Symbolic Computation in Software Science: My Personal View

TL;DR

This paper presents a personal perspective on the role and importance of symbolic computation within software science, exploring its connections with AI, automatic programming, and mathematical knowledge management.

Contribution

It offers a reflective analysis of symbolic computation's scope and relevance, integrating insights from the author's previous work and clarifying its relationship with related fields.

Findings

Symbolic computation is crucial for advancing software science.

It interacts closely with AI, automatic programming, and mathematical knowledge management.

The paper clarifies distinctions and overlaps among related computational fields.

Abstract

In this note, I develop my personal view on the scope and relevance of symbolic computation in software science. For this, I discuss the interaction and differences between symbolic computation, software science, automatic programming, mathematical knowledge management, artificial intelligence, algorithmic intelligence, numerical computation, and machine learning. In the discussion of these notions, I allow myself to refer also to papers (1982, 1985, 2001, 2003, 2013) of mine in which I expressed my views on these areas at early stages of some of these fields.