Memoization

Abstract: Despite the power of Parser Expression Grammars (PEGs) and GLR, parsing is not a solved problem. Adding nondeterminism (parser speculation) to traditional LL and LR parsers can lead to unexpected parse-time behavior and introduces practical issues with error handling, single-step debugging, and side-effecting embedded grammar actions. This paper introduces the LL(*) parsing strategy and an associated grammar analysis algorithm that constructs LL(*) parsing decisions from ANTLR grammars. At parse-time, decisions gracefully throttle up from conventional fixed k>=1 lookahead to arbitrary lookahead and, finally, fail over to backtracking depending on the complexity of the parsing decision and the input symbols. LL(*) parsing strength reaches into the context-sensitive languages, in some cases beyond what GLR and PEGs can express. By statically removing as much speculation as possible, LL(*) provides the expressivity of PEGs while retaining LL's good error handling and unrestricted grammar actions. Widespread use of ANTLR (over 70,000 downloads/year) shows that it is effective for a wide variety of applications.

Abstract: Techniques for efficiently evaluating future time Linear Temporal Logic (abbreviated LTL) formulae on finite execution traces are presented. While the standard models of LTL are infinite traces, finite traces appear naturally when testing and/or monitoring real applications that only run for limited time periods. A finite trace variant of LTL is formally defined, together with an immediate executable semantics which turns out to be quite inefficient if used directly, via rewriting, as a monitoring procedure. Then three algorithms are investigated. First, a simple synthesis algorithm for monitors based on dynamic programming is presented; despite the efficiency of the generated monitors, they unfortunately need to analyze the trace backwards, thus making them unusable in most practical situations. To circumvent this problem, two rewriting-based practical algorithms are further investigated, one using rewriting directly as a means for online monitoring, and the other using rewriting to generate automata-like monitors, called binary transition tree finite state machines (and abbreviated BTT-FSMs). Both rewriting algorithms are implemented in Maude, an executable specification language based on a very efficient implementation of term rewriting. The first rewriting algorithm essentially consists of a set of equations establishing an executable semantics of LTL, using a simple formula transforming approach. This algorithm is further improved to build automata on-the-fly via caching and reuse of rewrites (called memoization), resulting in a very efficient and small Maude program that can be used to monitor program executions. The second rewriting algorithm builds on the first one and synthesizes provably minimal BTT-FSMs from LTL formulae, which can then be used to analyze execution traces online without the need for a rewriting system. The presented work is part of an ambitious runtime verification and monitoring project at NASA Ames, called PathExplorer, and demonstrates that rewriting can be a tractable and attractive means for experimenting and implementing logics for program monitoring.

Abstract: Principles of principle-based parsing, R.C. Berwick deductive parsing - the use of knowledge of language, M. Johnson the computational implementation of principle-based parsers, S. Fong empty categories, chain binding, and parsing, N. Correa parsing Warlpiri - a free word order language, M.B. Kashket principle-based parsing for machine translation, B.J. Dorr principle-based interpretation of natural language quantifiers, S.S. Epstein avoid the pedestrian's paradox, E.P. Stabler Jr parsing with changing grammars - evaluating a language acquisition model, R. Kazman parsing by chunks, S.P. Abney subcategorization and sentence processing, P. Gorrell subjacency in a principle-based parser, B.L. Pritchett locating Wh traces, H.S. Kurtzman et al.

Abstract: Several recent projects have shown the feasibility of verifying low-level systems software. Verifications based on automated theorem-proving have omitted reasoning about first-class code pointers, which is critical for tasks like certifying implementations of threads and processes. Conversely, verifications that deal with first-class code pointers have featured long, complex, manual proofs. In this paper, we introduce the Bedrock framework, which supports mostly-automated proofs about programs with the full range of features needed to implement, e.g., language runtime systems.The heart of our approach is in mostly-automated discharge of verification conditions inspired by separation logic. Our take on separation logic is computational, in the sense that function specifications are usually written in terms of reference implementations in a purely functional language. Logical quantifiers are the most challenging feature for most automated verifiers; by relying on functional programs (written in the expressive language of the Coq proof assistant), we are able to avoid quantifiers almost entirely. This leads to some dramatic improvements compared to both past work in classical verification, which we compare against with implementations of data structures like binary search trees and hash tables; and past work in verified programming with code pointers, which we compare against with examples like function memoization and a cooperative threading library.