Large software systems need to be evolved to cope with their changing environment, e.g. to incorporate new functionalities, or to better use the underlying hardware. This paper proposes an approach to reveal which parts of a system can be isolated in a module, and which parts can potentially run in parallel. We use a graph representation for the data extracted from a target software system and for the queries that express our desired analyses. Then we employ a matching framework performing queries on the target graph. The data representation is highly flexible and supports several analyses, shown in our experiments.

Program Analysis and Graph Pattern Matching to Reveal Modularity and Potential for Parallelism

Andrea Fornaia;Misael Mongiovì;Giuseppe Pappalardo;Emiliano Tramontana
2018

Abstract

Large software systems need to be evolved to cope with their changing environment, e.g. to incorporate new functionalities, or to better use the underlying hardware. This paper proposes an approach to reveal which parts of a system can be isolated in a module, and which parts can potentially run in parallel. We use a graph representation for the data extracted from a target software system and for the queries that express our desired analyses. Then we employ a matching framework performing queries on the target graph. The data representation is highly flexible and supports several analyses, shown in our experiments.
978-1-7281-1970-0
Static analysis, data dependence, mining software repositories, refactoring, parallelism, big data
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/20.500.11769/365940
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