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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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Proceedings ArticleDOI
24 Aug 2011
TL;DR: The string stability of CACC is discussed and its performance with various packet loss ratios, beacon sending frequencies and time headway in simulations is evaluated.
Abstract: Recent development in wireless technology enables communication between vehicles. The concept of Co-operative Adaptive Cruise Control (CACC) — which uses wireless communication between vehicles — aims at string stable behaviour in a platoon of vehicles. “String stability” means any non-zero position, speed, and acceleration errors of an individual vehicle in a string do not amplify when they propagate upstream. In this paper, we will discuss the string stability of CACC and evaluate its performance with various packet loss ratios, beacon sending frequencies and time headway in simulations. The simulation framework is built up with a controller prototype, a traffic simulator, and a network simulator.

104 citations

Journal ArticleDOI
01 Mar 2012
TL;DR: The obtained results indicate that prioritisation based on string distances is more efficient in finding defects than random ordering of the test suite: the test suites prioritized using string distances are moreefficient in detecting the strongest mutants, and, on average, have a better APFD than randomly ordered test suites.
Abstract: Test case prioritisation aims at finding an ordering which enhances a certain property of an ordered test suite. Traditional techniques rely on the availability of code or a specification of the program under test. We propose to use string distances on the text of test cases for their comparison and elaborate a prioritisation algorithm. Such a prioritisation does not require code or a specification and can be useful for initial testing and in cases when code is difficult to instrument. In this paper, we also report on experiments performed on the "Siemens Test Suite", where the proposed prioritisation technique was compared with random permutations and four classical string distance metrics were evaluated. The obtained results, confirmed by a statistical analysis, indicate that prioritisation based on string distances is more efficient in finding defects than random ordering of the test suite: the test suites prioritized using string distances are more efficient in detecting the strongest mutants, and, on average, have a better APFD than randomly ordered test suites. The results suggest that string distances can be used for prioritisation purposes, and Manhattan distance could be the best choice.

104 citations

Journal ArticleDOI
TL;DR: This paper first gives a simple time- and space- optimal algorithm to find all tandem repeats, and then modify it to become a time-and-space-optimal algorithm for finding only the primitive tandem repeats.

103 citations

Journal ArticleDOI
TL;DR: This research proposes a similarity search of malware to detect these variants using novel distance metrics using a distance metric based on the distance between feature vectors of string-based signatures, and implements the distance metrics in a complete malware variant detection system.
Abstract: Static detection of malware variants plays an important role in system security and control flow has been shown as an effective characteristic that represents polymorphic malware. In our research, we propose a similarity search of malware to detect these variants using novel distance metrics. We describe a malware signature by the set of control flowgraphs the malware contains. We use a distance metric based on the distance between feature vectors of string-based signatures. The feature vector is a decomposition of the set of graphs into either fixed size k-subgraphs, or q-gram strings of the high-level source after decompilation. We use this distance metric to perform pre-filtering. We also propose a more effective but less computationally efficient distance metric based on the minimum matching distance. The minimum matching distance uses the string edit distances between programs’ decompiled flowgraphs, and the linear sum assignment problem to construct a minimum sum weight matching between two sets of graphs. We implement the distance metrics in a complete malware variant detection system. The evaluation shows that our approach is highly effective in terms of a limited false positive rate and our system detects more malware variants when compared to the detection rates of other algorithms.

103 citations

Patent
17 Dec 2004
TL;DR: In this article, a string replacement is performed in text using linguistic processing, which identifies the existence of direct or indirect links between the string to be replaced and other strings in the text.
Abstract: String replacement is performed in text using linguistic processing. The linguistic processing identifies the existence of direct or indirect links between the string to be replaced and other strings in the text. Morphological, syntactic, anaphoric, or semantic inconsistencies, which are introduced in strings with the identified direct or indirect links to the string that is to be replaced are detected and corrected.

103 citations


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