On Strongest Algebraic Program Invariants

Author:

Hrushovski Ehud1,Ouaknine Joël2,Pouly Amaury3,Worrell James1

Affiliation:

1. Oxford University, UK

2. Max Planck Institute for Software Systems, Germany

3. Université de Paris, IRIF, CNRS, France

Abstract

A polynomial program is one in which all assignments are given by polynomial expressions and in which all branching is nondeterministic (as opposed to conditional). Given such a program, an algebraic invariant is one that is defined by polynomial equations over the program variables at each program location. Müller-Olm and Seidl have posed the question of whether one can compute the strongest algebraic invariant of a given polynomial program. In this article, we show that, while strongest algebraic invariants are not computable in general, they can be computed in the special case of affine programs, that is, programs with exclusively linear assignments. For the latter result, our main tool is an algebraic result of independent interest: Given a finite set of rational square matrices of the same dimension, we show how to compute the Zariski closure of the semigroup that they generate.

Funder

ERC

DFG

EPSRC Fellowship

UKRI Fellowship

Publisher

Association for Computing Machinery (ACM)

Subject

Artificial Intelligence,Hardware and Architecture,Information Systems,Control and Systems Engineering,Software

Reference47 articles.

1. S. Almagor, D. Chistikov, J. Ouaknine, and J. Worrell. 2018. O-minimal invariants for linear loops. In Proceedings of the 45th International Colloquium on Automata, Languages and Programming. Schloss Dagstuhl - Leibniz-Zentrum fuer Informatik.

2. L. Babai, R. Beals, J.-Y. Cai, G. Ivanyos, and E. M. Luks. 1996. Multiplicative equations over commuting matrices. In Proceedings of the 7th Annual ACM-SIAM Symposium on Discrete Algorithms.498–507.

3. Gröbner Bases

4. Decidable and Undecidable Problems about Quantum Automata

5. A. R. Bradley and Z. Manna. 2007. The Calculus of Computation—Decision Procedures with Applications to Verification. Springer.

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1. Strong Invariants Are Hard: On the Hardness of Strongest Polynomial Invariants for (Probabilistic) Programs;Proceedings of the ACM on Programming Languages;2024-01-05

2. Solvable Polynomial Ideals: The Ideal Reflection for Program Analysis;Proceedings of the ACM on Programming Languages;2024-01-05

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