A tool for design pattern detection and software architecture reconstruction

Fontana, Francesca Arcelli; Zanoni, Marco

doi:10.1016/j.ins.2010.12.002

Cited by 56 publications

(6 citation statements)

References 40 publications

(43 reference statements)

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“…A tool that is able to recognize an instance of a Visitor pattern would be, in principle, more precise in detecting real smells than one that is unable to. We are also doing some preliminary research to correlate code smells and micro patterns [AFZ11a] and both antipatterns and design pattern detection within our MARPLE project [AFZ11b].…”

Section: Discussionmentioning

confidence: 99%

Automatic detection of bad smells in code: An experimental assessment.

Fontana¹,

Braione²,

Zanoni³

2012

JOT

Self Cite

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Code smells are structural characteristics of software that may indicate a code or design problem that makes software hard to evolve and maintain, and may trigger refactoring of code. Recent research is active in defining automatic detection tools to help humans in finding smells when code size becomes unmanageable for manual review. Since the definitions of code smells are informal and subjective, assessing how effective code smell detection tools are is both important and hard to achieve. This paper reviews the current panorama of the tools for automatic code smell detection. It defines research questions about the consistency of their responses, their ability to expose the regions of code most affected by structural decay, and the relevance of their responses with respect to future software evolution. It gives answers to them by analyzing the output of four representative code smell detectors applied to six different versions of GanttProject, an open source system written in Java. The results of these experiments cast light on what current code smell detection tools are able to do and what the relevant areas for further improvement are.

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Section: Discussionmentioning

confidence: 99%

Automatic detection of bad smells in code: An experimental assessment.

Fontana¹,

Braione²,

Zanoni³

2012

JOT

Self Cite

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“…The research described in [35] proposed a plug-in named as Metrics and Architecture Reconstruction Plug-in for Eclipse (MARPLE) for software architecture restructuring and design pattern detection of the source code implementation. The research described in [36] presented a generic metamodel-driven process for reconstructing software architecture and proposed CaCOphoNy.…”

Section: Related Workmentioning

confidence: 99%

Harmony Search-Based Approach for Multi-Objective Software Architecture Reconstruction

Prajapati

Geem

2020

Mathematics

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The success of any software system highly depends on the quality of architectural design. It has been observed that over time, the quality of software architectural design gets degraded. The software system with poor architecture design is difficult to understand and maintain. To improve the architecture of a software system, multiple design goals or objectives (often conflicting) need to be optimized simultaneously. To address such types of multi-objective optimization problems a variety of metaheuristic-oriented computational intelligence algorithms have been proposed. In existing approaches, harmony search (HS) algorithm has been demonstrated as an effective approach for numerous types of complex optimization problems. Despite the successful application of the HS algorithm on different non-software engineering optimization problems, it gained little attention in the direction of architecture reconstruction problem. In this study, we customize the original HS algorithm and propose a multi-objective harmony search algorithm for software architecture reconstruction (MoHS-SAR). To demonstrate the effectiveness of the MoHS-SAR, it has been tested on seven object-oriented software projects and compared with the existing related multi-objective evolutionary algorithms in terms of different software architecture quality metrics and metaheuristic performance criteria. The experimental results show that the MoHS-SAR performs better compared to the other related multi-objective evolutionary algorithms.

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“…Semantic web technologies are also exploited in , where a methodology is presented for pattern recognition, which is based on an internal semantic data model representation of the source code and on SPARQL queries execution as the analysis mechanism. The work described in proposes a tool, in the form of an Eclipse plug‐in called Metrics and Architecture Reconstruction Plug‐in for Eclipse (MARPLE), which perfectly falls in the scenario of pattern recognition from source code. In particular, MARPLE supports both the detection of design patterns and software architecture reconstruction activities through the use of metrics that are automatically extracted from JAVA source code.…”

Section: State Of Artmentioning

confidence: 99%

A rule-based procedure for automatic recognition of design patterns in UML diagrams

Martino

Esposito

2015

Softw. Pract. Exper.

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Summary In the present work, we describe a procedure and a prototype implementation for the automatic recognition of design patterns from documentation of software artefacts design and implementation, provided in a machine readable form, namely, the XML Metadata Interchange (XMI) coded representation of UML class diagrams. The procedure exploits a semantic representation of the patterns to be recognized, based on an existing Web Ontology Language (OWL), known as object design ontology layer (ODOL), defined by the University of Massey (New Zealand), which has been augmented with an OWL‐S based representation of the patterns' dynamic behaviour. Both the UML set of diagrams related to the analysed software artefacts and the ODOL+OWL‐S patterns representation are automatically scanned and translated into a first‐order logic representation (namely Prolog). A set of first‐order logic rules, independent from the specific pattern to be recognized, has been defined to describe the heuristics and features which trigger the recognition, exploiting the Prolog description of the patterns to be recognized and the base of Prolog facts, which represents the UML documentation. Copyright © 2015 John Wiley & Sons, Ltd.

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A tool for design pattern detection and software architecture reconstruction

Cited by 56 publications

References 40 publications

Automatic detection of bad smells in code: An experimental assessment.

Automatic detection of bad smells in code: An experimental assessment.

Harmony Search-Based Approach for Multi-Objective Software Architecture Reconstruction

A rule-based procedure for automatic recognition of design patterns in UML diagrams

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