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- Colesky, Michael, et al.
(författare)
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Helping Software Architects Familiarize with the General Data Protection Regulation
- 2019
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Ingår i: 2019 IEEE International Conference on Software Architecture Companion (ICSA-C). - : IEEE. - 9781728118772 - 9781728118765 ; , s. 226-229
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Konferensbidrag (refereegranskat)abstract
- Abstract—The General Data Protection Regulation (GDPR)impacts any information systems that process personal datain or from the European Union. Yet its enforcement is stillrecent. Organizations under its effect are slow to adopt itsprinciples. One particular difficulty is the low familiarity withthe regulation among software architects and designers. Thedifficulty to interpret the content of the legal regulation ata technical level adds to that. This results in problems inunderstanding the impact and consequences that the regulationmay have in detail for a particular system or project context.In this paper we present some early work and emergingresults related to supporting software architects in this situation.Specifically, we target those who need to understand how theGDPR might impact their design decisions. In the spirit ofarchitectural tactics and patterns, we systematically identifiedand categorized 155 forces in the regulation. These results formthe conceptual base for a first prototypical tool. It enablessoftware architects to identify the relevant forces by guidingthem through an online questionnaire. This leads them to relevantfragments of the GDPR and potentially relevant privacy patterns.We argue that this approach may help software professionals,in particular architects, familiarize with the GDPR and outlinepotential paths for evaluation.
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| 2. |
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| 3. |
- Gilson, Fabian, et al.
(författare)
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When Natural Language Processing Jumps into Collaborative Software Engineering
- 2019
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Ingår i: 2019 IEEE INTERNATIONAL CONFERENCE ON SOFTWARE ARCHITECTURE COMPANION (ICSA-C 2019). - : IEEE. - 9781728118765 ; , s. 238-241
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Konferensbidrag (refereegranskat)abstract
- Software engineering is an intrinsically collaborative activity, especially in the era of Agile Software Development. Many actors are partaking in development activities, such that a common understanding should be reached at numerous stages during the overall development life-cycle. For a few years now, Natural Language Processing techniques have been employed either to extract key information from free-form text or to generate models from the analysis of text in order to ease the sharing of knowledge across all parties. A significant part of these approaches focuses on retrieving lost domain and architectural knowledge through the analysis of documents, issue management systems or other forms of knowledge management systems. However, these post-processing methods are time-consuming by nature since they require to invest significant resources into the validation of the extracted knowledge. In this paper, inspired by collaborative tools, bots and Natural Language extraction approaches, we envision new ways to collaboratively record and document design decisions as they are discussed. These decisions will be documented as they are taken and, for some of them, static or behavioural models may be generated on-the-fly. Such an interactive process will ensure everyone agrees on critical design aspects of the software. We believe development teams will benefit from this approach because manual encoding of design knowledge will be reduced and will not be pushed to a later stage, when not forgotten.
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