scholarly journals A HYBRID TECHNIQUE FOR SOFTWARE CLONE DETECTION BY USING TOKEN BASED AND LINE BASED APPROACH

2018 ◽  
Vol 9 (2) ◽  
pp. 85-88
Author(s):  
Keyword(s):  
Hybrid Technique ◽  
Clone Detection ◽  
Software Clone Detection

scholarly journals HYBRID TECHNIQUE FOR SOFTWARE CODE CLONE DETECTION

2012 ◽  
Vol 2 (2) ◽  
pp. 98-102
Author(s):  
Priyanka Batta ◽  
Miss Himanshi
Keyword(s):  
Research Area ◽  
Software Systems ◽  
Base Line ◽  
Hybrid Technique ◽  
Clone Detection ◽  
Program Code ◽  
Code Clone ◽  
Text Base ◽  
Software Clone Detection ◽  
Software Code

Software Clone detection is one of the hottest research area that helps in detecting duplicate code from an applications. The research has shown that 5% to 20% of software systems can contain duplicated code that is generated by simply copying the existing program code and pasting with or without minor modifications. Cloning creates problem when a bug is found in one code segment that was copied and pasted at several locations earlier. The objective of this study is to analyze the working of hybrid clone detection technique that design and analyze a hybrid technique for detecting software clone in an application. We will combine metric approach with text base (line of code) technique for the above said reason. A model will be designed to automate the concept of clone detection.

Using Dynamic Time Warping to Detect Clones in Software Systems

2021 ◽  
Vol 9 (1) ◽  
pp. 20-36
Author(s):  
Mostefai Abdelkader
Keyword(s):  
Time Series ◽  
Dynamic Time Warping ◽  
Software Systems ◽  
Clone Detection ◽  
Code Clones ◽  
Time Warping ◽  
Code Clone ◽  
Software Modules ◽  
Software Clone Detection ◽  
Dynamic Time

Software clone detection is a widely researched area over the last two decades. Code clones are fragments of code judged similar by some metric of similarity. This paper proposes an approach for code clone detection using dynamic time warping technique (i.e., DTW). DTW is a well-known algorithm for aligning and measuring similarity of time series and it has been found effective in many domains where similarity plays an important role such as speech and gesture recognition. The proposed approach finds clones in three steps. First software modules are extracted. Then, the extracted modules are turned to time series. Finally, the time series are compared using the DTW algorithm to find clones. The results of the experiment conducted on a well-known Benchmark show that the approach can detect clones effectively in software systems.

scholarly journals Comprehensive Study of Software Clone Detection Techniques

2016 ◽  
Vol 18 (04) ◽  
pp. 15-19
Author(s):  
Sunayna Sunayna ◽  
Kamna Solanki ◽  
Sandeep Dalal ◽  
Sudhir Sudhir
Keyword(s):  
Clone Detection ◽  
Detection Techniques ◽  
Software Clone Detection ◽  
Comprehensive Study
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