Reachability and error diagnosis in LR(1) automata

National audienceGiven an LR(1) automaton, what are the states in which an error can be detected? For each such " error state " , what is a minimal input sentence that causes an error in this state? We propose an algorithm that answers these questions. Such an algorithm allows building a collection of pairs of an erroneous input sentence and a diagnostic message, ensuring that this collection covers every error state, and maintaining this property as the grammar evolves. We report on an application of this technique to the CompCert ISO C99 parser, and discuss its strengths and limitations

Reachability and Error Diagnosis in LR(1) Parsers

International audienceGiven an LR(1) automaton, what are the states in which an error can be detected? For each such " error state " , what is a minimal input sentence that causes an error in this state? We propose an algorithm that answers these questions. This allows building a collection of pairs of an erroneous input sentence and a (handwritten) diagnostic message, ensuring that this collection covers every error state, and maintaining this property as the grammar evolves. We report on an application of this technique to the CompCert ISO C99 parser, and discuss its strengths and limitations

LL(1) Parsing with Derivatives and Zippers

In this paper, we present an efficient, functional, and formally verified parsing algorithm for LL(1) context-free expressions based on the concept of derivatives of formal languages. Parsing with derivatives is an elegant parsing technique, which, in the general case, suffers from cubic worst-case time complexity and slow performance in practice. We specialise the parsing with derivatives algorithm to LL(1) context-free expressions, where alternatives can be chosen given a single token of lookahead. We formalise the notion of LL(1) expressions and show how to efficiently check the LL(1) property. Next, we present a novel linear-time parsing with derivatives algorithm for LL(1) expressions operating on a zipper-inspired data structure. We prove the algorithm correct in Coq and present an implementation as a parser combinators framework in Scala, with enumeration and pretty printing capabilities.Comment: Appeared at PLDI'20 under the title "Zippy LL(1) Parsing with Derivatives

Enforcing Strict Model-View Separation in Template Engines

The mantra of every experienced web application developer is the same: thou shalt separate business logic from display. Ironically, almost all template engines allow violation of this separation principle, which is the very impetus for HTML template engine development. This situation is due mostly to a lack of formal definition of separation and fear that enforcing separation emasculates a template 's power. I show that not only is strict separation a worthy design principle, but that we can enforce separation while providing a potent template engine. I demonstrate my StringTemplate engine, used to build jGuru.com and other commercial sites, at work solving some nontrivial generational tasks My goal is to formalize the study of template engines, thus, providing a common nomenclature, a means of classifying template generational power, and a way to leverage interesting results from formal language theory. I classify three types of restricted templates analogous to Chomsky's type 1..3 grammar classes and formally define separation including the rules that embody separation. Because this paper provides a clear definition of model-view separation, template engine designers may no longer blindly claim enforcement of separation. Moreover, given theoretical arguments and empirical evidence, programmers no longer have an excuse to entangle model and view