https://www.cs.usask.ca/~croy/papers/2009/RCK_SCP_Clones.pdf

Comparison and evaluation of code clone detection techniques and tools: A qualitative approach

It has been broadly assumed that code clones are inherently bad and that eliminating clones by refactoring would solve the problems of code clones. To investigate the validity of this assumption, we developed a formal denition of clone evolution and built a clone genealogy tool that automatically extracts the history of code clones from a source code repository. Using our tool we extracted clone genealogy information for two Java open source projects and analyzed their evolution. Our study contradicts some conventional wisdom about clones. In particular, refactoring may not always improve software with respect to clones for two reasons. First, many code clones exist in the system for only a short time; extensive refactoring of such short-lived clones may not be worthwhile if they are likely diverge from one another very soon. Second, many clones, especially long-lived clones that have changed consistently with other elements in the same group, are not easily refactorable due to programming language limitations. These insights show that refactoring will not help in dealing with some types of clones and open up opportunities for complementary clone maintenance tools that target these other classes of clones.

/pdf/an-empirical-study-of-code-clone-genealogies-4zeba5m7ml.pdf

An empirical study of code clone genealogies

A comprehensive literature survey on approaches for mining software repositories (MSR) in the context of software evolution is presented. In particular, this survey deals with those investigations that examine multiple versions of software artifacts or other temporal information. A taxonomy is derived from the analysis of this literature and presents the work via four dimensions: the type of software repositories mined (what), the purpose (why), the adopted/invented methodology used (how), and the evaluation method (quality). The taxonomy is demonstrated to be expressive (i.e., capable of representing a wide spectrum of MSR investigations) and effective (i.e., facilitates similarities and comparisons of MSR investigations). Lastly, a number of open research issues in MSR that require further investigation are identified.

/pdf/a-survey-and-taxonomy-of-approaches-for-mining-software-4vm8lmk0d5.pdf

A survey and taxonomy of approaches for mining software repositories in the context of software evolution

The goal of this paper is to discuss comparison of speech parameterization methods: Mel-Frequency Cepstrum Coefficients (MFCC) and Linear Prediction Cepstrum Coefficients (LPCC) for recognizing the stuttered events. Speech samples from UCLASS are used for our analysis. The stuttered events are identified through manual segmentation and used for feature extraction. Two simple classifiers are used for testing the proposed features. Conventional validation method is used for testing the reliability of the classifier. The experimental investigation elucidates MFCC and LPCC features which can be used for identifying the stuttered events and LPCC features were slightly outperformed than MFCC features.

Classification of speech dysfluencies with MFCC and LPCC features

Change impact analysis is required for constantly evolving systems to support the comprehension, implementation, and evaluation of changes. A lot of research effort has been spent on this subject over the last twenty years, and many approaches were published likewise. However, there has not been an extensive attempt made to summarize and review published approaches as a base for further research in the area. Therefore, we present the results of a comprehensive investigation of software change impact analysis, which is based on a literature review and a taxonomy for impact analysis. The contribution of this review is threefold. First, approaches proposed for impact analysis are explained regarding their motivation and methodology. They are further classified according to the criteria of the taxonomy to enable the comparison and evaluation of approaches proposed in literature. We perform an evaluation of our taxonomy regarding the coverage of its classification criteria in studied literature, which is the second contribution. Last, we address and discuss yet unsolved problems, research areas, and challenges of impact analysis, which were discovered by our review to illustrate possible directions for further research.

A review of software change impact analysis

This paper presents an approach to recover time variant information from software repositories. It is widely accepted that software evolves due to factors such as defect removal, market opportunity or adding new features. Software evolution details are stored in software repositories which often contain the changes history. On the other hand there is a lack of approaches, technologies and methods to efficiently extract and represent time dependent information. Disciplines such as signal and image processing or speech recognition adopt frequency domain representations to mitigate differences of signals evolving in time. Inspired by time-frequency duality, this paper proposes the use of Linear Predictive Coding (LPC) and Cepstrum coefficients to model time varying software artifact histories. LPC or Cepstrum allow obtaining very compact representations with linear complexity. These representations can be used to highlight components and artifacts evolved in the same way or with very similar evolution patterns. To assess the proposed approach we applied LPC and Cepstral analysis to 211 Linux kernel releases (i.e., from 1.0 to 1.3.100), to identify files with very similar size histories. The approach, the preliminary results and the lesson learned are presented in this paper.

http://www.antoniol.net/wp-content/papercite-data/pdf/2005/p14-antoniol.pdf

Linear predictive coding and cepstrum coefficients for mining time variant information from software repositories

With the widespread adoption of object-oriented technologies, the lack of computationally efficient and scalable approaches is limiting the ability to model and analyze the history of large object-oriented software systems. This paper proposes an approximate representation of object-oriented code characteristics, inspired by pattern recognition centroids for clustering. An interesting application of such a representation is a linear-time complexity algorithm to detect duplicate or nearly duplicated code in object-oriented systems. The algorithm accuracy and time complexity were assessed on 11 releases of a large software system, the Eclipse framework.

Linear complexity object-oriented similarity for clone detection and software evolution analyses

Software systems continuously evolve. CVS record almost all of the changes the system parts undergo. Hence, CVS repositories contain a great deal of information about software artifact evolution. Software artifacts of a system can evolve following similar evolution patterns as well as very different ones. A peculiar kind of similarity in evolution is the one among two or more artifacts having changed almost at the same times for a certain number of changes. We name these co-changing artifacts. Co-changing artifacts are relevant because co-changes can be inducted by not trivial dependencies among system parts. In this paper, we propose a definition of co-changes suitable of practical application. We assess the challenges arising in detection of groups of co-changing software parts, and we present a robust approach, based on dynamic time warping, to detect groups of co-changing files in CVS repositories. We also report and discuss the results of a preliminary application of the approach to the Mozilla CVS repository.

Detecting groups of co-changing files in CVS repositories

The paper presents a new application of content management based on a peer-to-peer platform. Several advantages following our choice of the peer-to-peer paradigm within the content management context are discussed, such as the improved scalability and flexibility of the system and the preserved ownership and off-line control of content from content creators.

ContentP2P: a peer-to-peer content management system

A. Taxpayer. IMSI contains corporate taxpayer data, which automatically creates IMSI cases that consist of one or more tax returns for the same taxpaying entity. Corporate data from ERCS (Examination Returns Control System) is the source for the IMSI repository. Tables are created which represent each of the following tax forms: 941, 1042, 1065, and 1120. Types of data collected: Taxpayer ID, TIN, Taxpayer Business ID, Business Name, taxpayer contact name, professional title; tax return exam ID and filing period; address; relationship; telephone number; percent of stock ownership by corporate officer.

V.F. Rollo

Papers

Linear predictive coding and cepstrum coefficients for mining time variant information from software repositories

Linear complexity object-oriented similarity for clone detection and software evolution analyses

Detecting groups of co-changing files in CVS repositories

ContentP2P: a peer-to-peer content management system

Business Change Impacts on System Integration.