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19 results for “software evolution”
Evolution of software code at the level of fine-grained elements: data files
<p>The data files available here (68GB uncompressed) have been used for studying the evolution of code at the level of fine-grained elements. The data are associated with the processing of the 89 open source software repositories hosted on GitHub. Details regarding each individual GitHub project are stored in the repos folder under directories matching the owner and project name used on GitHub. For example, the files under repos/KDE/kdevelop correspond to the project hosted on https://github.com/KDE/kdevelop. Data associated with the statistical analysis of the processed repositories are stored in the statistical-analysis folder. The file project_details.txt contains the data used for selecting the processed projects.</p>
Break the Code? Breaking Changes and Their Impact on Software Evolution (Artefacts)
<p>The artefacts included in this repository accompany the thesis "Break the Code? Breaking Changes and Their Impact on Software Evolution" authored by Lina María Ochoa Venegas and supervised by prof.dr. Jurgen Vinju, prof.dr. Mark van den Brand, and dr.Thomas Degueule. The thesis was developed at Eindhoven University of Technology (TU/e) in Eindhoven, The Netherlands and Centrum Wiskunde & Informatica (CWI) in Amsterdam, The Netherlands. It was submitted to revision in 2022 and defended in 2023.</p> <p> </p> <p><strong>Relevant Links</strong></p> <ul> <li><strong>Maracas:</strong> https://github.com/alien-tools/maracas</li> <li><strong>BreakBot: </strong>https://github.com/alien-tools/breakbot</li> </ul>
Architectural Feature Re-Modularization for Software Product Line Evolution
<p>Extensive maintenance leads to the Software Product Line Architecture<br> (PLA) degradation over time. When there is the need of<br> evolving the Software Product Line (SPL) to include new features,<br> or move to a new platform, a degraded PLA requires considerable<br> effort to understand and modify, demanding expensive refactoring<br> activity. In the state of the art, search-based algorithms are used to<br> improve PLA at package level. However, recent studies have shown<br> that the most variability and implementation details of an SPL are<br> described in the level of classes. There is a gap between existing<br> approaches and existing practical needs. In this work, we extend<br> the current state of the art to deal with feature modularization in<br> the level of classes by introducing a new search operator and a set<br> of objective functions to deal with feature modularization in a finer<br> granularity of the architectural elements, namely at class level. We<br> evaluated the proposal in an exploratory study with a PLA widely<br> investigated and a real-world PLA. The results of quantitative and<br> qualitative analysis point out that our proposal provides solutions<br> to properly re-modularize features in a PLA, being preferred by<br> practitioners, in order to support the evolution of SPLs.</p>
Replication Data for "Mapping the Structure and Evolution of Software Testing Research Over the Past Three Decades"
<p>In this research (publication included in the package), we have used author-assigned keywords as a quantitative data source for understanding the connections between keywords and research topics in software testing research, based on a large sample of studies from Scopus.</p> <p>We apply co-word analysis to map the topology of testing research as a network where author-assigned keywords are connected by edges indicating co-occurrence in publications. Keywords are clustered based on edge density and frequency of connection. We examine the most popular keywords, summarize clusters into high-level research topics, examine how topics connect, and examine how the field is changing. This package contains the map and network files used to perform our analyses, as well as the publication sample.</p>
Replication package for "Evolution of statistical analysis in empirical software engineering research: Current state and steps forward"
<p>This is the replication package for the analysis done in the paper "Evolution of statistical analysis in empirical software engineering research: Current state and steps forward" (DOI: <a href="https://doi.org/10.1016/j.jss.2019.07.002">https://doi.org/10.1016/j.jss.2019.07.002</a>, preprint: <a href="https://arxiv.org/abs/1706.00933">https://arxiv.org/abs/1706.00933</a>).</p> <p>The package includes CSV files with data on statistical usage extracted from 5 journals in SE (EMSE, IST, JSS, TOSEM, TSE). The data was extracted from papers between 2001 - 2015. The package also contains forms, scripts and figures (generated using the scripts) used in the paper.</p> <p>The extraction tool mentioned in the paper is available in dockerhub via: <a href="https://hub.docker.com/r/robertfeldt/sept">https://hub.docker.com/r/robertfeldt/sept</a></p>
Ergebnisse der Evaluation für die Bachelorarbeit "Instrumentierung von Testklassen zur Analyse von Software-Evolution"
<p>Dieses Dataset beinhaltet die rohen Ergebnisse der Evaluation für die Bachelorarbeit "Instrumentierung von Testklassen zur Analyse von Software-Evolution". Dabei betrachten wir die Fehler der Instrumentierung, die zusammengefassten Daten und die Veränderungen der gesetzten visuellen Merkmale für zwei verschiedene Softwareprojekte (Petclinic und Spring-Kafka).</p>
Software Evolution and Quality Data from Controlled, Multiple, Industrial Case Studies
<p>This data was obtained from a controlled, multiple case study involving six professional developers and four real-life, industrial systems. The study was designed to control for the moderator factors: programmer skill, maintenance task and learning effect. The primary data set contains multiple sets of defects, in the form of reports (excel files) extracted from six issue tracking systems. The secondary data consists of a series of attributes extracted from the software systems (i.e., code smells) and their evolution (i.e., code churn), and a log specifying the dates on which developers worked on each of the systems/tasks, in the form of excel files. Details on the controlled, multiple case study can be found in the doctoral dissertation by Yamashita titled: "Assessing the Capability of Code Smells to Support Software Maintainability Assessments: Empirical Inquiry and Methodological Approach" (online) Available at: https://www.duo.uio.no/handle/10852/34525</p>
Replication Package for "An Empirical Comparison of Dependency Network Evolution in Seven Software Packaging Ecosystems"
<p>This is the replication package for the article "An Empirical Comparison of Dependency Network Evolution in Seven Software Packaging Ecosystems" published in the Empirical Software Engineering journal.</p> <p>This package requires Python 3.5 and all the dependencies that are listed in "requirements.txt".<br> The notebooks (in "notebooks" folder) should be opened and executed with Jupyter.</p> <p>The notebooks require the graphs (in "graphs" folder) to be computed first. To do so, execute "helpers.py" with Python.<br> The graphs are built using the data provided by https://libraries.io under CC BY-SA<br> https://creativecommons.org/licenses/by-sa/4.0/<br> Those data can be found in the "data" folder.</p> <p> </p>
Performance Evolution Matrix: Visualizing Performance Variations along Software Versions
<p># Performance Evolution Matrix<br> This repository contains the artifacts needed to replicate our experiment in the paper "Performance Evolution Matrix".</p> <p># Video Demo<br> [download](https://github.com/jpsandoval/PerfEvoMatrix/blob/master/MatrixMovie.mp4)<br> <br> # XMLSupport and GraphET Examples</p> <p>To open the XMLSupport and GraphET Examples (which appears in the paper) execute the following commands in a Terminal.</p> <p>**MacOSX.** We do all the experiments in a Mac Book Pro. To open the Matrix execute the following command in the folder where this project was downloaded. </p> <p>```<br> ./Pharo-OSX/Pharo.app/Contents/MacOS/Pharo Matrix.image<br> ```</p> <p>**Windows.**<br> You may also run the experiment in Windows, but depending on the windows version you have installed it may be some some UI bugs.<br> ```<br> cd Pharo-Windows<br> Pharo.exe ../XMLSupportExample.image<br> ```</p> <p>**Open the Visualization.**<br> Please select the following code, then execute it using the green play button (at the top right of the window).<br> ```<br> ToadBuilder xmlSupportExample.<br> ```<br> or <br> ```<br> ToadBuilder graphETExample.<br> ```<br> **Note.** There are two buttons at the panel top left In (zoom in) and Out (zoom out). To move the visualization just drag the moves over the panel.</p> <p># Experiment<br> This subsection describe how to execute the tools, for replicating our experiment.</p> <p>## Baseline<br> The baseline contains the tools and the project-dataset to realize the tasks described in the paper (identifying and understanding performance variations).</p> <p>## Open the Baseline</p> <p>**MacOSX.** We do all the experiments in a Mac Book Pro. To open the Baseline execute the following command in the folder where this project was downloaded. </p> <p>```<br> ./Pharo-OSX/Pharo.app/Contents/MacOS/Pharo Baseline.image<br> ```</p> <p>**Windows.**<br> You may also run the experiment in Windows, but depending on the windows version you have installed it may be some some UI bugs.<br> ```<br> cd Pharo-Windows<br> Pharo.exe ../Baseline.image<br> ```</p> <p>## Open a Project</p> <p>There are three projects under study, depending on the project you wanna use for the task, you may execute one of the following scripts. For executing a script press Cmd-d or right-click and press do it.</p> <p>**Roassal**<br> ```<br> TProfileVersion openRoassal.<br> ```</p> <p>**XML**<br> ```<br> TProfileVersion openXML.<br> ```<br> **Grapher**<br> ```<br> TProfileVersion openGrapher.<br> ```</p> <p>## Baseline Options<br> For each project, we provide a UI which contains all the tools we use as a baseline. Each item in the list is a version of the selected project.</p> <p><img src="images/baseline.png" width="300"></p> <p>- Browse: open a standard window to inspect the code of the project in the selected version.<br> - Profile: open a window with a call context tree for the selected version.<br> - Source Diff: open a window with the code differences between the selected version and the previous one.<br> - Execution Diff: open a window with the merge call context tree gathered from the selected version and the previous one. </p> <p>**Note.** All these options require you select first a item in the list.</p> <p># Matrix</p> <p>## Open Matrix Image.</p> <p>**MacOSX.** We do all the experiments in a Mac Book Pro. To open the Matrix execute the following command in the folder where this project was downloaded. </p> <p>```<br> ./Pharo-OSX/Pharo.app/Contents/MacOS/Pharo Matrix.image<br> ```</p> <p>**Windows.**<br> You may also run the experiment in Windows, but depending on the windows version you have installed it may be some some UI bugs.<br> ```<br> cd Pharo-Windows<br> Pharo.exe ../Matrix.image<br> ```</p> <p>## Open a project</p> <p>There are three projects under study, depending on the project you wanna use for the task, you may execute one of the following scripts. For executing a script press Cmd-d or right-click and press do it.</p> <p>**Roassal**<br> ```<br> ToadBuilder roassal.<br> ```</p> <p>**XML**<br> ```<br> ToadBuilder xml.<br> ```<br> **Grapher**<br> ```<br> ToadBuilder grapher.<br> ```</p> <p># Data Gathering</p> <p>Before each participant starts a task we execute the following script in Smalltalk. For executing a script press Cmd-d or right-click and press do it. It allows us to track the time that a user starts the experiment and how many mouse clicks, movements.<br> ```<br> UProfiler newSession.<br> UProfiler current start.<br> ```</p> <p>After finishing the task we executed the following script. It stop recording the mouse events and save the stops time.<br> ```<br> UProfiler current end.<br> ```</p> <p>The last script generates a file with the following information: start time, end time, number of clicks, number of mouse movements, and the number of mouse drags (we do not use this last one).<br> ```<br> 11:34:52.5205 am,11:34:56.38016 am,14,75,0</p> <p>```<br> # Quit<br> To close the artifact, just close the window or press click in any free space of the window and select quit.</p>
Supplementary Material to SBIE 2024:Achieving Project Management Educational Web-Tool Evolution Using Service-based Software
Open the record for dataset details and reuse information.
Comparing the Intensity of Variability Changes in Software Product Line Evolution - Related Research Artifacts
<p>This archived open repository contains open science material related to the following submission to the <a href="https://www.journals.elsevier.com/journal-of-systems-and-software/call-for-papers/software-reuse-for-the-next-generation">Journal of Systems and Software (JSS) special issue <em>Software Reuse for the Next Generation</em></a>:</p> <p>C. Kröher, L. Gerling, K. Schmid, <em>Comparing the intensity of variability changes in software product line evolution</em>, Journal of Systems and Software. Submitted November 2022.</p> <p>The paper presents the application of a fine-grained, variability-centric analysis approach to four different software product lines: <a href="https://github.com/torvalds/linux">Linux kernel</a>, <a href="https://github.com/coreboot/coreboot">coreboot firmware</a>, <a href="https://github.com/mirror/busybox">BusyBox UNIX utilities</a>, and <a href="https://sourceforge.net/projects/axtls/">axTLS embedded SSL</a>. The approach is based on the differentiation between artifact-specific and variability information in code, build, and variability model artifacts to identify the intensity (the frequency and the amount) with which developers change variability information in practice.</p> <p>In order to complement the results presented in the submission and support reproducibility as well as reuse, the following artifacts are available:</p> <ul> <li><strong>JSS-VM_2022-11-01.zip</strong>: a compressed archive containing the virtual machine in which the analysis was executed. This virtual machine was created with <a href="https://www.vmware.com/content/vmware/vmware-published-sites/us/products/workstation-player/workstation-player-evaluation.html.html">VMware Workstation 16 Player</a> based on <a href="https://ubuntu.com/download/desktop">Ubuntu Desktop 22.04.1</a> (username and password: jss). It provides all installed software, configuration files, data sets, and results as described in the submission. Download, extract, and start the virtual machine to access the detailed description of its content and usage on the desktop.</li> <li><strong>ComAnI-Applications.zip</strong>: a compressed archive containing the technical realization of the analysis approach and the configuration files used to apply it to the individual software product lines. This includes: <ul> <li><em>ComAnI_Guide.pdf</em>: the guide explaining the application and its usage in general</li> <li><em>ComAnI.jar</em>: the Java executable archive file representing the main application for starting an analysis</li> <li><em>ComAnI-PS.jar</em>: a modified version of the previous Java executable archive file, which provides the number of code, build, and variability model artifacts as specified by the regular expressions of a given configuration file as well as their total number of lines based on the current state of a repository only (no history)</li> <li><em>DeadCodeChangeAnalyzer.jar</em>: a commit analyzer plug-in for detecting changes relevant to dead code detection (not used in the submission)</li> <li><em>GitCommitExtractor.jar</em>: a commit extraction plug-in for extracting commits from Git repositories</li> <li><em>SvnCommitExtractor.jar</em>: a commit extraction plug-in for extracting commits from Subversion (SVN) repositories</li> <li><em>VariabilityChangeAnalyzer.jar</em>: a commit analyzer plug-in for detecting changes to artifact-specific and variability information in code, build, and variability model artifacts (realization of the commit analysis process described in the submission)</li> <li><em>busybox-commit-list</em>: a plain text file containing a subset of the BusyBox commits as required by the application to extract and analyze only those parts of its entire history relevant for the submission (quote from the submission: <em>"For BusyBox, we had to further exclude commits before the complete migration to Kbuild and after the introduction of a script for extracting variability model information from code artifacts, which initiated defining variability information of the variability model as part of comments in code artifacts. This mixing of information and artifact types is not supported by our tooling"</em>)</li> <li><em>axtls.properties</em>: the configuration (file) defining the required properties for extracting and analyzing commits of the axTLS history</li> <li><em>busybox.properties</em>: the configuration (file) defining the required properties for extracting and analyzing all commits of the BusyBox history</li> <li><em>busybox-subset.properties</em>: the configuration (file) defining the required properties for extracting and analyzing the commits specified in the busybox-commit-list file only, resulting in the respective subset of the BusyBox history</li> <li><em>coreboot.properties</em>: the configuration (file) defining the required properties for extracting and analyzing all commits of the coreboot history</li> <li><em>linux.properties</em>: the configuration (file) defining the required properties for extracting and analyzing all commits of the Linux kernel history</li> <li><em>template.properties</em>: the configuration (file) template including descriptions of each property and its valid values</li> </ul> </li> <li><strong>ComAnI-Results.zip</strong>: a compressed archive containing the (raw) analysis results from applying the approach via its realization as provided by the previous archive to each of the software product lines. Hence, for each subject, a directory with the respective name exist, which in turn contains the following artifacts: <ul> <li><em>VariabilityChangeAnalyzer-Results_2022-09-[…]</em>: the directory containing the respective analysis results and some automated visualizations. Please note that some files are not correctly labeled, .e.g. some files for axTLS and BusyBox are prefixed with "coreboot", while containing the correct data for the respective subjects. Further, for BusyBox, two directories exist, which the additional readme-file explains</li> <li><em>project-size-trace.txt</em>: the complete trace from starting ComAnI-PS.jar (see description above) with a specific configuration file to its final output</li> </ul> </li> <li><strong>JSS23_Extended-Evolution-Analysis_Statistics.ods</strong>: a <a href="https://www.libreoffice.org/discover/calc/">LibreOffice Calc</a> spreadsheet containing data derived from the raw ones of the ComAnI-Results.zip and the respective visualizations as presented in the submission. Further, some sheets include additional data preparations used to write certain parts of the result and discussion sections.</li> </ul> <p>The additional <strong>LICENSE</strong> file defines <a href="https://www.apache.org/licenses/LICENSE-2.0">Apache License Version 2.0, January 2004</a> to apply for all artifacts in this repository.</p> <p>This work is partially supported by the Evoline project, funded by the DFG (German Research Foundation) under Priority Programme SPP 1593 and by the ITEA3 project REVaMP², funded by the BMBF (German Ministry of Research and Education) under grant 01IS16042H. Any opinions expressed herein are solely by the authors and not of the DFG or BMBF.</p>
Evolution of Teamwork Quality Instruments in Agile Software Development: A Systematic Literature Review
<p>Suplemmentary Material of the article: Evolution of Teamwork Quality Instruments in Agile Software Development: A Systematic Literature Review</p>
Towards Identifying Python Proficiency to Foster Software Maintenance and Evolution
Open the record for dataset details and reuse information.
Artfiact for the Proc. ACM Softw. Eng. article "Sharing Software-Evolution Datasets: Practices, Challenges, and Recommendations."
<p>This dataset is a collection of all notes taken for the article:</p> <p> David Broneske, Sebastian Kittan, and Jacob Krüger:<br> Sharing Software-Evolution Datasets: Practices, Challenges, and Recommendations. <br> Proc. ACM Softw. Eng. 1, FSE, 2024.<br> https://doi.org/10.1145/3660798</p> <p>Please refer to the readme for a description of the files involved in the zip file.</p>
Architectural Feature Re-Modularization for Software Product Line Evolution
<p>Extensive maintenance leads to the Software Product Line Architecture<br> (PLA) degradation over time. When there is the need of<br> evolving the Software Product Line (SPL) to include new features,<br> or move to a new platform, a degraded PLA requires considerable<br> effort to understand and modify, demanding expensive refactoring<br> activity. In the state of the art, search-based algorithms are used to<br> improve PLA at package level. However, recent studies have shown<br> that the most variability and implementation details of an SPL are<br> described in the level of classes. There is a gap between existing<br> approaches and existing practical needs. In this work, we extend<br> the current state of the art to deal with feature modularization in<br> the level of classes by introducing a new search operator and a set<br> of objective functions to deal with feature modularization in a finer<br> granularity of the architectural elements, namely at class level. We<br> evaluated the proposal in an exploratory study with a PLA widely<br> investigated and a real-world PLA. The results of quantitative and<br> qualitative analysis point out that our proposal provides solutions<br> to properly re-modularize features in a PLA, being preferred by<br> practitioners, in order to support the evolution of SPLs.</p>
Data for: Continuous API Evolution in Heterogenous Enterprise Software Systems
<p>The ability to independently deploy parts of a software system is one of the cornerstones of modern software development, and allows for these parts to evolve independently and at different speeds.</p> <p>A major challenge of such independent deployment, however, is to ensure that despite their individual evolution, the interfaces between interacting parts remain compatible. This is especially important for enterprise software systems, which are often highly integrated and based on heterogenous IT infrastructures.</p> <p>Although several approaches for interface evolution have been proposed, many of these rely on the developer to adhere to certain rules, but provide little guidance for doing so. In this paper, we present an approach for interface evolution that is easy to use for developers, and also addresses typical challenges of heterogenous enterprise software, especially legacy system integration.</p> <p>This dataset contains the questions and results from the survey among developers to roughly assess the applicability of the approach in practice.</p>
Data and R Code from "PAT-GEOM: A Software Package for the Analysis of Animal Patterns" (published in Methods in Ecology and Evolution)
<p>Datasets for Figures 2 and 4 in the article "PAT-GEOM: A Software Package for the Analysis of Animal Patterns" (published in Methods in Ecology and Evolution) and the R code used to perform the analysis described in the article.</p>
The Impact of Microservices on the Evolution of a Software Product Line
<p>Video apresentação artigo The Impact of Microservices on the Evolution of a Software Product Line</p>
REGISTRY for the Use of a Software for Automatic Detection of the Evolution of Aneurysmal Volume and Graft Migration After EVAR (EndoVascular Aneurysm Repair)
ClinicalTrials.gov study NCT05964348. IPD Sharing: Not stated. Countries: 1. Publications: 0.
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