String (computer science)

About: String (computer science) is a research topic. Over the lifetime, 19430 publications have been published within this topic receiving 333247 citations. The topic is also known as: str & s.

Functional unparsing

Abstract: A string-formatting function such as printf in C seemingly requires dependent types, because its control string determines the rest of its arguments. Examples:formula hereWe show how changing the representation of the control string makes it possible to program printf in ML (which does not allow dependent types). The result is well typed and perceptibly more efficient than the corresponding library functions in Standard ML of New Jersey and in Caml.

Directed Replacement

Abstract: This paper introduces to the finite-state calculus a family of directed replace operators In contrast to the simple replace expression, UPPER -> LOWER, defined in Karttunen (ACL-95), the new directed version, UPPER @-> LOWER, yields an unambiguous transducer if the lower language consists of a single string It transduces the input string from left to right, making only the longest possible replacement at each point A new type of replacement expression, UPPER @-> PREFIX SUFFIX, yields a transducer that inserts text around strings that are instances of UPPER The symbol denotes the matching part of the input which itself remains unchanged PREFIX and SUFFIX are regular expressions describing the insertions Expressions of the type UPPER @-> PREFIX SUFFIX may be used to compose a deterministic parser for a ``local grammar'' in the sense of Gross (1989) Other useful applications of directed replacement include tokenization and filtering of text streams

Genax: a genome sequencing accelerator

Abstract: Genomics can transform health-care through precision medicine. Plummeting sequencing costs would soon make genome testing affordable to the masses. Compute efficiency, however, has to improve by orders of magnitude to sequence and analyze the raw genome data. Sequencing software used today can take several hundreds to thousands of CPU hours to align reads to a reference sequence. This paper presents GenAx, an accelerator for read alignment, a time-consuming step in genome sequencing. It consists of a seeding and seed-extension accelerator. The latter is based on an innovative automata design that was designed from the ground-up to enable hardware acceleration. Unlike conventional Levenshtein automata, it is string independent and scales quadratically with edit distance, instead of string length. It supports critical features commonly used in sequencing such as affine gap scoring and traceback. GenAx provides a throughput of 4,058K reads/s for Illumina 101 bp reads. GenAx achieves 31.7x speedup over the standard BWA-MEM sequence aligner running on a 56--thread dualsocket 14-core Xeon E5 server processor, while reducing power consumption by 12 x and area by 5.6 x.

Practical Private DNA String Searching and Matching through Efficient Oblivious Automata Evaluation

Abstract: In [18] it was shown that the ability to perform oblivious automata evaluation was useful for performing DNA searching and matching. By oblivious automata evaluation we mean that one participant has a finite state machine and the other participant has a sequence, and at the end of the protocol the sequence owner learns whether the machine accepts the sequence. A protocol was given in [18], but it required O (n ) rounds (where n is the number of characters in the sequence) and O (mn ) modular exponentiations (where m is the number of states in the automata). Both of these factors limit the applicability of this approach. In this paper we propose a new protocol that requires only O (1) rounds and reduces the number of modular exponentiations to O (n ) without revealing any additional information. We have implemented both schemes and have shown experimentally that our scheme is two to three orders of magnitude faster than the previous scheme.