Evaluation of Accuracy in Design Pattern Occurrence Detection

Pettersson, Niklas; Löwe, Welf; Nivre, Joakim

doi:10.1109/tse.2009.92

Cited by 52 publications

(33 citation statements)

References 30 publications

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“…We also observed that there was a desire in conferences and publications for a means of evaluating patterns easily and eectively [63].…”

Section: Dpdx B1 Output Formats Of Dpd Toolsmentioning

confidence: 77%

“…These repositories are important in DPD research as a reference for assessing the accuracy of tools [63]. Moreover, a common exchange format would also help in achieving an automated round-trip in DPD tools (see Albin-Amiot et al [2]), including pattern detection, collection, fusion, visualization, validation, storage, and generation.…”

Section: Dpd Results Repositorymentioning

confidence: 99%

“…Petterson et al [63], for instance, summarized problems during the evaluation of accuracy in design pattern detection, Bellon et al [10] performed tests to evaluate and compare duplicated code detectors and Wagner et al [88] compared three Java coding rule checkers. Surprisingly, no author has yet proposed a general framework or benchmark for comparing and evaluating the results of reverse engineering tools like design pattern miners, duplicated code detectors and rule violation checkers.…”

Section: Steve Jobsmentioning

confidence: 99%

“…We also observed that there was a desire in conferences and publications for a means of evaluating patterns easily and eectively [63]. Hence, we developed a publicly available benchmark, DEEBEE (DEsign pattern Evaluation BEnchmark Environment), for evaluating and comparing design pattern miner tools.…”

Section: Thomas Bergermentioning

confidence: 99%

“…Petterson et al [63] summarized problems during an evaluation of accuracy in pattern detection. The goal was to make accuracy measurements more comparable.…”

Section: Evaluation Of Design Pattern Mining Toolsmentioning

confidence: 99%

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Evaluating and Improving Reverse Engineering Tools

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PrefaceDevelopers tend to leave some important steps and actions (e.g. properly designing the system's architecture, code review and testing) out of the software development process, and use risky practices (e.g. the copy-paste technique) so that the software can be released as fast as possible. However, these practices may turn out to be critical from the viewpoint of maintainability of the software system. In such cases, a cost-eective solution might be to re-engineer the system.Re-engineering consists of two stages, namely reverse-engineering information from the current system and, based on this information, forward-engineering the system to a new form. In this way, successful re-engineering signicantly depends on the reverse engineering phase. Therefore, it is vital to guarantee correctness, and to improve the results of the reverse engineering step. Otherwise, the re-engineering of the software system could fail due to the bad results of reverse engineering.The above issues motivated us to develop a method which extends and improves one of our reverse engineering tools, and to develop benchmarks and to perform experiments on evaluating and comparing reverse engineering tools.

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“…We also observed that there was a desire in conferences and publications for a means of evaluating patterns easily and eectively [63].…”

Section: Dpdx B1 Output Formats Of Dpd Toolsmentioning

confidence: 77%

Section: Dpd Results Repositorymentioning

confidence: 99%

Section: Steve Jobsmentioning

confidence: 99%

Section: Thomas Bergermentioning

confidence: 99%

“…Petterson et al [63] summarized problems during an evaluation of accuracy in pattern detection. The goal was to make accuracy measurements more comparable.…”

Section: Evaluation Of Design Pattern Mining Toolsmentioning

confidence: 99%

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Evaluating and Improving Reverse Engineering Tools

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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 review of code smell mining techniques

Rasool

Arshad

2015

J. Softw. Evol. and Proc.

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Over the past 15 years, researchers presented numerous techniques and tools for mining code smells. It is imperative to classify, compare, and evaluate existing techniques and tools used for the detection of code smells because of their varying features and outcomes. This paper presents an up-to-date review on the state-of-the-art techniques and tools used for mining code smells from the source code of different software applications. We classify selected code smell detection techniques and tools based on their detection methods and analyze the results of the selected techniques. We present our observations and recommendations after our critical analysis of existing code smell techniques and tools. Our recommendations may be used by existing and new tool developers working in the field of code smell detection. The scope of this review is limited to research publications in the area of code smells that focus on detection of code smells as compared with previous reviews that cover all aspects of code smells.

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Evaluation of Accuracy in Design Pattern Occurrence Detection

Cited by 52 publications

References 30 publications

Evaluating and Improving Reverse Engineering Tools

Evaluating and Improving Reverse Engineering Tools

Design pattern detection using a DSL-driven graph matching approach

A review of code smell mining techniques

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