• Symbolic computation for software science
  • September 8–10, 2021
  • Virtual
  • RISC, JKU Linz, Austria

The 9th International Symposium on Symbolic Computation in Software Science
— In the era of Computational and Artificial Intelligence —

Overview

SCSS 2021 is the 9th International Symposium on Symbolic Computation in Software Science. Its purpose is to promote research on theoretical and practical aspects of symbolic computation in software science, combined with modern artificial intelligence techniques. Due to COVID-19 pandemic, SCSS 2021 will be held as a virtual event, organized by the Research Institute for Symbolic Computation, Johannes Kepler University Linz, Austria.

Symbolic Computation is the science of computing with symbolic objects (terms, formulae, programs, representations of algebraic objects etc.). Powerful algorithms have been developed during the past decades for the major subareas of symbolic computation: computer algebra and computational logic. These algorithms and methods are successfully applied in various fields, including software science, which covers a broad range of topics about software construction and analysis.

Meanwhile, artificial intelligence methods and machine learning algorithms are widely used nowadays in various domains and, in particular, combined with symbolic computation. Several approaches mix artificial intelligence and symbolic methods and tools deployed over large corpora to create what is known as cognitive systems. Cognitive computing focuses on building systems which interact with humans naturally by reasoning, aiming at learning at scale.

Scope

The topics of the symposium include, but are not limited to the following:

  • automated reasoning, knowledge reasoning, common-sense reasoning and reasoning in science
  • algorithm (program) synthesis and/or verification, alignment and joint processing of formal, semi-formal, and informal libraries.
  • formal methods for the analysis of network and system security
  • termination analysis and complexity analysis of algorithms (programs)
  • extraction of specifications from algorithms (programs)
  • theorem proving methods and techniques, collaboration between automated and interactive theorem proving
  • proof carrying code
  • generation of inductive assertion for algorithm (programs)
  • algorithm (program) transformations
  • combinations of linguistic/learning-based and semantic/reasoning methods
  • formalization and computerization of knowledge (maths, medicine, economy, etc.)
  • methods for large-scale computer understanding of mathematics and science
  • artificial intelligence, machine learning and big-data methods in theorem proving and mathematics
  • formal verification of artificial intelligence and machine learning algorithms, explainable artificial intelligence, symbolic artificial intelligence
  • cognitive computing, cognitive vision, perception systems and artificial reasoners for robotics
  • component-based programming
  • computational origami
  • query languages (in particular for XML documents)
  • semantic web and cloud computing