Scientific Programs Imply Uncertainty. Results Expected and Unexpected
Sergey Andreyev

TL;DR
The paper discusses the distinction between well-known and uncertain scientific programs, emphasizing the need for tools that analyze situations beyond current knowledge and exploring the possibility of designing such programs.
Contribution
It introduces a conceptual framework for understanding programs that handle uncertainty and questions the feasibility of designing programs for analysis beyond existing knowledge.
Findings
Differentiates between calculators for known situations and analysis tools for uncertain scenarios.
Highlights the need for programs that can operate beyond the developers' current knowledge.
Raises questions about the design and development of such advanced analytical programs.
Abstract
Science and engineering have requests for a wide variety of programs, but I think that all of them can be divided between two groups. Programs of the first group deal with the well known situations and, by using well known equations, give results for any combination of input parameters. Such programs are specialized very powerful calculators. Another group of programs is needed to analyse the situations with different levels of uncertainty. Programs are developed at the best level of their authors, but scientists need to look at the situations beyond the area of current knowledge, and they need programs to do analysis in the areas of uncertainty. Is it possible do design programs which allow to analyse the situations beyond the knowledge of developers?
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Taxonomy
TopicsBiomedical and Engineering Education · Scientific Computing and Data Management
