Computing polynomial program invariants
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Cited by (85)
A novel data-driven approach on inferring loop invariants for C programs
2022, Journal of Computer LanguagesCitation Excerpt :Chen et al. [46] apply multivariate Lagrange interpolation to synthesize polynomial loop invariants directly. Müller-Olm et al. [47] exploit an abstract interpretation-based technique to obtain possible algebraic invariants by combining user-provided monomials. Cachera et al. [48] extend the work of Müller-Olm et al. [47], and utilize abstract interpretation with a constant-based technique to compute loop invariants for imperative programs, where program variables are interpreted as values over the real numbers.
Polynomial interrupt timed automata: Verification and expressiveness
2021, Information and ComputationCitation Excerpt :Linear constraints are not always expressive enough for modeling purposes. In an untimed setting, polynomials of discrete variables were considered for the analysis of programs [14–16]. In the context of hybrid systems, several biological models shown in [17] involve polynomials (or even rational functions) of continuous variables, that appear in the differential equations, but can also be compared with threshold values.
Complete algorithms for algebraic strongest postconditions and weakest preconditions in polynomial ODEs
2020, Science of Computer ProgrammingStrong Invariants Are Hard: On the Hardness of Strongest Polynomial Invariants for (Probabilistic) Programs
2024, Proceedings of the ACM on Programming LanguagesSolvable Polynomial Ideals: The Ideal Reflection for Program Analysis
2024, Proceedings of the ACM on Programming Languages
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On leave from Universität Dortmund.