Software clones are considered harmful in software maintenance and evolution. However, despite a decade of active research, there is a marked lack of work in the detection and analysis of near-miss software clones, those where minor to extensive modifications have been made to the copied fragments. In this thesis, we advance the state-of-the-art in clone detection and analysis in several ways. First, we develop a hybrid clone detection method, called NICAD, that can detect both exact and near-miss clones with high precision and recall and with reasonable performance. Second, in order to address the decade of vagueness in clone definition, we propose an editing taxonomy for clone creation that models developers' editing activities in the copy/pasted code in a top-down fashion. NICAD is designed to address the different types of clones in the editing taxonomy. Third, we have conducted a scenario-based qualitative comparison and evaluation of all of the currently available clone detection techniques and tools in the context of a unified conceptual framework. Using the results of this study one can more easily choose the right tools to meet the requirements and constraints of any particular application, and can identify opportunities for hybridizing different techniques. The hybrid architecture of NICAD was derived from this study. Fourth, in order to evaluate and compare the available tools in a realistic setting and to avoid the challenges and huge manual effort in validating candidate clones, we have developed a mutation-based framework that automatically and efficiently measures (and compares) the recall and precision of clone detection tools for different fine-grained clone types of the proposed editing taxonomy. We have evaluated NICAD using this framework and found that it is capable of detecting different types of clones with high precision and recall. Finally, we have conducted a large scale empirical study of cloning in open source systems, both to evaluate NICAD and to study the cloning characteristics of these systems in several different dimensions. The study has demonstrated that NICAD is capable of accurately finding both exact and near-miss function clones even in large systems and different languages, and that there seem to be a large number of clones in those systems. / Thesis (Ph.D, Computing) -- Queen's University, 2009-08-31 14:05:30.233

Software clones are considered harmful in software maintenance and evolution. However, despite a decade of active research, there is a marked lack of work in the detection and analysis of near-miss software clones, those where minor to extensive modifications have been made to the copied fragments. In this thesis, we advance the state-of-the-art in clone detection and analysis in several ways. First, we develop a hybrid clone detection method, called NICAD, that can detect both exact and near-miss clones with high precision and recall and with reasonable performance. Second, in order to address the decade of vagueness in clone definition, we propose an editing taxonomy for clone creation that models developers' editing activities in the copy/pasted code in a top-down fashion. NICAD is designed to address the different types of clones in the editing taxonomy. Third, we have conducted a scenario-based qualitative comparison and evaluation of all of the currently available clone detection techniques and tools in the context of a unified conceptual framework. Using the results of this study one can more easily choose the right tools to meet the requirements and constraints of any particular application, and can identify opportunities for hybridizing different techniques. The hybrid architecture of NICAD was derived from this study. Fourth, in order to evaluate and compare the available tools in a realistic setting and to avoid the challenges and huge manual effort in validating candidate clones, we have developed a mutation-based framework that automatically and efficiently measures (and compares) the recall and precision of clone detection tools for different fine-grained clone types of the proposed editing taxonomy. We have evaluated NICAD using this framework and found that it is capable of detecting different types of clones with high precision and recall. Finally, we have conducted a large scale empirical study of cloning in open source systems, both to evaluate NICAD and to study the cloning characteristics of these systems in several different dimensions. The study has demonstrated that NICAD is capable of accurately finding both exact and near-miss function clones even in large systems and different languages, and that there seem to be a large number of clones in those systems. / Thesis (Ph.D, Computing) -- Queen's University, 2009-08-31 14:05:30.233

Despite the fact that duplicated fragments of code also called code clones are considered one of the prominent code smells that may exist in software, cloning is widely practiced in industrial development. The larger the system, the more people involved in its development and the more parts developed by different teams result in an increased possibility of having cloned code in the system. While there are particular benefits of code cloning in software development, research shows that it might be a source of various troubles in evolving software. Therefore, investigating and understanding clones in a software system is important to manage the clones efficiently. However, when the system is fairly large, it is challenging to identify and manage those clones properly. Among the various types of clones that may exist in software, research shows detection of near-miss clones where there might be minor to significant differences (e.g., renaming of identifiers and additions/deletions/modifications of statements) among the cloned fragments is costly in terms of time and memory. Thus, there is a great demand of state-of-the-art technologies in dealing with clones in software. Over the years, several tools have been developed to detect and visualize exact and similar clones. However, usually the tools are standalone and do not integrate well with a software developer's workflow. In this thesis, first, a study is presented on the effectiveness of a fingerprint based data similarity measurement technique named 'simhash' in detecting clones in large scale code-base. Based on the positive outcome of the study, a time efficient detection approach is proposed to find exact and near-miss clones in software, especially in large scale software systems. The novel detection approach has been made available as a highly configurable and fully fledged standalone clone detection tool named 'SimCad', which can be configured for detection of clones in both source code and non-source code based data. Second, we show a robust use of the clone detection approach studied earlier by assembling its detection service as a portable library named 'SimLib'. This library can provide tightly coupled (integrated) clone detection functionality to other applications as opposed to loosely coupled service provided by a typical standalone tool. Because of being highly configurable and easily extensible, this library allows the user to customize its clone detection process for detecting clones in data having diverse characteristics. We performed a user study to get some feedback on installation and use of the 'SimLib' API (Application Programming Interface) and to uncover its potential use as a third-party clone detection library. Third, we investigated on what tools and techniques are currently in use to detect and manage clones and understand their evolution. The goal was to find how those tools and techniques can be made available to a developer's own software development platform for convenient identification, tracking and management of clones in the software. Based on that, we developed a clone-aware software development platform named 'SimEclipse' to promote the practical use of code clone research and to provide better support for clone management in software. Finally, we evaluated 'SimEclipse' by conducting a user study on its effectiveness, usability and information management. We believe that both researchers and developers would enjoy and utilize the benefit of using these tools in different aspect of code clone research and manage cloned code in software systems.