A Comparison of Reverse Engineering Tools Based on Design Pattern Decomposition

Arcelli, Francesca; Masiero, Simona; Raibulet, Claudia; Tisato, Francesco

doi:10.1109/aswec.2005.5

Cited by 19 publications

(15 citation statements)

References 16 publications

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“…Our approach to design pattern detection is based on the detection of design pattern subcomponents [6], which can be considered indicators of the presence of patterns. Currently we perform our analysis only exploiting static source code analysis: the Abstract Syntax Trees (ASTs) of the analyzed projects are parsed in order to obtain the structures we need for our elaboration, which we called basic elements (BE); we plan to extend our approach through the exploitation of behavioural analysis, both for DPD and SAR.…”

Section: Introductionmentioning

confidence: 99%

A tool for design pattern detection and software architecture reconstruction

Fontana

Zanoni

2011

Information Sciences

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Section: Introductionmentioning

confidence: 99%

A tool for design pattern detection and software architecture reconstruction

Fontana

Zanoni

2011

Information Sciences

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“…Perform the focused-snowballing process: for each selected paper, one author is assigned to go through the list of all references in order to find additional papers about classifications and quality properties of program metamodels. By performing the snowballing process, we additionally identified 9 papers about classification and comparisons of program metamodels and related concepts (Jin and Cordy 2006;Izquierdo and Molina 2014;Bellay and Gall 1997;Armstrong and Trudeau 1998;Sim et al 2000;Ferenc et al 2001;Ferenc et al 2002;Arcelli et al 2005;Amelunxen et al 2006) and 11 about quality properties (Favre et al 2003;Clark et al 2015;Kurtev et al 2002;Sim et al 2000;Ferenc et al 2002;Tilley et al 1994;Saint-Denis et al 2000;Jin 2001;Jin et al 2002;Czarnecki and Helsen 2003;Christopher 2006). …”

Section: Paper Selection Processmentioning

confidence: 99%

“…Then, existing classifications, comparisons of program metamodels and related concepts (Lethbridge et al 2004;Jin and Cordy 2006;Izquierdo and Molina 2014;Bellay and Gall 1997;Armstrong and Trudeau 1998;Lethbridge 1998;Sim et al 2000;Ferenc et al 2001Ferenc et al , 2002Arcelli et al 2005;Amelunxen et al 2006) are analyzed. This information is merged into one structure in the form of feature diagrams (Kang et al 1990) by referring to the basic term classification defined in our conceptual framework.…”

Section: Figmentioning

confidence: 99%

“…During the construction process of ProMeTA, the important characteristics from existing classification schemes/frameworks and comparisons (Lethbridge et al 2004;Jin and Cordy 2006;Izquierdo and Molina 2014;Bellay and Gall 1997;Armstrong and Trudeau 1998;Lethbridge 1998;Sim et al 2000;Ferenc et al 2001Ferenc et al , 2002Arcelli et al 2005;Amelunxen et al 2006) as well as discussions on quality properties (Favre et al 2003;Clark et al 2015;Kurtev et al 2002;Sim et al 2000;Ferenc et al 2002;Tilley et al 1994;Saint-Denis et al 2000;Jin 2001;Jin et al 2002;Czarnecki and Helsen 2003;Christopher 2006;Wu 2010) for program metamodels and related concepts identified by the SLR were included or mapped to the items, implying that it has adequate coverage. Thus, ProMeTA is implicitly benchmarked against existing classification schemes.…”

Section: Rq1: Does Prometa Cover All Possible Characteristics and Limmentioning

confidence: 99%

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ProMeTA: a taxonomy for program metamodels in program reverse engineering

2018

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To support program comprehension, maintenance, and evolution, metamodels are frequently used during program reverse engineering activities to describe and analyze constituents of a program and their relations. Reverse engineering tools often define their own metamodels according to the intended purposes and features. Although each metamodel has its own advantages, its limitations may be addressed by other metamodels. Existing works have evaluated and compared metamodels and tools, but none have considered all the possible characteristics and limitations to provide a comprehensive guideline for classifying, comparing, reusing, and extending program metamodels. To aid practitioners and researchers in classifying, comparing, reusing, and extending program metamodels and their corresponding reverse engineering tools according to the intended goals, we establish a conceptual framework with definitions of program metamodels and related concepts. We confirmed that any reverse engineering activity can be clearly described as a pattern based on the framework from the viewpoint of program metamodels. Then the framework is used (2018) 23:2323-2358 to provide a comprehensive taxonomy, named Program Metamodel TAxonomy (ProMeTA), which incorporates newly identified characteristics into those stated in previous works, which were identified via a systematic literature review (SLR) on program metamodels, while keeping the orthogonality of the entire taxonomy. Additionally, we validate the taxonomy in terms of its orthogonality and usefulness through the classification of popular metamodels.Empir Software Eng

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“…Arcelli et al [5] proposed three categories for design pattern mining tools, considering the information which was used during the detection process. These categories are the entire representation of design patterns, the minimal set of key structures that a design pattern consists of, and the sub-components of design patterns.…”

Section: Evaluation Of Design Pattern Mining Toolsmentioning

confidence: 99%

Evaluating and Improving Reverse Engineering Tools

Fülöp

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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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A Comparison of Reverse Engineering Tools Based on Design Pattern Decomposition

Abstract: * This research is partially supported by the MAIS project financed by MIUR -"Ministero dell'Istruzione, dell'Università e della Ricerca° in the context of the FIRB program "Fondo per gli Investimenti della Ricerca di Base". Abstract

Cited by 19 publications

References 16 publications

A tool for design pattern detection and software architecture reconstruction

A tool for design pattern detection and software architecture reconstruction

ProMeTA: a taxonomy for program metamodels in program reverse engineering

Evaluating and Improving Reverse Engineering Tools

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