A Method to Recover Design Patterns Using Software Product Metrics

Kim, Hyoseob; Boldyreff, Cornelia

doi:10.1007/978-3-540-44995-9_19

Cited by 19 publications

(8 citation statements)

References 7 publications

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“…There is also a technique that outputs candidate patterns based on features derived from metric measurements [6]. However, it requires manual confirmation; this technique can roughly identify candidate patterns, but the final choice depends on the developer's skill.…”

Section: Conventional Techniques and Their Problemsmentioning

confidence: 99%

Detecting Design Patterns in Object-Oriented Program Source Code by Using Metrics and Machine Learning

Uchiyama

Kubo

Washizaki

et al. 2014

JSEA

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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.

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Section: Conventional Techniques and Their Problemsmentioning

confidence: 99%

Detecting Design Patterns in Object-Oriented Program Source Code by Using Metrics and Machine Learning

Uchiyama

Kubo

Washizaki

et al. 2014

JSEA

View full text Add to dashboard Cite

show abstract

“…Another automatic approach based on metrics is proposed in Kim and Boldyreff (2000). The method is able to represent the source code in terms of metrics that can be of three possible categories: object-oriented, structural, and procedural.…”

Section: Related Workmentioning

confidence: 99%

Design pattern recovery through visual language parsing and source code analysis

Lucia

Deufemia

Gravino

et al. 2009

Journal of Systems and Software

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“…Metric‐based techniques compute program‐related metrics (e.g., generalizations, aggregations, associations, and interface hierarchies) from different source code representations and compare their values with source code DP metrics. These techniques are computationally efficient because they reduce the search space through filtration . The limit is that they have been experimented on a few numbers of patterns.…”

Section: Related Workmentioning

confidence: 99%

Design pattern detection using a DSL-driven graph matching approach

Bernardi

Cimitile

Lucca

2014

J. Softw. Evol. and Proc.

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Knowledge about design pattern (DP) instances improves program comprehension and reengineering of object‐oriented systems. Effectively, it helps to discover developer design decisions and trade‐offs that often are not documented. This work describes an approach to automatically detect DPs in existing object‐oriented systems by tracing systems' source code components with the roles they play in the patterns. In the proposed approach, DPs are modeled based on their high‐level structural properties (e.g., inheritance, dependency, invocation, delegation, type nesting, and membership relationships) that are checked, by source code parsing, against the system structure and components. Moreover, the approach can also detect pattern variants, defined by overriding the pattern properties. This paper presents a description of the approach, provides a brief description of the supporting tool, and discusses the results from the experiments carried out to validate it. The approach was validated on seven systems of an open benchmark that contains systems of increasing sizes. For five additional systems, the results have been compared with the ones from a similar approach existing in the literature. The obtained results, the identified DP variants, and the effectiveness of the approach are thoroughly presented and discussed. Copyright © 2014 John Wiley & Sons, Ltd.

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A Method to Recover Design Patterns Using Software Product Metrics

Cited by 19 publications

References 7 publications

Detecting Design Patterns in Object-Oriented Program Source Code by Using Metrics and Machine Learning

Detecting Design Patterns in Object-Oriented Program Source Code by Using Metrics and Machine Learning

Design pattern recovery through visual language parsing and source code analysis

Design pattern detection using a DSL-driven graph matching approach

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