Model clone detection based on tree comparison

Rattan, Dhavleesh; Bhatia, Rajesh; Singh, Maninder

doi:10.1109/indcon.2012.6420770

Cited by 11 publications

(6 citation statements)

References 14 publications

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“…Input References AST Nguyen et al 83 PDG Previous studies 83,85 XMI Previous studies 158,181 Code Previous studies 60,61,122,142,174 Design Previous studies 49,56,82,86,93,97,99,124,130,136,141,160,168,169,186 Software metrics Fourati et al 115 Abbreviations: AST, abstract syntax tree; PDG, program dependency graph; XMI, XML metadata interchange; XML, extended markup language. Figure 13 shows the chronological distributions of the PSs with respect to Java, C, C++, and other programing languages.…”

Section: T a B L E 8 Input Types Of Design Smells Detection Techniquesmentioning

confidence: 99%

See 1 more Smart Citation

Software smell detection techniques: A systematic literature review

AbuHassan

Alshayeb

Ghouti

2020

J Software Evolu Process

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Software smells indicate design or code issues that might degrade the evolution and maintenance of software systems. Detecting and identifying these issues are challenging tasks. This paper explores, identifies, and analyzes the existing software smell detection techniques at design and code levels. We carried out a systematic literature review (SLR) to identify and collect 145 primary studies related to smell detection in software design and code. Based on these studies, we address several questions related to the analysis of the existing smell detection techniques in terms of abstraction level (design or code), targeted smells, used metrics, implementation, and validation. Our analysis identified several detection techniques categories. We observed that 57% of the studies did not use any performance measures, 41% of them omitted details on the targeted programing language, and the detection techniques were not validated in 14% of these studies. With respect to the abstraction level, only 18% of the studies addressed bad smell detection at the design level. This low coverage urges for more focus on bad smell detection at the design level to handle them at early stages. Finally, our SLR brings to the attention of the research community several opportunities for future research.

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Section: T a B L E 8 Input Types Of Design Smells Detection Techniquesmentioning

confidence: 99%

“…Trees Previous studies 42,43,52,75,76,91,95,100,106,113,119,122,123,131,143,147,152,[161][162][163][164][165][166][167][168][169][170][171][172][174][175][176][177][179][180][181] Graphs Previous studies 63,[71][72][73][74][75][76][78][79][80][81][83][84][85][86]…”

Section: Category Referencesmentioning

confidence: 99%

Software smell detection techniques: A systematic literature review

AbuHassan

Alshayeb

Ghouti

2020

J Software Evolu Process

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“…Singh and Rattan [1] introduced an approach for the detection of UML models. This approach is used for finding the clones in the identical behavioral models.…”

Section: Related Workmentioning

confidence: 99%

“…The reason behind cloning could be intentional or unintentiona[l0]. According to Rattan et al [1] and Harjot Kaur and Kaur [2] copying existing code and pasting it with or without any change into other sections of programme is a popular process in software development. Moreover, according to Pham [7] model fragment is a set of model elements that is closed under some closure property of similarity.…”

Section: Related Workmentioning

confidence: 99%

Domain specific software cloning approach based on tokenization of UML artifacts

Amandeep

Kaur

2015

International Conference on Computing, Communication &Amp; Automation

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Unified Modeling Language domain models are conceptual models which are used to design and develop software in software development life cycle. Unexpected copy of model elements leads to many problems and are equally harmful for software maintenance the detection of clones needs to be done in domain models. The aim of the proposed technique is to analyze the software clones from Unified Modeling Language, to identify the type 1 and type 2 clones and to develop an approach for the analysis of software clones. The parameters analyzed are href, name, points, xmi: id and so on which are extracted from the class diagram. The results show the effectiveness of the technique in identifying software based on their domains.

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“…Tree comparison has been used by Rattan et al [10] for finding duplicates in class diagrams from the XMI representation using the DOM's API and XML parsing. Rubin et al [11] work with both structural and behavioural models, specifically class and statechart diagrams with the intent of refactoring models into product lines.…”

Section: Early Evaluationmentioning

confidence: 99%

An approach to clone detection in behavioural models

Antony

Alalfi

Cordy

2013

2013 20th Working Conference on Reverse Engineering (WCRE)

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Abstract-In this paper we present an approach for identifying near-miss interaction clones in reverse-engineered UML behavioural models. Our goal is to identify patterns of interaction ("conversations") that can be used to characterize and abstract the run-time behaviour of web applications and other interactive systems. In order to leverage robust near-miss code clone technology, our approach is text-based, working on the level of XMI, the standard interchange serialization for UML. Behavioural model clone detection presents several challenges -first, it is not clear how to break a continuous stream of interaction between lifelines into meaningful conversational units. Second, unlike programming languages, the XMI text representation for UML is highly non-local, using attributes to reference information in the model file remotely. In this work we use a set of contextualizing source transformations on the XMI text representation to reveal the hidden hierarchical structure of the model and granularize behavioural interactions into conversational units. Then we adapt NiCad, a near-miss code clone detection tool, to help us identify conversational clones in reverse-engineered behavioural models.

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Model clone detection based on tree comparison

Cited by 11 publications

References 14 publications

Software smell detection techniques: A systematic literature review

Software smell detection techniques: A systematic literature review

Domain specific software cloning approach based on tokenization of UML artifacts

An approach to clone detection in behavioural models

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