Thesis (M.S. in computer science)--Washington State University, December 2009. / Title from PDF title page (viewed on Jan. 20, 2010). "School of Electrical Engineering and Computer Science." Includes bibliographical references (p. 60-64).

M. Tech. Information Networks / Code clone is a code portion in one source code fragment that is similar or identical to a code portion in another source code fragment. Clones in applications are inevitable within an organization's intranet. There are a great number of clone detection tools to help maintenance programmers to locate and refactor code clones where they exist. Currently clone detection process has not been explored fully to construct digital libraries to store clones for reuse and shareability. This is because most of clone detection techniques produce Indexed Statistical Reports as textual file showing related group of code fragments. Other techniques visualize clones to depict clones versions history as genealogies. Furthermore current techniques do not indicate the reusability and shareability worthiness of the detected clones in taxonomy. In this mini-dissertation a Clone Wrapper Detection Technique prototype is developed to detect and store commonly used structural clones into a Discoverable Digital Clone Library hosted in Fedora Repository. Stored clones metadata are then extracted to induce a Clone Family Tree Ontology of related class clones in a taxonomy based on Abstraction (inheritance and composition hierarchy) process.

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

Software systems continue to play an increasingly important role in our daily lives, making the quality of software systems an extremely important issue. Therefore, a significant amount of recent research focused on the prioritization of software quality assurance efforts. One line of work that has been receiving an increasing amount of attention is Software Defect Prediction (SDP), where predictions are made to determine where future defects might appear. Our survey showed that in the past decade, more than 100 papers were published on SDP. Nevertheless, the adoption of SDP in practice to date is limited. In this thesis, we survey the state-of-the-art in SDP in order to identify the challenges that hinder the adoption of SDP in practice. These challenges include the fact that the majority of SDP research rarely considers the impact of defects when performing their predictions, seldom provides guidance on how to use the SDP results, and is too reactive and defect-centric in nature. We propose approaches that tackle these challenges. First, we present approaches that predict high-impact defects. Our approaches illustrate how SDP research can be tailored to consider the impact of defects when making their predictions. Second, we present approaches that simplify SDP models so they can be easily understood and illustrates how these simple models can be used to assist practitioners in prioritizing the creation of unit tests in large software systems. These approaches illustrate how SDP research can provide guidance to practitioners using SDP. Then, we argue that organizations are interested in proactive risk management, which covers more than just defects. For example, risky changes may not introduce defects but they could delay the release of projects. Therefore, we present an approach that predicts risky changes, illustrating how SDP can be more encompassing (i.e., by predicting risk, not only defects) and proactive (i.e., by predicting changes before they are incorporated into the code base). The presented approaches are empirically validated using data from several large open source and commercial software systems. The presented research highlights how challenges of pragmatic SDP can be tackled, making SDP research more beneficial and applicable in practice. / Thesis (Ph.D, Computing) -- Queen's University, 2012-08-02 13:12:39.707

No description available.

Project report (M.S.)--Virginia Polytechnic Institute and State University, 1990. / Abstract. Includes bibliographical references (leaf 104). Also available via the Internet.

Thesis (M.S.)--Rochester Institute of Technology, 1991. / Spine title: Effect of a Reverse Engineering Tool ... Includes bibliographical references (leaves 48-49).

Thesis (M. App. Sc.)--Carleton University, 2003. / Includes bibliographical references (p. 83-84). Also available in electronic format on the Internet.

Thesis (M.App.Sc.) - Carleton University, / Includes bibliographical references (p. 53-56). Also available in electronic format on the Internet.