Search Results for "backtracking"

RE2/J is a high-performance regular expression engine implemented in pure Java as a port of Google’s C++ RE2 library. Unlike traditional regex engines such as Java’s java.util.regex, PCRE, or Perl’s implementation—which rely on backtracking and can suffer from catastrophic exponential runtimes—RE2/J guarantees linear-time matching relative to input size. It achieves this efficiency by simulating all possible matches in a single pass using a nondeterministic finite automaton (NFA), ensuring predictable and safe performance even with complex patterns. This makes RE2/J ideal for applications that must handle user-supplied regular expressions securely without the risk of denial-of-service through regex backtracking. ...

RE2 is a fast, safe, thread-friendly alternative to backtracking regular expression engines like those used in PCRE, Perl, and Python. It is a C++ library. This is the source code repository for RE2, a regular expression library. There is a fair amount of documentation (including code snippets) in the re2.h header file. Unless otherwise noted, the RE2 source files are distributed under the BSD-style license found in the LICENSE file.

Angstrom is a parser-combinator library in OCaml designed for high-performance applications. It provides monadic and applicative interfaces for composing parsers and supports incremental input processing. ​

Tool to transcribe Parsing Expression Grammar into a parser written in Java. Parsing Expression Grammar (PEG) is a way to specify recursive-descent parsers with limited backtracking. The use of backtracking lifts the LL(1) restriction usually imposed by top-down parsers. In addition, PEG can define parsers with integrated lexing. Unlike some existing parser generators for PEG, the tool does not produce a complex and storage-hungry "packrat parser", but a collection of transparent recursive procedures. ...

...The material covers arrays, linked lists, stacks, queues, recursion, sorting, binary search, hash tables, strings, trees, heaps, and graphs. More advanced examples address backtracking, divide-and-conquer methods, dynamic programming, shortest paths, topological sorting, caches, and priority queues. Solutions are available across numerous languages, including C, C++, Java, Go, Python, JavaScript, Rust, Swift, Kotlin, and TypeScript. This multilingual layout helps learners compare syntax and implementation choices while studying the same concepts. ...

The subgraph matching problem (subgraph isomorphism) is NP-complete. Previously, we designed an exact subgraph matching (ESM) algorithm for dependency graphs using a backtracking approach (http://esmalgorithm.sourceforge.net). We further designed an approximate subgraph matching (ASM) algorithm that is capable of detecting approximate subgraph matching based on a subgraph distance. Assume that the graph G and the subgraph Gs have m and n vertices, and km and kn edges respectively, the total worst-case algorithm complexity is O(m^n * n(n-1)/2 * km * log m). ...

The subgraph matching problem (subgraph isomorphism) is NP-complete. We designed a simple exact subgraph matching (ESM) algorithm for dependency graphs using a backtracking approach. The total worst-case algorithm complexity is O(n^2 * k^n) where n is the number of vertices and k is the vertex degree. We have demonstrated the successful usage of our algorithm in three biomedical relation and event extraction applications: BioNLP 2011 shared tasks on event extraction, Protein-Residue association detection and Protein-Protein interaction identification. ...