An empirical study on the maintenance of source code clones

Abstract

Code cloning has been very often indicated as a bad software development practice. However, many studies appearing in the literature indicate that this is not always the case. In fact, either changes occurring in cloned code are consistently propagated, or cloning is used as a sort of templating strategy, where cloned source code fragments evolve independently. This paper (i) proposes an automatic approach to classify the evolution of source code clone fragments, and (ii) reports a fine-grained analysis of clone evolution in four different Java and C software systems, aimed at investigating to what extent clones are consistently propagated or they evolve independently. Also, the paper investigates the relationship between the presence of clone evolution patterns and other characteristics such as clone raSuresh Thummalapenta North Carolina State University, Raleigh, USA E-mail: sthumma@ncsu.edu Luigi Cerulo, Lerina Aversano, Massimiliano Di Penta Department of Engineering -University of Sannio, Benevento, Italy E-mail: lcerulo@unisannio.it, aversano@unisannio.it, dipenta@unisannio.it 2 dius, clone size and the kind of change the clones underwent, i.e., corrective maintenance or enhancement.

Searching for better configurations: a rigorous approach to clone evaluation

“…Several studies [18,32,22] have provided evidence for widespread presence of clones and there has been much interest and previous work on software engineering applications and implications such as software evolution [21,36,7,3,29], refactoring [4], and bug detection [24,31,23]. Many tools and techniques for detecting clones have been studied [34].…”

Towards multilingual programming environments

“…Commonly this versioning support lives mostly on the file or syntactical level. At the same time, useful historical analyses on the abstract semantical level are being developed, such as clone evolution [28]. The problem with abstract models and language inter-dependencies in the IDE is that they too must provide historic information in order to provide meaningful support [7].…”

Mining fine-grained code changes to detect unknown change patterns

“…Uddin et al [32] proposed to mine VCS histories of client applications to study how their use of APIs evolves over time, which is helpful both to developers and users of the libraries' APIs. Canfora et al [4,5] and Thummalapenta et al [30] used VCS snapshots to study and track the evolution of different software entities such as source lines, bugs, and clones. More recently, Nguyen et al [25] extracted methodlevel code changes from revision histories of Java projects and studied their within-project and cross-project repetitiveness.…”