Understanding the evolution of Type-3 clones: An exploratory study

Saha, Ripon K.; Roy, Chanchal K.; Schneider, Kevin A.; Perry, Dewayne E.

doi:10.1109/msr.2013.6624021

Cited by 23 publications

(15 citation statements)

References 27 publications

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“…Saha et al [14] conducted exploratory research on Type-I, Type-II, and Type-III clone evolution in six open source software systems which were written in two programming languages and compared the results with past research to increase understanding of Type-III clone evolution.…”

Section: Prior Researchmentioning

confidence: 99%

An Automatic Advisor for Refactoring Software Clones Based on Machine Learning

Sheneamer

2020

IEEE Access

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To assist developers refactored code and to enable improvements to software quality when numbers of clones are found in software programs, we require an approach to advise developers on what a clone needs to refactor and what type of refactoring is needed. This paper suggests a unique learning method that automatically extracts features from the detected code clones and trains models to advise developers on what type needs to be refactored. Our approach differs from others which specify types of refactored clones as classes and creates a model for detecting the types of refactored clones and the clones which are anonymous. We introduce a new method by which to convert refactoring clone type outliers into U nknown clone set to improve classification results. We present an extensive comparative study and an evaluation of the efficacy of our suggested idea by using state-of-the-art classification models

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Section: Prior Researchmentioning

confidence: 99%

An Automatic Advisor for Refactoring Software Clones Based on Machine Learning

Sheneamer

2020

IEEE Access

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“…This resolution pattern can be applied if the nodes to be merged are all statements. This case is typical of Type 3 clones (Saha et al 2013). We construct the following switch statement:…”

Section: Pattern: Switch Statement With Extra Parametermentioning

confidence: 99%

Cleaning up copy–paste clones with interactive merging

Narasimhan¹,

Reichenbach

Lawall

2018

Autom Softw Eng

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Copy-paste-modify is a form of software reuse in which developers explicitly duplicate source code. This duplicated source code, amounting to a code clone, is adapted for a new purpose. Copy-paste-modify is popular among software developers, however, empirical evidence shows that it complicates software maintenance and increases the frequency of bugs. To allow developers to use copy-paste-modify without having to worry about these concerns, we propose an approach that automatically merges similar pieces of code by creating suitable abstractions. Because different kinds of abstractions may be beneficial in different contexts, our approach offers multiple abstraction mechanisms, which were selected based on a study of popular open-source repositories. To demonstrate the feasibility of our approach, we have designed and implemented a prototype merging tool for C++ and evaluated it on a number of code clones exhibiting some variation, i.e., near-miss clones, in popular Open Source packages. We observed that maintainers find our algorithmically created abstractions to be largely preferable to the existing duplicated code.

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“…Krinke [29] also investigated the stability of cloned code compared to non-cloned code. Saha et al [41] conducted an empirical study on the evolution of Type-3 clones and discovered a higher proportion of inconsistent changes for Type-3 clones.…”

Section: Evolution Of Software Clonesmentioning

confidence: 99%

Recommending Clones for Refactoring Using Design, Context, and History

Wang

Godfrey

2014

2014 IEEE International Conference on Software Maintenance and Evolution

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Abstract-Developers know that copy-pasting code (aka code cloning) is often a convenient shortcut to achieving a design goal, albeit one that carries risks to the code quality over time. However, deciding which, if any, clones should be eliminated within an existing system is a daunting task. "Fixing" a clone usually means performing an invasive refactoring, and not all clones may be worth the effort, cost, and risk that such a change entails. Furthermore, sometimes cloning fulfils a useful design role, and should not be refactored at all [23]. And clone detection tools often return very large result sets, making it hard to choose which clones should be investigated and possibly removed.In this paper, we propose an automated approach to recommend clones for refactoring by training a decision tree-based classifier. We analyze more than 600 clone instances in three medium-to large-sized open source projects, and we collect features that are associated with the source code, the context, and the history of clone instances. Our approach achieves a precision of around 80% in recommending clone refactoring instances for each target system, and similarly good precision is achieved in cross-project evaluation. By recommending which clones are appropriate for refactoring, our approach allows for better resource allocation for refactoring itself after obtaining clone detection results, and can thus lead to improved clone management in practice.

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Understanding the evolution of Type-3 clones: An exploratory study

Cited by 23 publications

References 27 publications

An Automatic Advisor for Refactoring Software Clones Based on Machine Learning

An Automatic Advisor for Refactoring Software Clones Based on Machine Learning

Cleaning up copy–paste clones with interactive merging

Recommending Clones for Refactoring Using Design, Context, and History

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