33 research outputs found
Characterization of real time iterative array by alternating device
AbstractIn this paper, we show that real time k-dimensional iterative arrays are equivalent through reverse to real time one-way alternating k-counter automata
The Reachability Problem for Petri Nets is Not Elementary
Petri nets, also known as vector addition systems, are a long established
model of concurrency with extensive applications in modelling and analysis of
hardware, software and database systems, as well as chemical, biological and
business processes. The central algorithmic problem for Petri nets is
reachability: whether from the given initial configuration there exists a
sequence of valid execution steps that reaches the given final configuration.
The complexity of the problem has remained unsettled since the 1960s, and it is
one of the most prominent open questions in the theory of verification.
Decidability was proved by Mayr in his seminal STOC 1981 work, and the
currently best published upper bound is non-primitive recursive Ackermannian of
Leroux and Schmitz from LICS 2019. We establish a non-elementary lower bound,
i.e. that the reachability problem needs a tower of exponentials of time and
space. Until this work, the best lower bound has been exponential space, due to
Lipton in 1976. The new lower bound is a major breakthrough for several
reasons. Firstly, it shows that the reachability problem is much harder than
the coverability (i.e., state reachability) problem, which is also ubiquitous
but has been known to be complete for exponential space since the late 1970s.
Secondly, it implies that a plethora of problems from formal languages, logic,
concurrent systems, process calculi and other areas, that are known to admit
reductions from the Petri nets reachability problem, are also not elementary.
Thirdly, it makes obsolete the currently best lower bounds for the reachability
problems for two key extensions of Petri nets: with branching and with a
pushdown stack.Comment: Final version of STOC'1
Tradeoffs for language recognition on alternating machines
AbstractThe alternating machine having a separate input tape with k two-way, read-only heads, and a certain number of internal configurations, AM(k), is considered as a parallel computing model. For the complexity measure TIME · SPACE · PARALLELISM (TSP), the optimal lower bounds Ω(n2) and Ω(n3/2) respectively are proved for the recognition of specific languages on AM(1) and AM(k) respectively. For the complexity measure REVERSALS · SPACE · PARALLELISM (RSP), the lower bound Ω(n1/2) is established for the recognition of a specific language on AM(k). This result implies a polynomial lower bound on PARALLEL TIME · HARDWARE of parallel RAM's.Lower bounds on the complexity measures TIME · SPACE and REVERSALS · SPACE of nondeterministic machines are direct consequences of the result introduced above.All lower bounds obtained are substantially improved in the case that SPACE⩾ nɛ for 0<ɛ<1. Several strongest lower bounds for two-way and one-way alternating (deterministic, nondeterministic) multihead finite automata are obtained as direct consequences of these results. The hierarchies for the complexity measures TSP, RSP, TS and RS can be immediately achieved too
IST Austria Thesis
This dissertation concerns the automatic verification of probabilistic systems and programs with arrays by statistical and logical methods. Although statistical and logical methods are different in nature, we show that they can be successfully combined for system analysis. In the first part of the dissertation we present a new statistical algorithm for the verification of probabilistic systems with respect to unbounded properties, including linear temporal logic. Our algorithm often performs faster than the previous approaches, and at the same time requires less information about the system. In addition, our method can be generalized to unbounded quantitative properties such as mean-payoff bounds. In the second part, we introduce two techniques for comparing probabilistic systems. Probabilistic systems are typically compared using the notion of equivalence, which requires the systems to have the equal probability of all behaviors. However, this notion is often too strict, since probabilities are typically only empirically estimated, and any imprecision may break the relation between processes. On the one hand, we propose to replace the Boolean notion of equivalence by a quantitative distance of similarity. For this purpose, we introduce a statistical framework for estimating distances between Markov chains based on their simulation runs, and we investigate which distances can be approximated in our framework. On the other hand, we propose to compare systems with respect to a new qualitative logic, which expresses that behaviors occur with probability one or a positive probability. This qualitative analysis is robust with respect to modeling errors and applicable to many domains. In the last part, we present a new quantifier-free logic for integer arrays, which allows us to express counting. Counting properties are prevalent in array-manipulating programs, however they cannot be expressed in the quantified fragments of the theory of arrays. We present a decision procedure for our logic, and provide several complexity results