that allows users to model program intent by specifying both the structural- and behavioral-aspects of a design pattern. This dissertation evaluates MUSCAT and discusses the trade-offs between effectiveness and flexibility.
Keyphrases
design pattern java source code gof pattern java awt computer science recovering design pattern pattern detection tool new approach design level pattern detection language program understanding forward-engineering sense concrete definition pinot engine system behavior code struc-ture au-tomated pattern detection approach pattern intent lightweight static program analysis technique visual language program intent source code analysis tool reverse engineering apache ant program in-tent several benchmark applica-tions
