7,274 research outputs found
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)
Extraction of Product Evolution Tree from Source Code of Product Variants
Proceedings of the 17th International Software Product Line Conference SPLC '13 Proceedings of the 17th International Software Product Line Conferenc
Toward an improved understanding of software change
Structural changes, including moving, renaming, merging and splitting are important design change decisions made by programmers. However, during the process of software evolution, this information often gets lost. Recovering instances of structural changes in the past, as well as understanding them, are essential for us to achieve a better understanding of how and why software changes.
In this thesis, we propose an approach that helps to recover and understand the lost information of structural changes
Source File Set Search for Clone-and-Own Reuse Analysis
Clone-and-own approach is a natural way of source code reuse for software
developers. To assess how known bugs and security vulnerabilities of a cloned
component affect an application, developers and security analysts need to
identify an original version of the component and understand how the cloned
component is different from the original one. Although developers may record
the original version information in a version control system and/or directory
names, such information is often either unavailable or incomplete. In this
research, we propose a code search method that takes as input a set of source
files and extracts all the components including similar files from a software
ecosystem (i.e., a collection of existing versions of software packages). Our
method employs an efficient file similarity computation using b-bit minwise
hashing technique. We use an aggregated file similarity for ranking components.
To evaluate the effectiveness of this tool, we analyzed 75 cloned components in
Firefox and Android source code. The tool took about two hours to report the
original components from 10 million files in Debian GNU/Linux packages. Recall
of the top-five components in the extracted lists is 0.907, while recall of a
baseline using SHA-1 file hash is 0.773, according to the ground truth recorded
in the source code repositories.Comment: 14th International Conference on Mining Software Repositorie
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
SZZ Unleashed: An Open Implementation of the SZZ Algorithm -- Featuring Example Usage in a Study of Just-in-Time Bug Prediction for the Jenkins Project
Numerous empirical software engineering studies rely on detailed information
about bugs. While issue trackers often contain information about when bugs were
fixed, details about when they were introduced to the system are often absent.
As a remedy, researchers often rely on the SZZ algorithm as a heuristic
approach to identify bug-introducing software changes. Unfortunately, as
reported in a recent systematic literature review, few researchers have made
their SZZ implementations publicly available. Consequently, there is a risk
that research effort is wasted as new projects based on SZZ output need to
initially reimplement the approach. Furthermore, there is a risk that newly
developed (closed source) SZZ implementations have not been properly tested,
thus conducting research based on their output might introduce threats to
validity. We present SZZ Unleashed, an open implementation of the SZZ algorithm
for git repositories. This paper describes our implementation along with a
usage example for the Jenkins project, and conclude with an illustrative study
on just-in-time bug prediction. We hope to continue evolving SZZ Unleashed on
GitHub, and warmly invite the community to contribute
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