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28 results for “Software Product Lines”
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>
A Hybrid Feature Location Technique for Re-engineering Single Systems into Software Product Lines
<p>The dataset used for evaluating the hybrid feature location technique presented in the paper: "A Hybrid Feature Location Technique for Re-engineering Single Systems into Software Product Lines". This enables reproducibility, evaluation, and comparison of our study.</p> <p>_________________________________________________________________________________________________________</p> <p>Folder "Dataset" contains for each subject system used:</p> <p>(i) the artificial variants and their configurations;</p> <p>(ii) the ECCO repository containing the traces;</p> <p>(iii) the ground truth and composed variants;</p> <p>(iv) the metrics results.</p> <p>_________________________________________________________________________________________________________</p> <p>Folder "Scenarios" contains for each subject system used:</p> <p>(i) the videos recorded from exercising features on GUI.</p>
Software Product Line Traceability and Product Configuration in Class and Sequence Diagrams: an Empirical Study
<p>Software Product Line Traceability and Product Configuration in Class and Sequence Diagrams: an Empirical Study</p>
Software Product Line Configuration and Traceability: an Empirical Study on SMarty Class and Component Diagrams
<p>Software Product Line Configuration and Traceability: an Empirical Study on SMarty Class and Component Diagrams</p>
Tool Artifact for "Mutation-based Lifted Repair of Software Product Lines"
<p>In this work, we describe the installation, usage, and evaluation results of the tool SPLAllRepair introduced by the paper<br>``Mutation-based Lifted Repair of Software Product Lines''. We provide step-by-step instructions on how to download, run, and compare the tool's outputs to outputs described in the paper. The tool implements a novel lifted repair algorithm for program families (Software Product Lines - SPLs) based on code mutations. The inputs of our algorithm are an erroneous SPL and a specification given in the form of assertions. We use variability encoding to transform the given SPL into a single program, called family simulator, which is translated into a set of SMT formulas whose conjunction is satisfiable iff the simulator (i.e. the input SPL) violates an assertion. We use a predefined set of mutations applied to feature and program expressions of the given SPL.<br>The algorithm repeatedly mutates the erroneous family simulator and checks if it becomes (bounded) correct. The outputs are all minimal repairs in the form of minimal number of (feature and program) expression replacements such that the repaired SPL is (bounded) correct with respect to a given set of assertions. We present the experimental results showing that our approach is able to successfully repair various interesting #ifdef-based C SPLs.</p>
Reuse of Model Transformations for Propagating Variability Annotations in Annotative Software Product Lines - Evaluation Data
<p>This package contains all data that was produced for and used in the doctoral thesis for evaluating commutativity of propagating annotations in model-driven product lines.<br> This includes the implementation that conducts the evaluation, the measured results, and the input subjects.</p>
Achieving Energy Efficiency with a Software Product Line Engineering Approach
<p>This is a Live PhD. Thesis Presentation; Also playable at:</p><p><a href="https://youtu.be/yaYEoj4S3pc">https://youtu.be/yaYEoj4S3pc</a></p><p>Please access and cite the published PhD. Thesis book: <a href="https://doi.org/10.5281/zenodo.10007921 ">https://doi.org/10.5281/zenodo.10007921 </a></p><ul><li><strong>Author</strong>: Daniel-Jesus Munoz</li><li><strong>Directors</strong>: Lidia Fuentes and Monica Pinto.</li></ul><p>CAOSD group, Universidad de Málaga, Andalucía Tech, Spain </p><p>Post-defense presentation recorded at Universität Ulm in 2023.</p><p>Energy-aware software design can energy-aware software design can reduce total energy consumption by 30-90%. However, the different ways of measuring energy consumption in real time are very complex. Energy readings are provided as the total energy consumption in joules or the rate of energy consumption in watts. For battery-powered battery-powered devices, joules per task is a more interesting metric, while watts per task is more commonly used for battery-powered devices. per task is more used for devices directly connected to power. The usual approach to modelling and storing approach to modelling and storing power consumption readings is to describe them as a characteristic of individual components, such as monetary cost. individual components, such as the monetary cost of a hardware component. However, the energy consumption values have many interactions between components, which makes it difficult to describe them with individual, static energy values. This makes it difficult to describe them in terms of individual, static energy values. Instead, we can store and energy information can be stored and populated in collaborative databases. The IEA and Datarade offer free databases with energy consumption data. free databases with energy consumption data for energy efficiency and sustainability analysis. Without However, the databases are not scalable for highly configurable systems because of the curse of the dimension. Our work focuses on Industry 4.0, specifically on Cyber-Physical Systems (acronym CPS), which are characterised by their high configurability and adaptability, presenting a large number of alternatives and a colossal number of alternatives and a colossal number of different systems in operation. This is known as the This is known as the search/solution space, the size of which is the set of all possible points that satisfy an optimisation problem. optimisation problem. Partially known solution spaces are a common problem in many fields, such as computer engineering, machine learning, artificial intelligence and goal-oriented optimisation. engineering, machine learning, artificial intelligence and goal-oriented optimisation. The Constraint Satisfaction Problems (CSP) are mathematical problems defined as a set of objects whose state must satisfy a set of constraints. set of objects whose state must satisfy a set of constraints. Variability Models (acronym VMs) are tree-like structures used to represent the commonalities and differences of a CPS. Numerical Features (NFs) can be used in VMs to represent quantitative properties of the system, but they can be used to represent quantitative properties of the system, but most tools do not support NFs. In addition, NFs increase the size of the VM, NFs increase the size of the solution space by multiplying it by its domain size, which makes large solution spaces colossal. large solution spaces into colossal ones. Quality Models (QMs) are tree structures that are used to determine which Quality Attributes (QAs) such as energy efficiency are to be taken into account when evaluating a project. which Quality Attributes (QAs) such as energy efficiency are to be taken into account when evaluating a system. system. ISO/IEC 25010 is the most popular QM formalisation, which groups QAs into eight different types. The Automated reasoning is the automation of formal logical reasoning to compute different types of information about system models. Examples are providing a VM or QM to a reasoning tool, and calculating the size of the reasoning tool, and calculating the size of the solution space, checking the satisfiability of the model, or generating only optimal systems based on objective functions. only optimal systems based on objective functions based on one or more QAs. This thesis aims to find a native modelling and reasoning approach for a unified Quality and Variability Model (QVM). Variability and Quality Model (QVM). The aim is to develop an approach that supports modelling and reasoning for the reasoning oriented optimisation of numerical characteristics, an algebraic framework for unified QVMs, an online eco-assistant for optimising a user-constrained solution space measured for quality, and an algorithm and an online quality, and an algorithm and a web tool for learning the influences of energy and characteristics of user-constrained, domain-unknown and partially measured solution spaces.</p>
Evaluating usefulness, ease of use and usability of an UML-based Software Product Line Tool
<p>Vídeo de apresentação do artigo "Evaluating usefulness, ease of use and usability of an UML-based Software Product Line Tool" para o 34° Simpósio Brasileiro de Engenharia de Software (SBES'20), 21-23 de Outubro de 2020, Natal, RN, Brasil. Autores: Leandro F. da Silva e Edson OliveiraJr.</p>
dataset of SMartyPerspective: a perspective-based inspection technique for software product lines
<p>dataset of SMartyPerspective: a perspective-based inspection technique for software product lines</p>
Artifact for the paper "Mutation-based Lifted Repair of Software Product Lines"
<p>This work presents a novel lifted repair algorithm for program families (Software Product Lines - SPLs) based on code mutations.<br>The inputs of our tool are an erroneous SPL and a specification given in the form of assertions. We use variability encoding to transform the given SPL into a single program, called family simulator, which is translated into a set of SMT formulas whose conjunction is satisfiable iff the simulator (i.e. the input SPL) violates an assertion. We use a predefined set of mutations applied to feature and program expressions of the given SPL. The tool repeatedly mutates the erroneous family simulator and checks if it becomes (bounded) correct. The outputs of our tool are all minimal repairs in the form of minimal number of (feature and program) expression replacements such that the repaired SPL is (bounded) correct with respect to a given set of assertions.</p> <p>We present a prototype tool for repairing #ifdef-based C programs (i.e., annotative SPLs). The experimental results show that our approach is able to successfully repair various interesting SPLs.</p>
SimRE: A Requirements Similarity Tool for Software Product Lines - Dataset
<p>The <strong>RequirementsPairs</strong> file consists of 34 pairs of software requirements related to GIS (Geographic Information Systems), each paired with a corresponding similarity degree. It was introduced in the paper <em>"SimRE: A Requirements Similarity Tool for Software Product Lines."</em></p> <p><strong>GISv1</strong> and <strong>GISv2</strong> refer to version 1 and version 2 of the GIS dataset, respectively. These datasets are composed of 173 requirements that represent the functionality of a web-based GIS product line.</p>
A Systematic Mapping Study on Software Product Line Experiments
<p>Available data regarding a A Systematic Mapping Study on Software Product Line Experiments</p>
Data for a Systematic Literature Review of Lifted Software Product Line Analyses
<p>This artifact contains data pertaining to a systematic literature review for lifted analyses of software product lines.</p>
Open-Source Software Product Line Extraction Processes: the ArgoUML-SPL and Phaser Cases
<p>Collection of datasets and analysis scripts supporting the information provided in the text.</p> <p>There are two compressed files, one for the ArgoUML data and one for the Phaser data. Each compressed file contains a README describing important information.</p>
Leveraging Relational Concept Analysis for Automated Feature Location in Software Product Lines - Artefacts DataSet
<p>This Archive contains the Artefact of the paper, submitted at GPCE2021 :<br> <a href="https://doi.org/10.1145/3486609.3487208">Leveraging Relational Concept Analysis for Automated Feature Location in Software Product Lines</a></p> <p> </p> <p>It contains the dataset and the results of our Feature Location techniques when applied to this dataset.</p>
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>
Guidelines for Software Product Line Experiments: SMS extracted data and guidelines evaluation
<p>Guidelines for Softwrae Product Line Experiments: SMS extracted data and guidelines evaluation</p>
Complementary materials for: Looking For Novelty in Search-based Software Product Line Testing (TSE)
<p>In this repository, we provide complementary materials for the following paper: </p> <pre>Y. Xiang, H. Huang, M. Li, S. Li and X. Yang, "Looking For Novelty in Search-based Software Product Line Testing" in <em>IEEE Transactions on Software Engineering</em>, vol. , no. 01, pp. 1-1, 5555. doi: 10.1109/TSE.2021.3057853 url: https://doi.ieeecomputersociety.org/10.1109/TSE.2021.3057853</pre> <p>1. Correlation analysis results (Pearson'r and p-value) are tabulated in <a href="https://www.zenodo.org/api/files/f6451296-91dc-4c9c-89fc-28ebf315be10/CorrelationAnalysisResults.xlsx?versionId=2f4ec2ab-3e48-420d-9819-b5e60ea43c06">CorrelationAnalysisResults.xlsx</a>; </p> <p>2. MATLAB scripts and raw data, which were used to perform correlation analyses, are given in <a href="https://zenodo.org/api/files/f6451296-91dc-4c9c-89fc-28ebf315be10/RawDataForCorrelationAnalysis.rar?versionId=5a168e2e-df32-4773-b8f3-4bf49de8d01d">RawDataForCorrelationAnalysis.rar</a>. </p> <p>---------------------------------------------------------------------------------------------------------------------------------------</p> <p>We suggest reproducing the correlation analysis, and other experiments described in the paper, using the codes provided at Github: <a href="https://github.com/gzhuxiangyi/TSE_NS">https://github.com/gzhuxiangyi/TSE_NS </a></p> <p> </p>
Software Product Line Testing: A Systematic Literature Review Datasheets
<p>Software Product Line Testing: A Systematic Literature Review Dataset</p>
Online Supplement: Search-based Diverse Sampling from Real-world Software Product Lines
<p>This is the online supplement for the following paper: Yi Xiang, Han Huang, Yuren Zhou, Sizhe Li, Chuan Luo, Qingwei Lin, Miqing Li, and Xiaowei Yang. 2022. Search-based Diverse Sampling from Real-world Software Product Lines. In 44th International Conference on Software Engineering (ICSE’22), May 21-29, 2022, Pittsburgh, PA, USA. ACM, New York, NY, USA, 13 pages. https://doi.org/10.1145/3510003.3510053</p>
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