Interpretations of logical formulas over semirings (other than the Boolean semiring) have applications in various areas of computer science including logic, AI, databases, and security. Such interpretations provide richer information beyond the truth or falsity of a statement. Examples of such semirings include Viterbi semiring, min-max or access control semiring, tropical semiring, and fuzzy semiring. The present work investigates the complexity of constraint optimization problems over semirings. The generic optimization problem we study is the following: Given a propositional formula phi over n variable and a semiring (K,+, . ,0,1), find the maximum value over all possible interpretations of phi over K. This can be seen as a generalization of the well-known satisfiability problem (a propositional formula is satisfiable if and only if the maximum value over all interpretations/assignments over the Boolean semiring is 1). A related problem is to find an interpretation that achieves the maximum value. In this work, we first focus on these optimization problems over the Viterbi semiring, which we call optConfVal and optConf. We first show that for general propositional formulas in negation normal form, optConfVal and optConf are in FP^NP. We then investigate optConf when the input formula phi is represented in the conjunctive normal form. For CNF formulae, we first derive an upper bound on the value of optConf as a function of the number of maximum satisfiable clauses. In particular, we show that if r is the maximum number of satisfiable clauses in a CNF formula with m clauses, then its optConf value is at most 1/4^(m-r). Building on this we establish that optConf for CNF formulae is hard for the complexity class FP^NP[log]. We also design polynomial-time approximation algorithms and establish an inapproximability for optConfVal. We establish similar complexity results for these optimization problems over other semirings including tropical, fuzzy, and access control semirings.
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Semiring Provenance for Fixed-Point Logic
Semiring provenance is a successful approach, originating in database theory, to providing detailed information on how atomic facts combine to yield the result of a query. In particular, general provenance semirings of polynomials or formal power series provide precise descriptions of the evaluation strategies or “proof trees” for the query. By evaluating these descriptions in specific application semirings, one can extract practical information for instance about the confidence of a query or the cost of its evaluation.
This paper develops semiring provenance for very general logical languages featuring the full interaction between negation and fixed-point inductions or, equivalently, arbitrary interleavings of least and greatest fixed points. This also opens the door to provenance analysis applications for modal μ-calculus and temporal logics, as well as for finite and infinite model-checking games.
Interestingly, the common approach based on Kleene’s Fixed-Point Theorem for ω-continuous semirings is not sufficient for these general languages. We show that an adequate framework for the provenance analysis of full fixed-point logics is provided by semirings that are (1) fully continuous, and
(2) absorptive. Full continuity guarantees that provenance values of least and greatest fixed-points are well-defined. Absorptive semirings provide a symmetry between least and greatest fixed-points and make sure that provenance values of greatest fixed points are informative.
We identify semirings of generalized absorptive polynomials S∞[X] and prove universal properties that make them the most general appropriate semirings for our framework. These semirings have the further property of being (3) chain-positive, which is responsible for having truth-preserving interpretations that give non-zero values to all true formulae. We relate the provenance analysis of fixed-point formulae with provenance values of plays and strategies in the associated model-checking games. Specifically, we prove that the provenance value of a fixed point formula gives precise information on the evaluation strategies in these games.
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- Award ID(s):
- 1733794
- NSF-PAR ID:
- 10293797
- Date Published:
- Journal Name:
- Conference on Computer Science Logic, CSL 2021,
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Williams Brian ; Chen Yiling ; Neville Jennifer (Ed.)Interpretations of logical formulas over semirings (other than the Boolean semiring) have applications in various areas of computer science including logic, AI, databases, and security. Such interpretations provide richer information beyond the truth or falsity of a statement. Examples of such semirings include Viterbi semiring, min-max or access control semiring, tropical semiring, and fuzzy semiring. The present work investigates the complexity of constraint optimization problems over semirings. The generic optimization problem we study is the following: Given a propositional formula $\varphi$ over $n$ variable and a semiring $(K,+,\cdot,0,1)$, find the maximum value over all possible interpretations of $\varphi$ over $K$. This can be seen as a generalization of the well-known satisfiability problem (a propositional formula is satisfiable if and only if the maximum value over all interpretations/assignments over the Boolean semiring is 1). A related problem is to find an interpretation that achieves the maximum value. In this work, we first focus on these optimization problems over the Viterbi semiring, which we call \optrustval\ and \optrust. We first show that for general propositional formulas in negation normal form, \optrustval\ and {\optrust} are in ${\mathrm{FP}}^{\mathrm{NP}}$. We then investigate {\optrust} when the input formula $\varphi$ is represented in the conjunctive normal form. For CNF formulae, we first derive an upper bound on the value of {\optrust} as a function of the number of maximum satisfiable clauses. In particular, we show that if $r$ is the maximum number of satisfiable clauses in a CNF formula with $m$ clauses, then its $\optrust$ value is at most $1/4^{m-r}$. Building on this we establish that {\optrust} for CNF formulae is hard for the complexity class ${\mathrm{FP}}^{\mathrm{NP}[\log]}$. We also design polynomial-time approximation algorithms and establish an inapproximability for {\optrustval}. We establish similar complexity results for these optimization problems over other semirings including tropical, fuzzy, and access control semirings.more » « less
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Garbage collection (GC) support for unmanaged languages can reduce programming burden in reasoning about liveness of dynamic objects. It also avoids temporal memory safety violations and memory leaks.
Sound GC for weakly-typed languages such as C/C++, however, remains an unsolved problem. Current value-based GC solutions examine values of memory locations to discover the pointers, and the objects they point to. The approach is inherently unsound in the presence of arbitrary type casts and pointer manipulations, which are legal in C/C++. Such language features are regularly used, especially in low-level systems code.In this paper, we propose Dynamic Pointer Provenance Tracking to realize sound GC. We observe that pointers cannot be created out-of-thin-air, and they must have provenance to at least one valid allocation. Therefore, by tracking pointer provenance from the source (e.g., malloc) through both explicit data-flow and implicit control-flow, our GC has sound and precise information to compute the set of all reachable objects at any program state. We discuss several static analysis optimizations, that can be employed during compilation aided with profiling, to significantly reduce the overhead of dynamic provenance tracking from nearly 8× to 16% for well-behaved programs that adhere to the C standards. Pointer provenance based sound GC invocation is also 13% faster and reclaims 6% more memory on average, compared to an unsound value-based GC.
- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/10.4230/LIPIcs.CSL.2021.17
