HCMay 22, 2019

Scientific Programs Imply Uncertainty. Results Expected and Unexpected

arXiv:1905.09644v1
Originality Synthesis-oriented
AI Analysis

This is an incremental discussion on improving program design for uncertain scenarios in science and engineering.

The paper addresses the challenge of designing programs that can analyze situations beyond the developers' current knowledge, particularly in scientific and engineering contexts with uncertainty, but does not provide specific results or numbers.

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?

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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