Centrala begrepp
The author argues for the implementation of low-modeling techniques to accelerate software development by reducing manual modeling efforts and enhancing productivity.
Sammanfattning
Low-modeling is proposed as a solution to address the increasing complexity of software systems. By automating model generation and leveraging existing knowledge, low-modeling aims to streamline the development process. Strategies like heuristic-based model generation, knowledge-based model enrichment, and ML-based model inference are discussed to illustrate the benefits of low-modeling in creating smart software systems efficiently.
Statistik
Low-code platforms accelerate app delivery by reducing hand-coding.
Low-modeling accelerates modeling by reducing hand-modeling efforts.
AI elements are challenging to specify, architect, test, and verify.
Knowledge-based model enrichment uses existing structured knowledge to enhance models.
ML techniques can infer models from unstructured sources.
Citat
"Low-modeling accelerates the modeling of software systems by reducing manual efforts."
"Knowledge-based model enrichment leverages existing structured knowledge to improve models."