What is Your Code Clone Detection and Evolution Research Made Of?

Object-oriented programming today, is the main prototype in typical software development. Code Cloning defines generally, all through the designing and development of software systems. Detection can be based on Textual analysis, Lexical analysis, Syntax analysis, Semantic analysis, Hybrid analysis and Metric analysis. The major drawback of the present research is that it focuses more on fragments of copied code and does not focus on the aspect that the fragments of duplicated code are may be part of a larger replicated program structure. In this process, techniques take a lot of time and it creates complexity. In our research, a source code is then scanned for detecting various methods by adopting a “OPTIMIZED SVM ALGORITHM” and the method definitions are extracted and collected by means of a CLONE CODE and saved for further reference. To evaluate the performance parameters we calculate the LOC, the number of repetitions, and maximum and minimum LOC. To enhance the performance metrics precision recall, accuracy and reduce the error rate and time complexity

Download Full-text

Code clone detection experience at microsoft

Proceeding of the 5th international workshop on Software clones - IWSC '11 ◽

10.1145/1985404.1985417 ◽

2011 ◽

Cited By ~ 13

Author(s):

Yingnong Dang ◽

Song Ge ◽

Ray Huang ◽

Dongmei Zhang

Keyword(s):

Clone Detection ◽

Code Clone

Download Full-text

Integrated Reasoning Engine for Code Clone Detection

ABC Journal of Advanced Research ◽

10.18034/abcjar.v3i2.575 ◽

2014 ◽

Vol 3 (2) ◽

pp. 143-152 ◽

Cited By ~ 5

Author(s):

Naresh Babu Bynagari

Keyword(s):

Clone Detection ◽

Code Clones ◽

High Pitch ◽

Detection Process ◽

Code Clone ◽

Similar Code ◽

Reasoning Engine

This article seeks to foray into the nitty-gritty of integrated reasoning for code clone detection and how it is effectively carried out, given the amount of analytics usually associated with such activities. Detection of codes requires high-pitch familiarity with cloning systems and their workings. Hence, discovering similar code segments that are often regarded and seen as code imitations (clone) is not an easy responsibility. More especially, this very detection process might possess key purposes in the context of susceptibility findings, refactoring, and imitation detecting. Through the voyage of discovery this article intends to expose you to, you will realize that identical code segments, more often than not described as code clones, appear to be a serious duty, especially for large code bases <1; 2; 3; 4>. There are certain approaches and deep technicalities that this sort of detection is known for. Still, from the avalanche of resources that formed the bedrock of this article, one would discover the easiest formula to adopt in maneuvering such strenuous issues.

Download Full-text

Code Clone Detection using Generic Approach

International Journal for Research in Applied Science and Engineering Technology ◽

10.22214/ijraset.2018.3556 ◽

2018 ◽

Vol 6 (3) ◽

pp. 2431-2434

Author(s):

Dr. Amita Goel

Keyword(s):

Clone Detection ◽

Code Clone

Download Full-text

Using Dynamic Time Warping to Detect Clones in Software Systems

International Journal of Software Innovation ◽

10.4018/ijsi.2021010103 ◽

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.

Download Full-text