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25 results for “Software Industry”
Software Engineering Education Knowledge versus Industrial Needs
<p>Dataset of the research paper: <strong>Software Engineering Education Knowledge versus Industrial Needs</strong></p> <p><em>Contribution</em>: Determine and analyze the gap between software practitioners’ education outlined in the 2014 IEEE/ACM Software Engineering Education Knowledge (SEEK) and industrial needs pointed by Wikipedia articles referenced in Stack Overflow (SO) posts.<br> <em>Background</em>: Previous work has uncovered deficiencies in the coverage of computer fundamentals, people skills, software processes, and human-computer interaction, suggesting rebalancing.<br> <em>Research Questions</em>: 1) To what extent are developers’ needs, in terms of Wikipedia articles referenced in SO posts, covered by the SEEK knowledge units? 2) How does the popularity of Wikipedia articles relate to their SEEK coverage? 3) What areas of computing knowledge can be better covered by the SEEK knowledge units? 4) Why are Wikipedia articles covered by the SEEK knowledge units cited on SO?<br> <em>Methodology</em>: Wikipedia articles were systematically collected from SO posts. The most cited were manually mapped to the SEEK knowledge units, assessed according to their degree of coverage. Articles insufficiently covered by the SEEK were classified by hand using the 2012 ACM Computing Classification System. A sample of posts referencing sufficiently covered articles was manually analyzed. A survey was conducted on software practitioners to validate the study findings.<br> <em>Findings</em>: SEEK appears to cover sufficiently computer science fundamentals, software design and mathematical concepts, but less so areas like the World Wide Web, software engineering components, and computer graphics. Developers seek advice, best practices and explanations about software topics, and code review assistance. Future SEEK models and the computing education could dive deeper in information systems, design, testing, security, and soft skills.</p> <p>The following data files are included.</p> <ul> <li><strong>wikipedia_articles.csv</strong>: Wikipedia articles mapped to the knowledge units of the 2014 IEEE/ACM Software Engineering Education Knowledge (SEEK) and the first and second level categories of the 2012 ACM Computing Classification System (CCS).</li> <li> <p><strong>posts_analysis.csv</strong>: Stack Overflow post data and metadata.</p> </li> <li> <p><strong>posts_aggregated_codes.csv</strong>: The aggregated codes that resulted from the manual analysis of the Stack Overflow posts by grouping individual keywords assigned to the posts.</p> </li> <li> <p><strong>survey_questionnaire.csv</strong>: The final survey questionnaire.</p> </li> <li> <p><strong>survey_responses.csv</strong>: Anonymized responses of the final survey questionnaire. (E-mail addresses have been excluded for privacy reasons.)</p> </li> </ul>
Data for: Drivers and Barriers for Microservice Adoption in the German Software Industry
<p>Microservices are an architectural style for software which currently receives a lot of attention in both industry and academia. Several companies employ microservice architectures with great success, and there is a wealth of blog posts praising their advantages. Especially so-called Internet-scale systems use them to satisfy their enormous scalability requirements and to rapidly deliver new features to their users.<br> However, microservices are not only popular with large, Internet-scale systems. Many traditional companies are also considering whether microservices are a viable option for their applications. However, these companies may have other motivations to employ microservices, and see other barriers which may prevent them from adopting microservices. Furthermore, these drivers and barriers may differ among industry sectors.<br> This dataset contains the questions and results of a survey on drivers and barriers for microservice adoption among professionals in the German software industry. In addition to overall drivers and barriers, we particularly focused on the use of microservices to modernize existing software, with special emphasis on implications for runtime performance and transactionality.</p>
Figure 1. Visual and synthetic representation of the modelling process in the software industry-The Fundamentals Regarding the Usage of the Concept of Interface for the Modeling of the Software Artefacts
<p>The experience that is accumulated regarding the modelling paradigms in the software engineering is impressive. Thus, the software engineering recognizes modelling paradigms like object orientation, aspect orientation, component orientation, service orientation, agent orientation. In one form or another, these paradigms prove their ex- cellence in certain types of IT projects. At the same time, these paradigms reveal their objective limits when they are used to engineer the real world software systems. Every modelling paradigm represents, in fact, a modality to represent the real world using a specific formal framework. The specificity of the formal framework is defined from both a syntactic and semantic perspective. The formal syntactic framework of a paradigm refers to the concepts that are used by the paradigm in order to represent the real world, but also to the recommended principles that allow for these concepts to interact in a correct and efficient manner. Both the concepts and the principles benefit from a formal representation that ultimately favours communication as a secondary modelling lever inside the IT projects. Every syntactic artefact of a paradigm can be associated with a certain real world semantics, which it abstracts. As a consequence, considering that the real world continuously enhances its semantic potential, the syntactic constructs that are favoured by the paradigm may become problematic.</p>
Data Set Used in Combinatorial Modeling and Test Case Generation for Industrial Control Software using ACTS
<p>This document contains the data set used for the study Combinatorial Modeling and Test Case Generation for Industrial Control Software using ACTS that is currently in submission.</p>
Survey and Interview Data from Mixed-Method Survey of Serverless Computing and Function-as-a-Service Software Development in Industrial Practice
<p>This dataset contains the almost-raw data resulting from two out of the three methods chosen by the researchers for their namesake study «A Mixed-Method Empirical Study of Function-as-a-Service Software Development in Industrial Practice». Among the files are web survey questions, anonymised survey results, and interview guidelines. We encourage other researchers to perform open coding and other analysis techniques on the data to verify our claims and to generate new insights.</p>
Software Variability Tools: Industrial Survey and Systematic Mapping Study
<p>Software Variability Tools: Industrial Survey and Systematic Mapping Study</p>
Replication Package for a Systematic Literature Mapping of Agility in Safety-Critical Software Development within the Aerospace Industry
<p>This file collection package facilitates the replication of a Systematic Literature Mapping (SLM) focused on Agility in Safety-Critical Software Development within the Aerospace Industry. Authored by J. Eduardo Ferreira Ribeiro, João Gabriel Silva, and Ademar Aguiar, this dataset is dedicated to improving transparency and reproducibility in this field of study and future research.</p> <p>Specifically, the package includes:</p> <ul> <li><a href="https://github.com/zemacedo99/Replication-Package-Builder/releases/tag/v1.0.2">Replication Package Builder Version 1.0.2</a></li> <li>A list of terms (both inclusion and exclusion) used to construct the research string.</li> <li>A list of venues unrelated to the research topic, to be excluded from the results.</li> <li>The inclusion and exclusion criteria applied during the study.</li> <li>Lists of publication results from indexing services like Scopus, IEEE Xplore, Science Direct, HAL Open Science, Springer Nature, and the ACM Digital Library are all provided in CSV file format.</li> <li>A list of all publications in CSV format, compiled after the automated exclusion phase using the established inclusion and exclusion criteria.</li> <li>Finally, a complete list of all publications, including those from Snowball sampling, in XLSX format was compiled after the manual exclusion phase using the established inclusion and exclusion criteria.</li> </ul> <p>Compiled and published on Saturday, September 14, 2024, this dataset is crucial for researchers seeking to replicate or extend the SLM's findings.</p> <p>Lastly, we thank J. Antonio Dantas Macedo for contributing to developing and providing this <a href="https://github.com/zemacedo99/Replication-Package-Builder">replication package builder</a>.</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>
Software Development Waste amidst COVID-19 Pandemic: An Industry Study
<p>The dataset is to support the publication "Software Development Waste amidst COVID-19 Pandemic: An Industry Study" in ISEC 2024. </p>
Study Data: Semi-Automated Prioritization of Industrial Security Findings in Agile Software Development
<p>Dataset for the study of the paper "Semi-Automated Prioritization of Industrial Security Findings in Agile Software Development"</p>
Agile Minds, Innovative Solutions, and Industry–Academia Collaboration: Lean R&D Meets Problem-based Learning in Software Engineering Education
<p>Supplementary materials of the paper "Agile Minds, Innovative Solutions, and Industry–Academia Collaboration: Lean R&D Meets Problem-based Learning in Software Engineering Education"</p>
Survey Data for "Software Testing: Survey of the Industry Practices"
<p>Dataset for the surveys presented in our article "Software Testing: Survey of the Industry Practices."</p>
Which RESTful API Design Rules are Important and How Do They Improve Software Quality? A Delphi Study with Industry Experts
<p>The dataset of a Delphi study with 8 industry experts who reached consensus on the perceived importance and positive software quality impact of 82 RESTful API design rules from the catalogue by Mark Massé ("REST API Design Rulebook", O’Reilly Media, 2011). The replication package contains:</p> <ul> <li><strong>rules.csv:</strong> the final consensus results for the 82 rules in CSV format</li> <li><strong>rule-importance.xlsx</strong>: the detailed results and analysis for rule importance as an Excel spreadsheet</li> <li><strong>rule-sw-quality-impact.xlsx</strong>: the detailed results and analysis for rule impact on software quality as an Excel spreadsheet</li> </ul> <p>In this version, we updated the final numbers for the software quality mapping with the results from the synchronous meeting.</p>
Systematic Comparison of Software Agents and Digital Twins: Differences, Similarities, and Synergies in Industrial Production: A Dataset
<p>Supplementary dataset containing extrated information regarding the capabilites, properties, purposes, and axes of RAMI 4.0 of Agents and Digital Twins.</p>
Supplementary Material for the paper entitled The maternity challenges in the software industry and academia: a survey with mothers from the Software Engineering field
Open the record for dataset details and reuse information.
Material Suplementar - Is secure software development education necessary in the software industry? Answers from professionals of a technology hub in Brazil
<p><span>Context: The education and training of information security professionals is essential to ensure the protection of data and systems, as well as the privacy and security of sensitive information. Problem: This work aims to explore the context of a local technology hub to answer the following research question: Is secure software development education necessary in the software industry? Solution: To answer this question, an exploratory study was performed to understand the need for secure software development education from the point of view of software practitioners in a technology hub. Method: A questionnaire was prepared and sent to professionals of a Brazilian technology hub. Answers were analyzed by using qualitative research methods. Results: We obtained thirty eight answers. According to the results obtained, the majority of participants consider information security education important for the development of secure software. However, there is still a lack of information security education. Contributions: It is concluded that companies should invest more in adequate and comprehensive training on the topic, in addition to encouraging and rewarding professionals who prioritize software security in their projects. It is essential to disseminate a culture of information security throughout the organization, from senior management to development professionals, to make everyone aware of the importance of information security and their responsibility in maintaining it. Finally, it should be noted that developers have a crucial role in ensuring software security, being responsible for seeking knowledge and improving their skills in secure development through training, reading and practice</span><span>. (Paper accepted in the Brazilian Symposium of Software Engineering)</span></p>
Identifying Improvement Opportunities in Software Engineering Education at the Maranhão State: Listening to Voices from Academy and Industry
<p>The teaching of Software Engineering (SE) has become challenging due to the large amount of content taught and the constant evolution of the software industry, directly impacting the requirements necessary to apply for a position in the area of Information Technology (IT). In this context, it is clear that students of computer courses still find it difficult to know how to prepare for the job market, and Higher Education Institutions (HEIs) may have difficulties in aligning themselves with market expectations with their syllabus in SE. This paper aims to provide a holistic view of the teaching-learning process, involving the views of students, HEIs and IT companies in the context of the state of Maranhão; and to propose reflections on the current state of the education to complement the contents and methodologies applied in the classroom with the needs of the local industry. To do so, three activities were carried out: (1) mapping expectations and evaluating higher education from the students’ point of view; (2) analysis of higher education disciplines in higher education institutions in the state of Maranhão in Brazil; and (3) survey of expectations of the IT market considering the vacancies disclosed in relation to the SE area in the state of Maranhão. The results indicate a partial fulfillment of the demand regarding the taught topics related to SE from the local industry by the HEIs. In addition, there is a need to improve the teaching-learning methodological processes, focusing on practical activities and the learning of teamwork skills, in addition to knowledge in software development.</p>
Survey data in PDF-What industry wants from academia in software testing research (phase 1)
<p>Survey data in PDF-What industry wants from academia in software testing research</p>
Dataset for survey of industry-academia collaboration in software engineering (phase 1)
<p>Dataset for survey of industry-academia collaboration in software engineering (phase 1)</p>
Software development output metrics for four industrial projects
<p>Data used for the paper "Benchmarking ongoing development output in real-life software projects"</p>
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OpenNeuro
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