Paper Info
Title
Ranking Refactoring Suggestions Based on Historical Volatility
Abstract
The widespread acceptance of refactorings as a simple yet effective approach to improve the design of object-oriented systems, has stimulated an effort to develop semi-automatic tools for detecting design flaws, with simultaneous suggestions for their removal. However, even in medium-sized projects the number of detected occurrences can be so large that the refactoring process becomes intractable for the designer. It is reasonable to expect that some of the suggested refactorings will have a significant effect on the improvement of maintainability while others might be less important. This implies that the suggested solutions can be ranked according to one or more criteria. In this paper we propose the exploitation of past source code versions in order to rank refactoring suggestions according to the number, proximity and extent of changes related with the corresponding code smells. The underlying philosophy is that code fragments which have been subject to maintenance tasks in the past, are more likely to undergo changes in a future version and thus refactorings involving the corresponding code should have a higher priority. To this end, historical volatility models drawn from the field of forecasting risk in financial markets, are investigated as measures expressing the urgency to resolve a given design problem. The approach has been integrated into an existing smell detection Eclipse plug-in, while the evaluation results focus on the forecast accuracy of the examined models.
Year
DOI
Venue
2011
10.1109/CSMR.2011.7
Software Maintenance and Reengineering
Keywords
Field
DocType
object-oriented methods,risk management,software maintenance,source coding,stock markets,code fragments,design flaw detection,financial markets,historical volatility model,object-oriented system design,refactoring suggestion ranking,risk forecasting,smell detection Eclipse plug-in,source code version,code smell,forecasting models,historical volatility,refactoring,software history,software repositories
Data mining,Ranking,Software engineering,Source code,Computer science,Risk management,Software maintenance,Code refactoring,Maintainability,Maintenance engineering,Code smell
Conference
ISSN
ISBN
Citations 
1534-5351
978-1-61284-259-2
23
PageRank 
References 
Authors
0.73
27
2
Name
Order
Citations
PageRank
Nikolaos Tsantalis174332.14
Alexander Chatzigeorgiou279060.13