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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.


Papers
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Journal ArticleDOI
01 Feb 2014
TL;DR: Based on the presented techniques, Stranger, an automata-based string analysis tool for detecting string-related security vulnerabilities in PHP applications is implemented and able to detect known/unknown vulnerabilities, and prove the absence of vulnerabilities with respect to given attack patterns.
Abstract: Verifying string manipulating programs is a crucial problem in computer security. String operations are used extensively within web applications to manipulate user input, and their erroneous use is the most common cause of security vulnerabilities in web applications. We present an automata-based approach for symbolic analysis of string manipulating programs. We use deterministic finite automata (DFAs) to represent possible values of string variables. Using forward reachability analysis we compute an over-approximation of all possible values that string variables can take at each program point. Intersecting these with a given attack pattern yields the potential attack strings if the program is vulnerable. Based on the presented techniques, we have implemented Stranger, an automata-based string analysis tool for detecting string-related security vulnerabilities in PHP applications. We evaluated Stranger on several open-source Web applications including one with 350,000+ lines of code. Stranger is able to detect known/unknown vulnerabilities, and, after inserting proper sanitization routines, prove the absence of vulnerabilities with respect to given attack patterns.

66 citations

Journal ArticleDOI
26 May 2017
TL;DR: The proposed control method solves an optimization problem and achieves a controller that is able to provide not only the system stability, but also the string stability as distinct from the traditional $H_{\infty }$ control.
Abstract: Autonomous vehicle following systems are playing a decisive role to increase vehicle density on roads by shortening intervehicle time gaps However, disturbance attenuation along a platoon of vehicles, ie, string stability, is being a challenging task while time gap is getting shorter In order to guarantee the string stability of a vehicle platoon, a multiobjective $H_{\infty }$ control formulation for adaptive cruise control and cooperative adaptive cruise control structures has been investigated in this paper The proposed control method solves an optimization problem and achieves a controller that is able to provide not only the system stability, but also the string stability as distinct from the traditional $H_{\infty }$ control

66 citations

Patent
Nima Mokhlesi1
13 Nov 2006
TL;DR: In this article, the boost structures are provided for individual NAND strings and can be individually controlled to assist in programming, verifying and reading processes, and boost structures can be commonly boosted and individually discharged, in part, based on a target programming state or verify level.
Abstract: A non-volatile memory having boost structures. Boost structures are provided for individual NAND strings and can be individually controlled to assist in programming, verifying and reading processes. The boost structures can be commonly boosted and individually discharged, in part, based on a target programming state or verify level. The boost structures assists in programming so that the programming and pass voltage on a word line can be reduced, thereby reducing side effects such as program disturb. During verifying, all storage elements on a word line can be verified concurrently. The boost structure can also assist during reading. In one approach, the NAND string has dual source-side select gates between which the boost structure contacts the substrate at a source/drain region, and a boost voltage is provided to the boost structure via a source-side of the NAND string.

66 citations

Patent
26 Aug 2004
TL;DR: In this article, a system and method of recognizing characters in a captured image, including selecting a portion of the image encompassing a string of characters in the captured image to be recognized.
Abstract: A system and method of recognizing characters in a captured image, includes selecting a portion of the image encompassing a string of characters in the captured image to be recognized. The selected portion is examined to identify segments that potentially include the characters of the string. During the examining multiple tests on pixels in the selected portion are performed. The identified segments are then examined to recognize the string of characters.

66 citations

Journal ArticleDOI
TL;DR: The main contribution of this paper is to introduce automata equivalent to PSTs but having the following properties: Learning the automaton, for any L, takes O (n) time, and prediction of a string of m symbols by the Automaton takes O(m) time.
Abstract: Statistical modeling of sequences is a central paradigm of machine learning that finds multiple uses in computational molecular biology and many other domains. The probabilistic automata typically built in these contexts are subtended by uniform, fixed-memory Markov models. In practice, such automata tend to be unnecessarily bulky and computationally imposing both during their synthesis and use. Recently, D. Ron, Y. Singer, and N. Tishby built much more compact, tree-shaped variants of probabilistic automata under the assumption of an underlying Markov process of variable memory length. These variants, called Probabilistic Suffix Trees (PSTs) were subsequently adapted by G. Bejerano and G. Yona and applied successfully to learning and prediction of protein families. The process of learning the automaton from a given training set S of sequences requires theta(Ln2) worst-case time, where n is the total length of the sequences in S and L is the length of a longest substring of S to be considered for a candidate state in the automaton. Once the automaton is built, predicting the likelihood of a query sequence of m characters may cost time theta(m2) in the worst case. The main contribution of this paper is to introduce automata equivalent to PSTs but having the following properties: Learning the automaton, for any L, takes O (n) time. Prediction of a string of m symbols by the automaton takes O (m) time. Along the way, the paper presents an evolving learning scheme and addresses notions of empirical probability and related efficient computation, which is a by-product possibly of more general interest.

66 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
20222
2021491
2020704
2019759
2018816
2017806