Search arXivSearch

arXiv · 2301.09234

Refutations of pebble minimization via output languages

Abstract

Polyregular functions are the class of string-to-string functions definable by pebble transducers, an extension of finite-state automata with outputs and multiple two-way reading heads (pebbles) with a stack discipline. If a polyregular function can be computed with $k$ pebbles, then its output length is bounded by a polynomial of degree $k$ in the input length. But Bojańczyk has shown that the converse fails. In this paper, we provide two alternative easier proofs. The first establishes by elementary means that some quadratic polyregular function requires 3 pebbles. The second proof - just as short, albeit less elementary - shows a stronger statement: for every $k$, there exists some polyregular function with quadratic growth whose output language differs from that of any $k$-fold composition of macro tree transducers (and which therefore cannot be computed by a $k$-pebble transducer). Along the way, we also refute a conjectured logical characterization of polyblind functions.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Sandra Kiefer, Lê Thành Dũng Nguyên, Cécilia Pradic. 2023-06-20. Refutations of pebble minimization via output languages. https://arxiv.org/abs/2301.09234

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related papers

Simple grammar bisimilarity, with an application to session type equivalence

We provide an algorithm for deciding simple grammar bisimilarity whose complexity is polynomial in the valuation of the grammar (maximum seminorm among production rules). Since the valuation is at most exponential in the size of the grammar, this gives rise to a (single) exponential running time. Previously only a double-exponential algorithm was known. As an application, we provide a conversion from context-free session types to simple grammars whose valuation is linear in the size of the type. In this way, we provide the first polynomial-time algorithm for deciding context-free session type equivalence.

cs.FL

Testing and Learning Symbolic Finite State Machines

Symbolic finite state machines (SFSMs) describe input/output behaviour using guards and output assignments with possibly infinite data domains. We study deterministic and completely specified SFSMs whose guards and output assignments depend only on the current input. We define finite representative input sets that contain witnesses for relevant guard overlaps and separating witnesses for output assignments that differ on those overlaps. Our main theorem shows that language equivalence of the finite instantiations implies language equivalence over the full input domain. This result transfers complete testing methods for deterministic finite state machines (DFSMs) to SFSMs, provided finite sets of admissible guards and output assignments and an upper bound on the number of distinguishable reachable states are known. Under these assumptions, a DFSM learner with complete testing can learn a finite instantiation, which is then lifted to an equivalent SFSM. We establish a bound on the size of representative input sets and give an SMT construction whose correctness and termination hold under stated solver assumptions.

cs.FL

Recognizable Picture Languages: Separating UREC from coUREC via Communication Complexity

We introduce communication-complexity lifting techniques into the study of recognizable picture languages. As an application, we resolve a long-standing open problem of Anselmo et al. (2006) by constructing a language in UREC whose complement does not belong to REC. Our lower-bound argument is inspired by the communication-complexity approach to unambiguous automata of Göös et al. (2022), although its implementation in the setting of picture languages requires substantially different technical ingredients.

cs.FL