Proceedings of the 9th International Symposium on Symbolic Computation in Software Science
Temur Kutsia

TL;DR
This symposium volume presents recent advances in symbolic computation applied to software science, emphasizing the integration of artificial intelligence and machine learning techniques with symbolic methods for software analysis and construction.
Contribution
It introduces new research on combining symbolic computation with AI and machine learning in software science, highlighting theoretical and practical developments.
Findings
Integration of AI with symbolic computation enhances software analysis.
New algorithms for symbolic reasoning in software engineering.
Advances in cognitive systems using symbolic and AI methods.
Abstract
This volume contains papers presented at the Ninth International Symposium on Symbolic Computation in Software Science, SCSS 2021. 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…
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