Is cloned code really stable?

Mondal, Manishankar; Rahman, Saidur; Roy, Chanchal K.; Schneider, Kevin A.

doi:10.1007/s10664-017-9528-y

Cited by 26 publications

(6 citation statements)

References 39 publications

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“…To predict clone consistency-requirement during software development phase, we develop a prototype tool as an eclipse plug-in. 3 In order to collect clone instances, our prototype constructs all clone genealogies for each of the software repositories based on the detection results of NiCad, and identifies the clone consistent change pattern for each pair of clone groups occurring between adjacent versions guided by the definitions. After that, our prototype extracts attribute sets for each clone instance, and generates the training dataset for machine-learning models with the attributes.…”

Section: Methodsmentioning

confidence: 99%

“…In this genealogy, clones that are similar to one another are grouped together to form clone groups. It has been shown that frequent changes on code clones do occur during software evolution [3]. Within a clone group, changes made to one piece of code clone may require to be propagated to other clones within the group, thus remaining to be similar.…”

Section: Introductionmentioning

confidence: 99%

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Improving Maintenance-Consistency Prediction During Code Clone Creation

Zhang¹,

Khoo²,

Su³

2020

IEEE Access

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Developers frequently introduce code clones into software through the copy-and-paste operations during the software development phase in order to shorten development time. Not all such clone creations are beneficial to software maintenance, as they may introduce extra effort at the software maintenance phase, where additional care is needed to ensure consistent change among these clones; i.e., changes made to a piece of code may need to be propagated to other clones. Failure in doing so may risk introducing bugs into software, which are usually called consistent defect. In response to the rampant maintenance cost caused by the introduction of new clones, some researchers have advocated the use of machine-learning approach to predict the likelihood of consistent change requirement when clones are freshly introduced. Leading in this approach is the work by Wang et al., which uses Bayesian Network to model maintenance-consistency of newly introduced clones. In this work, we leverage the success of the above-mentioned work by providing a revised set of attributes that has been shown to strengthen the predictive power of the Bayesian network model, as determined more quantitatively by the precision and recall levels. We firstly provide the definition of clone consistency-maintenance requirement, which can help transfer this problem to a classification problem. Then, based on collecting all clone creation operations through traversing clone genealogies, we redesign the attribute sets for representing clone creation with more information in code and context perspective. We evaluate the effectiveness of our approach on four open source projects with more quantitative analysis, and the experimental results show that our approach possesses a powerful ability in predicting clone consistency. To transfer this work into practice, we develop an Eclipse plug-in tool of this prediction to aid developers in software development and maintenance.INDEX TERMS Code clones, clone consistent change, clone consistency prediction, software maintenance, machine learning.

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Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Improving Maintenance-Consistency Prediction During Code Clone Creation

Zhang¹,

Khoo²,

Su³

2020

IEEE Access

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“…Empirical studies on code clone evolution show that evolutionary aspects of clones cannot be revealed through analysis of clones in a single version. Evolution studies are performed for different types of clones [ 15 , 16 ] and for different granularity levels [ 17 – 19 ]. One of the earliest studies on code clone evolution in a systematic way was done by Kim et al [ 2 ].…”

Section: Literature Surveymentioning

confidence: 99%

Historical perspective of code clone refactorings in evolving software

et al. 2022

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Cloning in software is generally perceived as a threat to its maintenance and that is why it needs to be managed properly. Understanding clones from a historical perspective is essential for effective clone management. Analysis of code refactorings performed on clones in previous releases will help developers in taking decisions about clone refactoring in future releases. In this paper we perform a longitudinal study on the evolution of clone refactorings in various versions of five software systems. To perform a systematic study on clone refactoring evolution, we define clone evolution patterns for studying refactorings in a formal notation. Our results show that only a small proportion of code clones are refactored between the versions and most of the refactorings are inconsistent within clone classes. Moreover, clone refactorings may cause clone removal. Analysis of the source code of refactored clones reveals similar reasons of inconsistent refactorings and clone removal for five Java systems. This analysis will help in devising appropriate strategies for managing clone refactorings in software and hence provide foundation for devising better clone management tools.

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“…In [27] Mondal et al compared the stability of cloned and non-cloned parts in a software. They used eight code stability metrics and seven different methodologies in a common framework to analyze the code stability in a software.…”

Section: Literature Surveymentioning

confidence: 99%

Evolutionary Perspective of Structural Clones in Software

et al. 2019

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Cloning in software represents similar program structures having its own benefits and drawbacks. Proper clone analysis is required to exploit the benefits of clones. A study of software clone evolution serves the purpose of understanding the maintenance implications of clones, which leads to their appropriate management. Structural clones (recurring patterns of simple clones) represent design level similarities in software. Evolutionary characteristics of clones can assess the relevance of those clones for software developers and maintainers. Although the evolution of simple clones has been thoroughly studied by researchers, the evolution of structural clones is still to be explored. In this paper, we study the evolution of structural clones by performing a longitudinal study on multiple versions of five Java systems. To perform a systematic study of the structural clone evolution, we define structural clones and their evolution patterns in a formal notation. Our results show that structural clones are more likely to change inconsistently, however, less frequently than simple clones, whereas the lifetime of the structural clones is similar to that of the simple clones. Evolutionary characteristics of structural clones suggest that they require more attention in their management. Analysis of structural clone evolution reveals similar reasons for changes, and similar trends in evolution patterns, for all subject systems. These trends reveal evolutionary characteristics of structural clones that can help in devising appropriate strategies for managing them, hence devising better clone management systems.INDEX TERMS Clone evolution, software clones, structural clones, software engineering, software evolution, software design.JAWERIA KANWAL received the M.Phil. degree in computer science from Quaid-i-Azam University, Islamabad, Pakistan, in 2011, where she is currently pursuing the Ph.D. degree in computer science.

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Is cloned code really stable?

Cited by 26 publications

References 39 publications

Improving Maintenance-Consistency Prediction During Code Clone Creation

Improving Maintenance-Consistency Prediction During Code Clone Creation

Historical perspective of code clone refactorings in evolving software

Evolutionary Perspective of Structural Clones in Software

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