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Languages for Non-developers: What, How, Where? Invited Talk - Extended Abstract

Tolvanen Juha-Pekka

Annals of Computer Science and Information Systems

2024

Vol. 39

61--62

Productivity has improved each time programming languages have raised the level of abstraction. This trend continues today with languages that narrow the scope they address -- referred to as domain-specific languages (DSLs). However, many of these DSLs are built by developers for developers and tend to concentrate on the solution domain rather than the problem domain. In this talk, I will advocate for languages to be aligned more closely with the problem domain, addressing the needs of domain experts. Such languages enable non-developers to capture and communicate their knowledge, and together with tools support testing, validation, and feedback. Tools can also transform precise knowledge representations into software code and other artifacts. I will provide examples of non-developer languages used by usability experts, safety engineers, insurance experts, and instrumentation experts. These languages differ from traditional programming languages as they aim to align more closely with the domain, representing knowledge through maps, diagrams, or tables rather than with plain text only. The talk will identify key characteristics of non-developer languages and discuss how creating them differs from programming languages. This leads us to envision the role of non-developers in language creation and identify domains in which non-developer languages are more suitable.

Methodology of Diagnostic Knowledge Acquisition

Moczulski W.

Bulletin of the Polish Academy of Sciences. Technical Sciences

2001

vol. 49, nr 2

337-357

The paper deals with a comprehensive methodology concerning knowledge acquisition on machinery for the purpose of expert systems suitable for aiding of diagnostic inference. The methodology includes selected methods of diagnostic knowledge representation, methods of knowledge acquisition from domain experts and from previously classified examples, methods of assessment of previously acquired knowledge and a scenario of knowldge acquisition process. All the methods have been implemented in a Knowledge Acquisition System. Moreover, some examples of applications of the elaborated methodology have been given.