Structured Review of the Evidence for Effects of Code Duplication on Software Quality

This report presents the detailed steps and results of a structured review of code clone literature. The aim of the review is to investigate the evidence for the claim that code duplication has a negative effect on code changeability. This report contains only the details of the review for which there is not enough place to include them in the companion paper published at a conference (Hordijk, Ponisio et al. 2009 - Harmfulness of Code Duplication - A Structured Review of the Evidence)

コードクローン ブンセキ ツール Gemini ヲ モチイタ コードクローン ブンセキ シュホウ

第5 回クリティカル・ソフトウェア・ワークショップ2005 年11

Reverse engineering to achieve maintainable WWW sites

The growth of the World Wide Web and the accelerated development of web sites and associated web technologies has resulted in a variety of maintenance problems. The maintenance problems associated with web sites and the WWW are examined. It is argued that currently web sites and the WWW lack both data abstractions and structures that could facilitate maintenance. A system to analyse existing web sites and extract duplicated content and style is described here. In designing the system, existing Reverse Engineering techniques have been applied, and a case for further application of these techniques is made in order to prepare sites for their inevitable evolution in futur

A novel approach for Software Clone detection using Data Mining in Software

The Similar Program structures which recur in variant forms in software systems are code clones. Many techniques are proposed in order to detect similar code fragments in software. The software maintenance is generally helped by maintenance is generally helped by the identification and subsequent unification. When the patterns of simple clones reoccur, it is an indication for the presence of interesting higher-level similarities. They are called as Structural Clones. The structural clones when compared to simple clones show a bigger picture of similarities. The problem of huge number of clones is alleviated by the structural clones, which are part of logical groups of simple clones. In order to understand the design of the system for better maintenance and reengineering for reuse, detection of structural clones is essential. In this paper, a technique which is useful to detect some useful types of structural clones is proposed. The novelty of the present approach comprises the formulation of the structural clone concept and the application of data mining techniques. A novel approach is useful for implementation of the proposed technique is described

An Extended Stable Marriage Problem Algorithm for Clone Detection

Code cloning negatively affects industrial software and threatens intellectual property. This paper presents a novel approach to detecting cloned software by using a bijective matching technique. The proposed approach focuses on increasing the range of similarity measures and thus enhancing the precision of the detection. This is achieved by extending a well-known stable-marriage problem (SMP) and demonstrating how matches between code fragments of different files can be expressed. A prototype of the proposed approach is provided using a proper scenario, which shows a noticeable improvement in several features of clone detection such as scalability and accuracy.Comment: 20 pages, 10 figures, 6 table

Enhancing code clone detection using control flow graphs

Code clones are syntactically or semantically equivalent code fragments of source code. Copy-and-paste programming allows software developers to improve development productivity, but it could produce code clones that can introduce non-trivial difficulties in software maintenance. In this paper, a code clone detection framework is presented with a feature extractor and a clone classifier using deep learning. The clone classifier is trained with true and false clones and then is tested with a test dataset to evaluate the performance of the proposed approach to clone detection. In particular, the proposed approach to clone detection uses Control Flow Graphs (CFGs) to extract features of a given code snippet. The selected features are used to compute similarity scores for comparing two code fragments. The clone classifier is trained and tested with similarity scores that quantify the degree of how similar two code fragments are. The experimental results demonstrate that using CFG features is a viable methodology in terms of the effectiveness of clone detection for both syntactic and semantic clones