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)

Structured Review of Code Clone Literature

This report presents the results of a structured review of code clone literature. The aim of the review is to assemble a conceptual model of clone-related concepts which helps us to reason about clones. This conceptual model unifies clone concepts from a wide range of literature, so that findings about clones can be compared with each other

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

Dissection of a Bug Dataset: Anatomy of 395 Patches from Defects4J

Well-designed and publicly available datasets of bugs are an invaluable asset to advance research fields such as fault localization and program repair as they allow directly and fairly comparison between competing techniques and also the replication of experiments. These datasets need to be deeply understood by researchers: the answer for questions like "which bugs can my technique handle?" and "for which bugs is my technique effective?" depends on the comprehension of properties related to bugs and their patches. However, such properties are usually not included in the datasets, and there is still no widely adopted methodology for characterizing bugs and patches. In this work, we deeply study 395 patches of the Defects4J dataset. Quantitative properties (patch size and spreading) were automatically extracted, whereas qualitative ones (repair actions and patterns) were manually extracted using a thematic analysis-based approach. We found that 1) the median size of Defects4J patches is four lines, and almost 30% of the patches contain only addition of lines; 2) 92% of the patches change only one file, and 38% has no spreading at all; 3) the top-3 most applied repair actions are addition of method calls, conditionals, and assignments, occurring in 77% of the patches; and 4) nine repair patterns were found for 95% of the patches, where the most prevalent, appearing in 43% of the patches, is on conditional blocks. These results are useful for researchers to perform advanced analysis on their techniques' results based on Defects4J. Moreover, our set of properties can be used to characterize and compare different bug datasets.Comment: Accepted for SANER'18 (25th edition of IEEE International Conference on Software Analysis, Evolution and Reengineering), Campobasso, Ital

Systematic evaluation of design choices for software development tools

[Abstract]: Most design and evaluation of software tools is based on the intuition and experience of the designers. Software tool designers consider themselves typical users of the tools that they build and tend to subjectively evaluate their products rather than objectively evaluate them using established usability methods. This subjective approach is inadequate if the quality of software tools is to improve and the use of more systematic methods is advocated. This paper summarises a sequence of studies that show how user interface design choices for software development tools can be evaluated using established usability engineering techniques. The techniques used included guideline review, predictive modelling and experimental studies with users