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- Abrahao, Silvia, et al.
(författare)
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Modeling and Architecting of Complex Software Systems
- 2024
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Ingår i: IEEE SOFTWARE. - 0740-7459 .- 1937-4194. ; 41:3, s. 76-79
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Tidskriftsartikel (refereegranskat)abstract
- This edition of the "Practitioners' Digest" covers recent papers on novel approaches and tools to assist developers in modeling and architecting software systems from two conferences: the 26th ACM/IEEE International Conference on Model Driven Engineering Languages and Systems (MODELS) and the 20th IEEE International Conference on Software Architecture (ICSA). Feedback or suggestions are welcome. Also, if you try or adopt any of the practices included in the column, please send us and the authors of the paper(s) a note about your experiences.
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| 4. |
- Abrahao, Silvia, et al.
(författare)
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Open Source Software: Communities and Quality
- 2023
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Ingår i: IEEE Software. - 1937-4194 .- 0740-7459. ; 40:4, s. 96-99
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Tidskriftsartikel (refereegranskat)abstract
- This edition of the Practitioner's Digest features recent papers on open source software related to toxicity in open source discussions, newcomers in open source projects, quality of ansible scripts, code review practices, orphan vulnerabilities in open source software, and the relationship between community and design smells.
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- Carver, Jeffrey C., et al.
(författare)
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Extracting Requirements and Modeling Information and Controlling Risk
- 2021
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Ingår i: IEEE Software. - 1937-4194 .- 0740-7459. ; 38:3, s. 121-124
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Forskningsöversikt (refereegranskat)abstract
- Presents papers from the 2020 IEEE Conference on Requirements Engineering and the ACM/ IEEE 23rd International Conference on Model Driven Engineering Languages and Systems (MODELS 2020).
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| 7. |
- Chaudron, Michel, 1969, et al.
(författare)
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Proceedings of the 2nd Workshop on Experiences and Empirical Studies in Software Modelling
- 2012
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Ingår i: Research Reports in Software Engineering and Management. - Göteborg : University of Gothenburg.
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Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract
- The International Workshop on Experiences and Empirical Studies in Software Modelling (EESSMod) is a satellite event of the ACM/IEEE International Conference on Model Driven Engineering Languages and Systems (MoDELS), with professionals and researchers interested in software modelling as intended audience, and with the bjective to 1) build a better understanding of the industrial use of modelling techniques, languages and tools; 2) start building theories about the effectiveness of modelling approaches; 3) identify directions for future research in the field; 4) facilitate and encourage joint research and experimentation in software modelling.The report contains the proceedings of the 2nd edition of the workshop, held in Innsbruck, Oct 2, 2012.
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| 8. |
- Khalajzadeh, Hourieh, et al.
(författare)
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Fifth International Workshop on Human Factors in Modeling / Modeling of Human Factors (HuFaMo'21)
- 2021
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Ingår i: Companion Proceedings - 24th International Conference on Model-Driven Engineering Languages and Systems, MODELS-C 2021. ; , s. 337-340
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Konferensbidrag (refereegranskat)abstract
- Studying human factors and experiences in modeling helps to gain knowledge on the process and use of modeling in practice to optimize system outcomes and user well-being. Moreover, to better support the human aspects of stakeholders and end-users of the software, incorporating the human aspects into software engineering processes from the early modeling and design stages is essential. Considering human factors in software design involves not only 1) studying in detail the interactions between users (humans), but also 2) studying the human factors of the end-users of the system. The HuFaMo workshop was established in 2015 to promote this form of research by creating a venue to discuss and disseminate these topics. The HuFaMo Workshop originally aimed at studying human factors for software systems (implemented or not) allowing humans to model. Hosted within the MODELS conference, the first four editions of the workshop benefited from a high-quality audience, allowing significant progress on this issue. For this fifth edition, we have widened the scope of the workshop to consider the modeling of human factors during the design of the software as well. This helps to study all types of relationships that modeling and human factors can have and their impact on processes, products, and end-users as well as others that might be affected by the system.
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| 9. |
- Liebel, Grischa, 1987, et al.
(författare)
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Human factors in model-driven engineering: future research goals and initiatives for MDE
- 2024
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Ingår i: SOFTWARE AND SYSTEMS MODELING. - 1619-1366 .- 1619-1374.
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Tidskriftsartikel (refereegranskat)abstract
- Software modelling and model-driven engineering (MDE) is traditionally studied from a technical perspective. However, one of the core motivations behind the use of software models is inherently human-centred. Models aim to enable practitioners to communicate about software designs, make software understandable, or make software easier to write through domain-specific modelling languages. Several recent studies challenge the idea that these aims can always be reached and indicate that human factors play a role in the success of MDE. However, there is an under-representation of research focusing on human factors in modelling. During a GI-Dagstuhl seminar, topics related to human factors in modelling were discussed by 26 expert participants from research and industry. In breakout groups, five topics were covered in depth, namely modelling human aspects, factors of modeller experience, diversity and inclusion in MDE, collaboration and MDE, and teaching human-aware MDE. We summarise our insights gained during the discussions on the five topics. We formulate research goals, questions, and propositions that support directing future initiatives towards an MDE community that is aware of and supportive of human factors and values.
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| 10. |
- Penzenstadler, Birgit, 1981, et al.
(författare)
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AI, Tech, Energy, and Collaboration
- 2023
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Ingår i: IEEE Software. - 1937-4194 .- 0740-7459. ; 40:3, s. 80-83
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Tidskriftsartikel (refereegranskat)abstract
- This edition of the “Practitioner’s Digest” features recent papers on artificial intelligence (AI) and machine learning (ML), along with papers on tech debt, energy consumption, and collaboration between industry and academia.
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| 11. |
- Penzenstadler, Birgit, 1981, et al.
(författare)
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Bots in Software Engineering
- 2022
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Ingår i: IEEE Software. - 1937-4194 .- 0740-7459. ; 39:5, s. 101-104
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Forskningsöversikt (refereegranskat)
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| 12. |
- Staron, Miroslaw, 1977, et al.
(författare)
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Bringing Software Engineering Discipline to the Development of AI-Enabled Systems
- 2024
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Ingår i: IEEE Software. - 1937-4194 .- 0740-7459. ; 41:5, s. 79-82
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Tidskriftsartikel (refereegranskat)abstract
- Engineering AI Software systems is starting to evolve from the pure development of machine learning (ML) models to a more structured discipline that treats ML components as part of much larger software systems. As such, more structured principles are required for their development, such as established design principles, established development models, and safeguards for deployed ML models. This column focuses on papers presented at the Third International Conference on AI Engineering—Software Engineering for AI (CAIN 2024). The selected papers reflect the current development of the field of AI systems engineering and AI software development, taking it to the next level of maturity. Feedback or suggestions are welcome. In addition, if you try or adopt any of the practices included in the column, please send us and the authors of the paper(s) a note about your experiences.
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| 13. |
- Staron, Miroslaw, 1977, et al.
(författare)
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Human Aspects and Security in Software Development
- 2024
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Ingår i: IEEE SOFTWARE. - 0740-7459 .- 1937-4194. ; 41:4, s. 171-174
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Tidskriftsartikel (refereegranskat)abstract
- This edition of the "Practitioners' Digest" brings you recent articles on approaches to addressing selected human and technical aspects of software development, from finding security vulnerabilities, system-level testing, to understanding the impact of personality on requirements engineering activities, published at selected software engineering conferences.
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| 16. |
- Staron, Miroslaw, 1977, et al.
(författare)
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Testing, Debugging, and Log Analysis With Modern AI Tools
- 2024
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Ingår i: IEEE Software. - 0740-7459 .- 1937-4194. ; 41, s. 99-102
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Tidskriftsartikel (refereegranskat)abstract
- This edition of the Practitioners Digest covers recent papers employing generative artificial intelligence in support of testing, debugging, and log analysis that were presented at the 38th IEEE/ACM International Conference on Automated Software Engineering (ASE 2023) and the 16th IEEE International Conference on Software, Testing, Verification and Validation (ICST 2023). Feedback or suggestions are welcome. In addition, if you try or adopt any of the practices included in the column, please send us and the authors of the paper(s) a note about your experiences.
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| 17. |
- Zúñiga-Prieto, Miguel, et al.
(författare)
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Dynamic reconfiguration of cloud application architectures
- 2018
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Ingår i: Software, practice & experience. - : John Wiley & Sons. - 0038-0644 .- 1097-024X. ; 48:2, s. 327-344
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Tidskriftsartikel (refereegranskat)abstract
- Service-based cloud applications are software systems that continuously evolve to satisfy new user requirements and technological changes. This kind of applications also require elasticity, scalability, and high availability, which means that deployment of new functionalities or architectural adaptations to fulfill service level agreements (SLAs) should be performed while the application is in execution. Dynamic architectural reconfiguration is essential to minimize system disruptions while new or modified services are being integrated into existing cloud applications. Thus, cloud applications should be developed following principles that support dynamic reconfiguration of services, and also tools to automate these reconfigurations at runtime are needed. This paper presents an extension of a model-driven method for dynamic and incremental architecture reconfiguration of cloud services that allows developers to specify new services as software increments, and the tool to generate the implementation code for the services integration logic and the deployment and architectural reconfiguration scripts specific to the cloud environment in which the service will be deployed (e.g., Microsoft Azure). We also report the results of a quasi-experiment that empirically validate our method. It was conducted to evaluate their perceived ease of use, perceived usefulness, and perceived intention to use. The results show that the participants perceive the method to be useful, and they also expressed their intention to use the method in the future. Although further experiments must be carried out to corroborate these results, the method has proven to be a promising architectural reconfiguration process for cloud applications in the context of agile and incremental development processes.
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