A Systematic Review of Semantic Clone Detection Techniques in Software Systems

Kumar, Ajad; Yadav, Rashmi; Kumar, Kuldeep

doi:10.1088/1757-899x/1022/1/012074

Cited by 6 publications

(4 citation statements)

References 7 publications

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“…A program control flow graph was utilized to capture every statement's execution attributes and extract the context association of diverse statements in the control flow. The experimental outcomes proved that the recommended mechanism performed more effectively as compared to other techniques while detecting the clone of Type-3 and Type-4 (12) .…”

Section: Related Workmentioning

confidence: 91%

“…Researchers have conducted diverse studies and presented several code clone detection techniques for improving the process of detecting code cloning (4)(5)(6)(7)(8)(9)(10)(11)(12)(13)(14)(15)(16)(17)(18)(19)(20) . There are distinct domains for these techniques.…”

Section: Related Workmentioning

confidence: 99%

“…There are distinct domains for these techniques. Diverse techniques for clone detection are reviewed in this section (4)(5)(6)(7)(8)(9)(10)(11)(12) .…”

Section: Related Workmentioning

confidence: 99%

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Analysis of Research Trends Towards Types of Code Clone Detection Techniques

Solanki¹,

Dalal²

2023

IJST

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Objective: The key research objectives of this study are: (1.) To compare and contrast the research trend towards the tree, token, text, metric, and graph-based code clone detection techniques; (2.) To study the distribution of metric-based code clone detection techniques on various online repositories; (3.) To make a statistical analysis of the hybrid techniques available for clone detection. The overall objective is to investigate the research trends of code clone detection approaches. Methods: Various repositories like google scholar, IEEE, and ELSEVIER Digital Libraries were systematically examined to attain the results in terms of research articles published in various places like conferences, journals, etc. followed by the inclusion and exclusion criteria. Findings: (1.) The findings related to objective 1 depicted that 50% of total clone detection techniques are tree and graph-based Code Clone Detection techniques followed by 20% of text-based and 30% of token-based code-clone detection techniques (2.) The findings related to the second objective depicted that an equal percentage of 46% of research work related to metric-based code clone detection techniques has been published in journals and conferences. (3.) The findings related to the third objective showed that 43% of hybrid code clone detection techniques are based on machine learning techniques, 24% are based on neural networks, and 18% of techniques are data mining based followed by 15% nature inspired based algorithms. Novelty: The study conducted is novel in identifying and exploring those potential code clone detection techniques that are underutilized and least explored. The result of research questions will assist researchers to draw inferences regarding usage, application, research trends, future needs, and research directions.

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Section: Related Workmentioning

confidence: 91%

Section: Related Workmentioning

confidence: 99%

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Analysis of Research Trends Towards Types of Code Clone Detection Techniques

Solanki¹,

Dalal²

2023

IJST

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“…However, the proliferation of code clones can create maintenance problems that are time-consuming and costly to address [15]. Code clones can be classified into two basic categories: syntactic clones, which are based on the structure of the code (first, second, and third types), and semantic clones, which based on the functionality of the code (fourth type) [16].…”

Section: Code Clonementioning

confidence: 99%

A literature review for measuring maintainability of code clone

Khaleel,

Al-Khatouni

2023

IJEECS

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Software organizations face constant pressure due to stakeholder requirements and the increasing complexity of software systems. This complexity, combined with defects in code quality and failures, can pose risks to software systems. To ensure code is understood before maintenance, developers must spend over 60% of their time modifying and improving code quality, which is costly. This study examines the impact of code refactoring activities on software maintainability and quality by reviewing relevant research and explaining key terms. The research finds that refactoring activities can enhance specific quality characteristics, including maintainability, understandability, and testability. The study also identifies important factors that should be considered when developing refactoring tools. Refactoring enables code improvement without altering program behavior and can be applied multiple times to source code.

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