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Towards Consistency Analysis Between Formal and Informal Software Architecture Artefacts

Keim, Jan; Schneider, Yves; Koziolek, Anne

Abstract (englisch):
Documenting the architecture of a software system is important, especially to capture reasoning and design decisions. A lot of tacit knowledge can easily get lost when the documentation is incomplete, resulting in threats for the software system’s success and increased costs. However, software architecture documentation is often missing or outdated. One explanation for this phenomenon is the tedious and costly process of creating documentation in comparison to (perceived) low benefits. In this paper, we first present our long-term vision, where we plan to persist information from any sources, e.g. from whiteboard discussions, to avoid losing crucial information about a system. A core problem in this vision is the possible inconsistency of information from different sources. A major
challenge of ensuring consistency is the consistency between formal artefacts, i.e. models, and informal documentation. We plan to address consistency analyses between models and textual natural language artefacts using natural language understanding and plan to include knowledge bases to improve these analyses.
After extracting information out of the natural language documents, we plan to create traceability links and check whether statements within the textual documentation are consistent with the software architecture models. ... mehr



Zugehörige Institution(en) am KIT Institut für Programmstrukturen und Datenorganisation (IPD)
Publikationstyp Proceedingsbeitrag
Jahr 2019
Sprache Englisch
Identifikator KITopen-ID: 1000097783
Erschienen in Proceedings of the 2nd International Workshop on Establishing a Community-Wide Infrastructure for Architecture-Based Software Engineering
Verlag IEEE Press, Piscataway, NJ, USA
Seiten 6–12
Serie ECASE ’19
Schlagworte Natural language processing, Software architecture, Software engineering, Software architecture documentation, Consistency, Natural language understanding
Nachgewiesen in Scopus
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