In this research project, we aim to provide consistency analyses between different kind of documentation, namely formal models and informal (textual) documentation.
Documenting the architecture of a software system is important, especially to capture reasoning and design decisions. A lot of tacit knowledge is easily 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 However, software architecture documentation is often missing or outdated.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. With our project, we want to step forward in 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.
ArDoCo is actively developed by researchers of the Modelling for Continuous Software Engineering (MCSE) group of KASTEL - Institute of Information Security and Dependability at the KIT.
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