Relevant bibliographies by topics / Computer algorithms. Data structures (Computer science)

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers

Academic literature on the topic 'Computer algorithms. Data structures (Computer science)'

Author: Grafiati
Published: 4 June 2021
Last updated: 1 February 2022

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Journal articles on the topic "Computer algorithms. Data structures (Computer science)"

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Manjula, V. "Graph Applications to Data Structures." Advanced Materials Research 433-440 (January 2012): 3297–301. http://dx.doi.org/10.4028/www.scientific.net/amr.433-440.3297.

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This paper presents a topic on Graph theory and its application to data Structures which I consider basic and useful to students in APPLIED MATHEMATICS and ENGINEERING.This paper gives an elementary introduction of Graph theory and its application to data structures. Elements of Graph theory are indispensable in almost all computer Science areas .It can be used in Some areas such as syntactic analysis, fault detection, diagnosis in computers and minimal path problems. The computer representation and manipulation of graph are also discussed so that certain algorithms can be included .A major th
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Taubenfeld, Gadi. "Contention-sensitive data structures and algorithms." Theoretical Computer Science 677 (May 2017): 41–55. http://dx.doi.org/10.1016/j.tcs.2017.03.017.

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Shand, Mark A. "Algorithms for corner stitched data-structures." Algorithmica 2, no. 1-4 (1987): 61–80. http://dx.doi.org/10.1007/bf01840349.

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Delgado-Friedrichs, Olaf. "Data structures and algorithms for tilings I." Theoretical Computer Science 303, no. 2-3 (2003): 431–45. http://dx.doi.org/10.1016/s0304-3975(02)00500-5.

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Laube, Ulrich, and Markus E. Nebel. "Maximum likelihood analysis of algorithms and data structures." Theoretical Computer Science 411, no. 1 (2010): 188–212. http://dx.doi.org/10.1016/j.tcs.2009.09.025.

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Vitter, Jeffrey Scott. "Algorithms and Data Structures for External Memory." Foundations and Trends® in Theoretical Computer Science 2, no. 4 (2006): 305–474. http://dx.doi.org/10.1561/0400000014.

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Franaszek, P. A., P. Heidelberger, D. E. Poff, and J. T. Robinson. "Algorithms and data structures for compressed-memory machines." IBM Journal of Research and Development 45, no. 2 (2001): 245–58. http://dx.doi.org/10.1147/rd.452.0245.

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Prokop, Yu V., O. H. Trofymenko, and O. V. Dykyi. "RESEARCH OF APPROACHES TO TEACHING THE COURSE “ALGORITHMS AND DATA STRUCTURES” FOR COMPUTER SCIENCE STUDENTS." Scientific notes of Taurida National V.I. Vernadsky University. Series: Technical Sciences 1, no. 2 (2021): 216–20. http://dx.doi.org/10.32838/2663-5941/2021.2-1/34.

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Knop, A., S. Lovett, S. McGuire, and W. Yuan. "Guest Column." ACM SIGACT News 52, no. 2 (2021): 46–70. http://dx.doi.org/10.1145/3471469.3471479.

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Communication complexity studies the amount of communication necessary to compute a function whose value depends on information distributed among several entities. Yao [Yao79] initiated the study of communication complexity more than 40 years ago, and it has since become a central eld in theoretical computer science with many applications in diverse areas such as data structures, streaming algorithms, property testing, approximation algorithms, coding theory, and machine learning. The textbooks [KN06,RY20] provide excellent overviews of the theory and its applications.
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K, Bhargavi. "Data Dimensionality Reduction Techniques : Review." International Journal of Engineering Technology and Management Sciences 4, no. 4 (2020): 62–65. http://dx.doi.org/10.46647/ijetms.2020.v04i04.010.

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Data science is the study of data. It involves developing methods of recording, storing, and analyzing data to effectively extract useful information. The goal of data science is to gain insights and knowledge from any type of data — both structured and unstructured. Data science is related to computer science, but is a separate field. Computer science involves creating programs and algorithms to record and process data, while data science covers any type of data analysis, which may or may not use computers. Data science is more closely related to the mathematics field of Statistics, which inc
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Dissertations / Theses on the topic "Computer algorithms. Data structures (Computer science)"

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Costa, Andre. "Analytic modelling of agent-based network routing algorithms." Title page, contents and abstract only, 2002. http://web4.library.adelaide.edu.au/theses/09PH/09phc8373.pdf.

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Karras, Panagiotis. "Data structures and algorithms for data representation in constrained environments." Thesis, Click to view the E-thesis via HKUTO, 2007. http://sunzi.lib.hku.hk/hkuto/record/B38897647.

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宋永健 and Wing-kin Sung. "Fast labeled tree comparison via better matching algorithms." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 1998. http://hub.hku.hk/bib/B31239316.

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Sung, Wing-kin. "Fast labeled tree comparison via better matching algorithms /." Hong Kong : University of Hong Kong, 1998. http://sunzi.lib.hku.hk/hkuto/record.jsp?B20229999.

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Jain, Jhilmil Cross James H. "User experience design and experimental evaluation of extensible and dynamic viewers for data structures." Auburn, Ala., 2007. http://repo.lib.auburn.edu/2006%20Fall/Dissertations/JAIN_JHILMIL_3.pdf.

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黎少斌 and Shiao-bun Lai. "Trading off time for space for the string matching problem." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 1996. http://hub.hku.hk/bib/B31214216.

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Lai, Shiao-bun. "Trading off time for space for the string matching problem /." Hong Kong : University of Hong Kong, 1996. http://sunzi.lib.hku.hk/hkuto/record.jsp?B18061795.

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Benjamin, Jim Isaac. "Quadtree algorithms for image processing /." Online version of thesis, 1991. http://hdl.handle.net/1850/11078.

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Mak, Vivian. "Algorithms for proximity problems in the presence of obstacles /." Hong Kong : University of Hong Kong, 1999. http://sunzi.lib.hku.hk/hkuto/record.jsp?B21414944.

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Bae, Sung Eun. "Sequential and Parallel Algorithms for the Generalized Maximum Subarray Problem." Thesis, University of Canterbury. Computer Science and Software Engineering, 2007. http://hdl.handle.net/10092/1202.

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The maximum subarray problem (MSP) involves selection of a segment of consecutive array elements that has the largest possible sum over all other segments in a given array. The efficient algorithms for the MSP and related problems are expected to contribute to various applications in genomic sequence analysis, data mining or in computer vision etc. The MSP is a conceptually simple problem, and several linear time optimal algorithms for 1D version of the problem are already known. For 2D version, the currently known upper bounds are cubic or near-cubic time. For the wider applications, it would
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Books on the topic "Computer algorithms. Data structures (Computer science)"

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Lewis, Harry R. Data structures & their algorithms. HarperCollins Publishers, 1991.

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Algorithms and data structures. Prentice-Hall, 1986.

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Algorithms 2: Data structures and search algorithms. Wiley, 1990.

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Robert, Lafore, ed. Data structures & algorithms in Java. Waite Group Press, 1998.

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Robert, Lafore, ed. Data structures & algorithms in Java. 2nd ed. Sams, 2003.

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Wood, Derick. Data structures, algorithms and performance. Addison-Wesley, 1992.

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Data structures, algorithms, and performance. Addison-Wesley, 1993.

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Antoni, Kreczmar, and Rytter Wojciech, eds. Analysis of algorithms and data structures. Addison-Wesley, 1991.

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Goodrich, Michael T. Data structures and algorithms in C++. 2nd ed. Wiley, 2011.

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1960-, Tamassia Roberto, and Mount David M, eds. Data structures and algorithms in C++. 2nd ed. Wiley, 2011.

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Book chapters on the topic "Computer algorithms. Data structures (Computer science)"

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Italiano, Giuseppe F. "Resilient Algorithms and Data Structures." In Lecture Notes in Computer Science. Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-13073-1_3.

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Erwig, Martin. "Graph algorithms = iteration + data structures?" In Graph-Theoretic Concepts in Computer Science. Springer Berlin Heidelberg, 1993. http://dx.doi.org/10.1007/3-540-56402-0_54.

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Taubenfeld, Gadi. "Contention-Sensitive Data Structures and Algorithms." In Lecture Notes in Computer Science. Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-04355-0_17.

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Hains, Gaétan, and John Mullins. "Array structures and data-parallel algorithms." In Lecture Notes in Computer Science. Springer Berlin Heidelberg, 1996. http://dx.doi.org/10.1007/bfb0024730.

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Devroye, Luc. "Probabilistic analysis of algorithms and data structures." In Lecture Notes in Computer Science. Springer Berlin Heidelberg, 1989. http://dx.doi.org/10.1007/3-540-51542-9_20.

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Bieri, Hanspeter. "Teaching Algorithms and Data Structures: 10 Personal Observations." In Lecture Notes in Computer Science. Springer Berlin Heidelberg, 2003. http://dx.doi.org/10.1007/3-540-36477-3_4.

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Nymeyer, Albert, and Kairong Qian. "Heuristic Search Algorithms Based on Symbolic Data Structures." In Lecture Notes in Computer Science. Springer Berlin Heidelberg, 2003. http://dx.doi.org/10.1007/978-3-540-24581-0_83.

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Brookes, Stephen, and Shai Geva. "Continuous functions and parallel algorithms on concrete data structures." In Lecture Notes in Computer Science. Springer Berlin Heidelberg, 1992. http://dx.doi.org/10.1007/3-540-55511-0_17.

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Chen, Danny Z., and Haitao Wang. "Improved Points Approximation Algorithms Based on Simplicial Thickness Data Structures." In Lecture Notes in Computer Science. Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-19222-7_36.

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Fürlinger, Karl, Colin Glass, Jose Gracia, et al. "DASH: Data Structures and Algorithms with Support for Hierarchical Locality." In Lecture Notes in Computer Science. Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-14313-2_46.

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Conference papers on the topic "Computer algorithms. Data structures (Computer science)"

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Martinez, Cristian A., Carlos Nocera, Diego A. Rodriguez, Ismael Orozco, and Eduardo Xamena. "Teaching practice in algorithms and data structures." In 2017 36th International Conference of the Chilean Computer Science Society (SCCC). IEEE, 2017. http://dx.doi.org/10.1109/sccc.2017.8405106.

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Silva, Davi Bernardo, Rafael de Lima Aguiar, Diogo Steinke Dvconlo, and Carlos N. Silla. "Recent Studies About Teaching Algorithms (CS1) and Data Structures (CS2) for Computer Science Students." In 2019 IEEE Frontiers in Education Conference (FIE). IEEE, 2019. http://dx.doi.org/10.1109/fie43999.2019.9028702.

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King, Jason. "Combining Theory and Practice in Data Structures & Algorithms Course Projects." In SIGCSE '21: The 52nd ACM Technical Symposium on Computer Science Education. ACM, 2021. http://dx.doi.org/10.1145/3408877.3432476.

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Lucas, Joan M. "Illustrating the Interaction of Algorithms and Data Structures Using the Matching Problem." In SIGCSE '15: The 46th ACM Technical Symposium on Computer Science Education. ACM, 2015. http://dx.doi.org/10.1145/2676723.2677212.

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Su, Simon, Edward Zhang, Paul Denny, and Nasser Giacaman. "A Game-Based Approach for Teaching Algorithms and Data Structures using Visualizations." In SIGCSE '21: The 52nd ACM Technical Symposium on Computer Science Education. ACM, 2021. http://dx.doi.org/10.1145/3408877.3432520.

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Zhong, Fay. "Designing Adaptive Learning Objects for Enhanced Student Engagement in Data Structures and Algorithms." In SIGCSE '18: The 49th ACM Technical Symposium on Computer Science Education. ACM, 2018. http://dx.doi.org/10.1145/3159450.3162323.

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Färnqvist, Tommy, and Fredrik Heintz. "Competition and Feedback through Automated Assessment in a Data Structures and Algorithms Course." In ITiCSE '16: Innovation and Technology in Computer Science Education Conference 2016. ACM, 2016. http://dx.doi.org/10.1145/2899415.2899454.

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Kapoor, Amanpreet, and Christina Gardner-Mccune. "Introducing a Technical Interview Preparation Activity in a Data Structures and Algorithms Course." In ITiCSE 2021: 26th ACM Conference on Innovation and Technology in Computer Science Education. ACM, 2021. http://dx.doi.org/10.1145/3456565.3460033.

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Poulsen, Seth. "Using Spatio-Algorithmic Problem Solving Strategies to Increase Access to Data Structures." In ITiCSE '20: Innovation and Technology in Computer Science Education. ACM, 2020. http://dx.doi.org/10.1145/3341525.3394004.

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R.M. Debenham, Evan, and Roberto Solis-Oba. "New Algorithms for Computing Field of Vision over 2D Grids." In 6th International Conference on Computer Science, Engineering And Applications (CSEA 2020). AIRCC Publishing Corporation, 2020. http://dx.doi.org/10.5121/csit.2020.101801.

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The aim of this paper is to propose new algorithms for Field of Vision (FOV) computation which improve on existing work at high resolutions. FOV refers to the set of locations that are visible from a specific position in a scene of a computer game. We summarize existing algorithms for FOV computation, describe their limitations, and present new algorithms which aim to address these limitations. We first present an algorithm which makes use of spatial data structures in a way which is new for FOV calculation. We then present a novel technique which updates a previously calculated FOV, rather th
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