Martin Berglund

Recognizing shuffled languages

Language models that use interleaving, or shuffle, operators have applications in various areas of computer science, including system verification, plan recognition, and natural language processing. We study the complexity of the membership problem for such models, i.e., how difficult it is to determine if a string belongs to a language or not. In particular, we investigate how interleaving can be introduced into models that capture the context-free languages.

Analyzing Matching Time Behavior of Backtracking Regular Expression Matchers by Using Ambiguity of NFA

We apply results from ambiguity of non-deterministic finite automata to the problem of determining the asymptotic worst-case matching time, as a function of the length of the input strings, when attempting to match input strings with a given regular expression, where the matcher being used is a backtracking regular expression matcher.

Analyzing Catastrophic Backtracking Behavior in Practical Regular Expression Matching

We consider in some detail how regular expression matching happens in Java, as a popular representative of the category of regex-directed matching engines. We extract a slightly idealized algorithm ...

On the semantics of regular expression parsing in the wild

We introduce prioritized transducers to formalize capturing groups in regular expression matching in a way that permits straightforward modelling of and comparison with real-world regular expression matching library behaviors. The broader questions of parsing semantics and performance are discussed, and also the complexity of deciding equivalence of regular expressions with capturing groups.

Cuts in Regular Expressions

Most software packages with regular expression matching engines offer operators that extend the classical regular expressions, such as counting, intersection, complementation, and interleaving. Some of the most popular engines, for example those of Java and Perl, also provide operators that are intended to control the nondeterminism inherent in regular expressions. We formalize this notion in the form of the cut and iterated cut operators. They do not extend the class of languages that can be defined beyond the regular, but they allow for exponentially more succinct representation of some languages. Membership testing remains polynomial, but emptiness testing becomes PSPACE-hard.

Uniform vs. Nonuniform Membership for Mildly Context-Sensitive Languages: A Brief Survey

Parsing for mildly context-sensitive language formalisms is an important area within natural language processing. While the complexity of the parsing problem for some such formalisms is known to be polynomial, this is not the case for all of them. This article presents a series of results regarding the complexity of parsing for linear context-free rewriting systems and deterministic tree-walking transducers. We discuss the difference between uniform and nonuniform complexity measures and how parameterized complexity theory can be used to investigate how different aspects of the formalisms influence how hard the parsing problem is. The main results we survey are all hardness results and indicate that parsing is hard even for relatively small values of parameters such as rank and fan-out in a rewriting system.

On the Semantics of Regular Expression Parsing in the Wild

We introduce prioritized transducers to formalize capturing groups in regular expression matching in a way that permits straightforward modelling of and comparison with real-world regular expression matching library behaviors. The broader questions of parsing semantics and performance are discussed, and also the complexity of deciding equivalence of regular expressions with capturing groups.

Shuffled languages : representation and recognition

Language models that use interleaving, or shuffle, operators have applications in various areas of computer science, including system verification, plan recognition, and natural language processing ...

Formalising Boost POSIX Regular Expression Matching

Whereas Perl-compatible regular expression matchers typically exhibit some variation of leftmost-greedy semantics, those conforming to the posix standard are prescribed leftmost-longest semantics. However, the posix standard leaves some room for interpretation, and Fowler and Kuklewicz have done experimental work to confirm differences between various posix matchers. The Boost library has an interesting take on the posix standard, where it maximises the leftmost match not with respect to subexpressions of the regular expression pattern, but rather, with respect to capturing groups. In our work, we provide the first formalisation of Boost semantics, and we analyse the complexity of regular expression matching when using Boost semantics.