Software Architecture Recovery based on Pattern Matching Techniques - Sartipi, Kamran
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This book presents a model and an environment for recovering high level design of legacy software systems based on user defined architectural patterns and graph matching techniques. In the proposed model, a high-level view of a software system in terms of abstract components and their constrained interactions is represented as a query using a new description language. This query is mapped onto a pattern-graph, where a component and its constrained interactions with other components are represented as a group of graph-nodes and a group of graph-edges. Such a pattern is applied against an…mehr

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Produktbeschreibung
This book presents a model and an environment for recovering high level design of legacy software systems based on user defined architectural patterns and graph matching techniques. In the proposed model, a high-level view of a software system in terms of abstract components and their constrained interactions is represented as a query using a new description language. This query is mapped onto a pattern-graph, where a component and its constrained interactions with other components are represented as a group of graph-nodes and a group of graph-edges. Such a pattern is applied against an entity-relation graph of the software system. An approximate graph matching process performs a series of graph edit operations (i.e., node/edge insertion/deletion) on the pattern- graph and uses a ranking mechanism based on data mining association rules to obtain a suboptimal solution that complies with the given query. An interactive toolkit (Alborz) is developed that performs architecture recovery in two levels. First, the system is decomposed into a number of subsystems of files. Second, each subsystem is decomposed into a number of modules of functions, datatypes, and variables.
Autorenporträt
Dr. Sartipi, BSc, MSc, MMath, PhD, PEng joined McMaster University in 2003. He is interested in software engineering, reverse engineering, SOA, data mining, health informatics, and embedded systems. He has over 50 papers, developed Alborz toolkit for multi-view architecture recovery, and has been a co-developer of MSc in eHealth at McMaster.