Abstract
Detecting well-known design patterns in object-oriented program source code can help maintainers understand the design of a program. Through the detection, the understandability, maintainability, and reusability of object-oriented programs can be improved. There are automated detection techniques; however, many existing techniques are based on static analysis and use strict conditions composed on class structure data. Hence, it is difficult for them to detect and distinguish design patterns in which the class structures are similar. Moreover, it is difficult for them to deal with diversity in design pattern applications. To solve these problems in existing techniques, we propose a design pattern detection technique using source code metrics and machine learning. Our technique judges candidates for the roles that compose design patterns by using machine learning and measurements of several metrics, and it detects design patterns by analyzing the relations between candidates. It suppresses false negatives and distinguishes patterns in which the class structures are similar. As a result of experimental evaluations with a set of programs, we confirmed that our technique is more accurate than two conventional techniques.
Highlights
A design pattern is an abstracted repeatable solution to a commonly occurring software design problem under a certain context
We propose a pattern detection technique that uses source code metrics and machine learning for detecting firstly roles and secondly patterns as structure of those roles1
In cross-validation, data are divided into n groups, and a test to verify a candidate role judgment is executed such that the testing data are one data group and the learning data are n-1 data groups
Summary
A design pattern is an abstracted repeatable solution to a commonly occurring software design problem under a certain context. Among the large number of reported design patterns extracted from well-designed software, the. (2014) Detecting Design Patterns in Object-Oriented Program Source Code by Using Metrics and Machine Learning. Journal of Software Engineering and Applications, 7, 983-998. Gang-of-Four (GoF) design patterns [1] are known and used in object-oriented design. Design patterns targeting object-oriented design are usually defined as partial designs composed of classes that describe the roles and abilities of objects. This pattern is composed of roles named Context, State, and ConcreteState
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