Graph-Based Analysis and Prediction for Software Evolution.

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Bibliographic Details
Title:	Graph-Based Analysis and Prediction for Software Evolution.
Authors:	Bhattacharya, Pamela¹ pamelab@cs.ucr.edu, Iliofotou, Marios¹ marios@cs.ucr.edu, Neamtiu, Iulian¹ neamtiu@cs.ucr.edu, Faloutsos, Michalis¹ michalis@cs.ucr.edu
Source:	ICSE: International Conference on Software Engineering. Feb2012, p419-429. 11p.
Subjects:	Computer software development, Computer programming management, Computer reliability, Software refactoring, Open source software, Mozilla Firefox (Computer software)
Abstract:	We exploit recent advances in analysis of graph topology to better understand software evolution, and to construct predictors that facilitate software development and maintenance. Managing an evolving, collaborative software system is a complex and expensive process, which still cannot ensure software reliability. Emerging techniques in graph mining have revolutionized the modeling of many complex systems and processes. We show how we can use a graph-based characterization of a software system to capture its evolution and facilitate development, by helping us estimate bug severity, prioritize refactoring efforts, and predict defect-prone releases. Our work consists of three main thrusts. First, we construct graphs that capture software structure at two different levels: (a) the product, i.e., source code and module level, and (b) the process, i.e., developer collaboration level. We identify a set of graph metrics that capture interesting properties of these graphs. Second, we study the evolution of eleven open source programs, including Firefox, Eclipse, MySQL, over the lifespan of the programs, typically a decade or more. Third, we show how our graph metrics can be used to construct predictors for bug severity, high-maintenance software parts, and failureprone releases. Our work strongly suggests that using graph topology analysis concepts can open many actionable avenues in software engineering research and practice. [ABSTRACT FROM AUTHOR]
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Database:	Engineering Source

Description
Abstract:	We exploit recent advances in analysis of graph topology to better understand software evolution, and to construct predictors that facilitate software development and maintenance. Managing an evolving, collaborative software system is a complex and expensive process, which still cannot ensure software reliability. Emerging techniques in graph mining have revolutionized the modeling of many complex systems and processes. We show how we can use a graph-based characterization of a software system to capture its evolution and facilitate development, by helping us estimate bug severity, prioritize refactoring efforts, and predict defect-prone releases. Our work consists of three main thrusts. First, we construct graphs that capture software structure at two different levels: (a) the product, i.e., source code and module level, and (b) the process, i.e., developer collaboration level. We identify a set of graph metrics that capture interesting properties of these graphs. Second, we study the evolution of eleven open source programs, including Firefox, Eclipse, MySQL, over the lifespan of the programs, typically a decade or more. Third, we show how our graph metrics can be used to construct predictors for bug severity, high-maintenance software parts, and failureprone releases. Our work strongly suggests that using graph topology analysis concepts can open many actionable avenues in software engineering research and practice. [ABSTRACT FROM AUTHOR]