Laboratory for compositional systems and methods

TalTech priority area
Research classification (Frascati)
Head of the research group
Keyword
compositionality
open systems
applied category theory
programming languages
trustworthy software
diagrammatic reasoning
string diagrams
logic in computer science
relational methods
quantum computing
Overview
The group's goal is to study compositional techniques in the context of models of computation, understood broadly. Compositionality means that syntactic descriptions for (open) systems are designed to be compatible with their semantics. While the examples motivating the research come from a broad section of scientific disciplines (logic, control theory, formal language theory, control theory, business processes, game theory, economics, machine learning), we have identified common principles for reasoning about open systems, guided by category theory. These including a semantic universe based on relations rather than functions, and the use of the diagrammatic syntax of string diagrams. String diagrams provide an intuitive calculus for computations via diagrammatic reasoning, and fine-grained control over resources, which is important for faithful descriptions of open systems. Our big questions/challenges are 1) design a next generation of programming/specification languages that will be more suited for compositional (and therefore, more trustworthy and reliable) descriptions of systems, 2) use compositionality to improve the analysis of systems, including the design of new techniques and algorithms, and 3) design and implement tools for working with string diagrams, fast-tracking the passage from theory to practice.
Important results
Hadzihasanovic, A.; Kessler, D. (2023). Higher-dimensional subdiagram matching. 2023 38th Annual ACM/IEEE Symposium on Logic in Computer Science (LICS), 26 - 29 June, 2023, Boston, USA. ACM, 13 pp. DOI: 10.1109/LICS56636.2023.10175726
Period of activity of the research group
Related department