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Journal articles on the topic 'Theoretical foundations of computer science'

Author: Grafiati

Published: 4 June 2025

Last updated: 1 August 2025

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1

Krajíček, Jan. "Hardness assumptions in the foundations of theoretical computer science." Archive for Mathematical Logic 44, no. 6 (2005): 667–75. http://dx.doi.org/10.1007/s00153-005-0279-x.

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2

Farin, G. "Theoretical foundations of computer graphics and CAD." Computer-Aided Design 21, no. 9 (1989): 596–97. http://dx.doi.org/10.1016/0010-4485(89)90023-7.

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3

McClean, Jarrod R., Nicholas C. Rubin, Joonho Lee, et al. "What the foundations of quantum computer science teach us about chemistry." Journal of Chemical Physics 155, no. 15 (2021): 150901. http://dx.doi.org/10.1063/5.0060367.

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With the rapid development of quantum technology, one of the leading applications that has been identified is the simulation of chemistry. Interestingly, even before full scale quantum computers are available, quantum computer science has exhibited a remarkable string of results that directly impact what is possible in a chemical simulation with any computer. Some of these results even impact our understanding of chemistry in the real world. In this Perspective, we take the position that direct chemical simulation is best understood as a digital experiment. While on the one hand, this clarifie

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4

Binkley, Dave, Sebastian Danicic, Tibor Gyimóthy, Mark Harman, Ákos Kiss, and Bogdan Korel. "Theoretical foundations of dynamic program slicing." Theoretical Computer Science 360, no. 1-3 (2006): 23–41. http://dx.doi.org/10.1016/j.tcs.2006.01.012.

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5

Li, Xiaodong, Wenjian Luo, and Xin Yao. "Theoretical foundations of evolutionary computation." Genetic Programming and Evolvable Machines 9, no. 2 (2007): 107–8. http://dx.doi.org/10.1007/s10710-007-9047-5.

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6

Artemov, Sergei, and Anil Nerode. "Special Issue on Logical Foundations of Computer Science." Journal of Logic and Computation 30, no. 1 (2020): 1. http://dx.doi.org/10.1093/logcom/exaa026.

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7

Galinkin, Erick. "Review of The Foundations of Computability Theory (Second Edition) by Borut Robič." ACM SIGACT News 52, no. 2 (2021): 7–9. http://dx.doi.org/10.1145/3471469.3471472.

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Computability theory forms the foundation for much of theoretical computer science. Many of our great unsolved questions stem from the need to understand what problems can even be solved. The greatest question of computer science, P vs. NP, even sidesteps this entirely, asking instead how efficiently we can find solutions for the problems that we know are solvable. For many students both at the undergraduate and graduate level, a first exposure to computability theory follows a standard sequence on data structures and algorithms and students often marvel at the first results they see on undeci

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8

Wu, Yonghao, Minyi Liu, and Jun Li. "Detection and Recognition of Visual Geons Based on Specific Object-of-Interest Imaging Technology." Sensors 25, no. 10 (2025): 3022. https://doi.org/10.3390/s25103022.

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Across domains such as visual processing, computer graphics, neuroscience, and biological sciences, geons are recognized as fundamental components of complex shapes. Their theoretical significance has been extensively acknowledged in scientific research. However, accurately identifying and extracting these structural components remains a persistent challenge. This study integrates theoretical foundations from signal processing, computer graphics, neuroscience, and biological sciences. We employ specific object-of-interest imaging and neural networks to mathematically operationalize visual geon

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Gorrieri, Roberto, and Fabio Martinelli. "Theoretical foundations of security analysis and design II." Theoretical Computer Science 340, no. 1 (2005): 1–2. http://dx.doi.org/10.1016/j.tcs.2005.03.001.

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Lehre, Per Kristian, Aneta Neumann, and Chao Qian. "Special Issue on Theoretical Foundations of Evolutionary Computation." Theoretical Computer Science 950 (March 2023): 113785. http://dx.doi.org/10.1016/j.tcs.2023.113785.

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11

Nielsen, Mogens, and Branislav Rovan. "Introduction—Combined TCSA/TCSB issue—mathematical foundations of computer science 2000." Theoretical Computer Science 340, no. 3 (2005): 457–58. http://dx.doi.org/10.1016/j.tcs.2005.03.010.

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12

Gielen, C. "Neural networks: Theoretical foundations and analysis." Neurocomputing 5, no. 2-3 (1993): 146–47. http://dx.doi.org/10.1016/0925-2312(93)90035-2.

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13

Ferrand, G., W. Lesaint, and A. Tessier. "Theoretical Foundations of Value Withdrawal Explanations for Domain Reduction." Electronic Notes in Theoretical Computer Science 76 (November 2002): 99–114. http://dx.doi.org/10.1016/s1571-0661(04)80788-6.

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14

Banerjee, Mohua, and Mihir K. Chakraborty. "Foundations of Vagueness." Electronic Notes in Theoretical Computer Science 82, no. 4 (2003): 10–19. http://dx.doi.org/10.1016/s1571-0661(04)80701-1.

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15

Budzynska, Katarzyna, Mathilde Janier, Chris Reed, and Patrick Saint-Dizier. "Theoretical foundations for illocutionary structure parsing1." Argument & Computation 7, no. 1 (2016): 91–108. http://dx.doi.org/10.3233/aac-160005.

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16

Buche, C., N. Le Bigot, and M. Polceanu. "Simulation within simulation for agent decision-making: Theoretical foundations from cognitive science to operational computer model." Cognitive Systems Research 40 (December 2016): 46–58. http://dx.doi.org/10.1016/j.cogsys.2016.03.001.

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17

Dell’Aquila, Elena, Michela Ponticorvo, and Pierpaolo Limone. "Psychological Foundations for Effective Human–Computer Interaction in Education." Applied Sciences 15, no. 6 (2025): 3194. https://doi.org/10.3390/app15063194.

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This paper investigates the integration of emotional, cognitive, and interactional processes in the design of educational technologies through the lens of Human–Computer Interaction (HCI). While previous studies have focused on cognitive and interactional engagement, emotional engagement remains underdeveloped in many tools, limiting learning effectiveness. To bridge this gap, this study proposes a theoretical holistic framework integrating usability, emotional intelligence, and adaptive interaction. Through a qualitative analysis, we examine educational platforms—including Duolingo, Khan Acad

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18

G. Kaushik Raj, G. Kaushik Raj. "Quantum Computing." Journal of Software Engineering and Simulation 11, no. 5 (2025): 15–21. https://doi.org/10.35629/3795-11051521.

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Quantum computing performs computations by tapping the very laws that govern quantum mechanics, thereby making those computations far more efficient than does a classical computer. Quantum computers, through qubits and quantum phenomena like superposition, entanglement, and interference, will be able to solve some complex problems in cryptography, chemistry, optimization, and others. This paper discusses core principles and historical development, theoretical foundations of quantum computing, practical implications, and current challenges. However, as research progresses, quantum computing wou

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19

Kruger, Felix, Zabenaso Queen, Ocean Radelva, and Neil Lawrence. "Comparative Analysis of Scientific Approaches in Computer Science: A Quantitative Study." International Transactions on Education Technology (ITEE) 2, no. 2 (2024): 120–28. http://dx.doi.org/10.33050/itee.v2i2.567.

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Computer Science is an interdisciplinary field drawing its foundations from a multitude of scientific and engineering domains. The study of Computer Science necessitates the integration of concepts from various fields, blending theoretical frameworks with practical applications. This dual approach, combining abstraction and design, allows for a comprehensive understanding of computational systems. Over the years, the historical evolution of Computer Science has witnessed the emergence of numerous sub-disciplines that increasingly communicate and overlap, driven by the advancement of communicat

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20

Yang, Dazhi, and Shannon Skelcher. "Improving Teachers' Understanding of Theoretical Foundations of Technology Use." International Journal of Information and Communication Technology Education 15, no. 4 (2019): 113–27. http://dx.doi.org/10.4018/ijicte.2019100108.

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Situated in a theoretical foundations of educational technology course, this study explored how practicing teachers who had not previously taken any formal learning theories courses connected theories with the use of technology. It examined the mindset of teachers after their learning and exposure to learning theories and relevant school of thoughts for a sustained period of time. Results show that teachers showed an appreciation for theories and an awareness for the need of theories in guiding technology use. Teachers also connected theories with technology use. The learning of theories equip

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21

Diaconescu, Răzvan, and Kokichi Futatsugi. "Logical foundations of CafeOBJ." Theoretical Computer Science 285, no. 2 (2002): 289–318. http://dx.doi.org/10.1016/s0304-3975(01)00361-9.

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22

R�hrl, Helmut. "Convexity theories 0. Foundations." Applied Categorical Structures 2, no. 1 (1994): 13–43. http://dx.doi.org/10.1007/bf00878500.

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23

Garifullina, Nadezhda A. "THE INTRODUCTION OF MASSIVE OPEN ONLINE COURSES IN THE EDUCATIONAL PROCESS: NEW PERSPECTIVES FOR TEACHING COMPUTER SCIENCE." EKONOMIKA I UPRAVLENIE: PROBLEMY, RESHENIYA 7/5, no. 148 (2024): 107–17. http://dx.doi.org/10.36871/ek.up.p.r.2024.07.05.013.

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This article discusses the prospects for the introduction of massive open online courses (MOOCs) into the educational process, with an emphasis on teaching computer science. The theoretical foundations of MOOCs, their advantages and challenges are described, as well as new approaches to integrating MOOCs into traditional education are proposed. Examples of successful use of MOOCs and methods for evaluating their effectiveness are given. The article emphasizes the importance of MOOCs for improving the accessibility and quality of education in the field of computer science.

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24

Goldreich, Oded. "Foundations of Cryptography – A Primer." Foundations and Trends™ in Theoretical Computer Science 1, no. 1 (2005): 1–116. http://dx.doi.org/10.1561/0400000001.

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25

Mitrović, Melanija, Mahouton Norbert Hounkonnou, and Marian Alexandru Baroni. "Theory of Constructive Semigroups with Apartness – Foundations, Development and Practice." Fundamenta Informaticae 184, no. 3 (2022): 233–71. http://dx.doi.org/10.3233/fi-2021-2098.

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This paper has several purposes. We present through a critical review the results from already published papers on the constructive semigroup theory, and contribute to its further development by giving solutions to open problems. We also draw attention to its possible applications in other (constructive) mathematics disciplines, in computer science, social sciences, economics, etc. Another important goal of this paper is to provide a clear, understandable picture of constructive semigroups with apartness in Bishop’s style both to (classical) algebraists and the ones who apply algebraic knowled

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26

Meystel, A. "Theoretical foundations of planning and navigation for autonomous robots." International Journal of Intelligent Systems 2, no. 2 (1987): 73–128. http://dx.doi.org/10.1002/int.4550020203.

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27

Katoen, Joost-Pieter. "Conference Reports." ACM SIGLOG News 12, no. 2 (2025): 34. https://doi.org/10.1145/3734192.3734196.

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This edition of SIGLOG News features a report on the 44th edition of Foundations of Software Technology and Theoretical Computer Science (FSTTCS), the premier international computer science conference in India. The first FSTTCS conference was held in 1981. The conference consists of two tracks: Track A focusing on algorithms, complexity and related topics, and Track B, focusing on logic, automata and formal methods. FSTTCS 2024 was organised by IARCS, the Indian Association for Research in Computing Science in association with ACM India. FSTTCS 2024 took place at the IIT Gandhinagar.

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28

Freitas, Endhel Lopes de, Bruno Rabello Monteiro, and Ane Grasiele Gomes de Freitas. "From syllabi to classrooms: a quantitative study of Database teaching in Brazil." Caderno Pedagógico 22, no. 6 (2025): e15845. https://doi.org/10.54033/cadpedv22n6-254.

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This article surveys the teaching of Databases in undergraduate computer science programs using a mixed-methods analysis approach. The content taught aligns with the National Curriculum Guidelines established by Brazil’s Ministry of Education, the training frameworks proposed by the Brazilian Computing Society (SBC), and the Association for Computing Machinery (ACM) curricular recommendations. While the theoretical foundations of Databases date back to the 1970s, new data models, technologies, and evolving computing environments raise relevant questions about the need to review and update thes

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29

Hansen, Michael R., and Zhou Chaochen. "Duration calculus: Logical foundations." Formal Aspects of Computing 9, no. 3 (1997): 283–330. http://dx.doi.org/10.1007/bf01211086.

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30

Hilberdink, Hendrik. "New Foundations for Rewriting Logic." Electronic Notes in Theoretical Computer Science 36 (2000): 43–69. http://dx.doi.org/10.1016/s1571-0661(05)80126-4.

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31

Jürjens, Jan. "Foundations for Designing Secure Architectures." Electronic Notes in Theoretical Computer Science 142 (January 2006): 31–46. http://dx.doi.org/10.1016/j.entcs.2005.07.012.

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32

Keimel, Klaus. "Topological Cones: Foundations for a Domain Theoretical Semantics Combining Probability and Nondeterminism." Electronic Notes in Theoretical Computer Science 155 (May 2006): 423–43. http://dx.doi.org/10.1016/j.entcs.2005.11.066.

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33

Iakushev, Viktor Р., Vladimir M. Bure, Olga А. Mitrofanova, and Evgenii Р. Mitrofanov. "Theoretical foundations of probabilistic and statistical forecasting of agrometeorological risks." Vestnik of Saint Petersburg University. Applied Mathematics. Computer Science. Control Processes 17, no. 2 (2021): 174–82. http://dx.doi.org/10.21638/11701/spbu10.2021.207.

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Еach model for forecasting agrometeorological risks based on the analysis of one-dimensional time series is effective for a certain range of initial information. In addition, the values of the initial observations can differ significantly for each specific case, respectively, the widespread use of one method for the analysis of arbitrary information can lead to significant inaccuracies. Thus, the problem of choosing a forecasting method for the initial set of agrometeorological data arises. In this regard, a universal adaptive probabilistic-statistical approach to predicting agrometeorological

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34

Dwork, Cynthia, and Aaron Roth. "The Algorithmic Foundations of Differential Privacy." Foundations and Trends® in Theoretical Computer Science 9, no. 3-4 (2013): 211–407. http://dx.doi.org/10.1561/0400000042.

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35

Sassone, Vladimiro. "Foundations of Software Science and Computational Structures: Selected papers from FOSSACS 2005." Theoretical Computer Science 390, no. 2-3 (2008): 127–28. http://dx.doi.org/10.1016/j.tcs.2007.09.019.

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36

Wróblewski, Jakub. "Theoretical Foundations of Order-Based Genetic Algorithms." Fundamenta Informaticae 28, no. 3,4 (1996): 423–30. http://dx.doi.org/10.3233/fi-1996-283414.

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37

Researcher. "SOFTWARE ENGINEERING: FOUNDATIONS, PRACTICES, AND FUTURE DIRECTIONS." Journal of Software Engineering (JSE) 2, no. 2 (2024): 43–54. https://doi.org/10.5281/zenodo.14472069.

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Software engineering is a vital discipline that connects the principles of theoretical computer science with the practical demands of software development. Through the use of systematic methods, tools, and frameworks, software engineering ensures the creation of robust, scalable, and efficient software systems tailored to meet diverse user needs. This article provides a comprehensive exploration of the foundations of software engineering, highlighting key methodologies, industry-standard practices, and emerging trends that are shaping its evolution. In addition to discussing these advancements

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38

Mulesa, Pavlo, Roman Momot, and Olena Semenikhina. "CONCEPTUAL FOUNDATIONS FOR PREPARING MATHEMATICS AND COMPUTER SCIENCE TEACHERS FOR THE USE OF VIRTUAL CLARITY MEANS." PEDAGOGY AND EDUCATION MANAGEMENT REVIEW, no. 4 (December 30, 2022): 13–23. http://dx.doi.org/10.36690/2733-2039-2022-4-13.

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In the article, the authors touch on the problem of professional training of teachers of mathematics and computer science in the context of the development of digital technologies and the demand of society for visual support of training. The generalization of scientific and pedagogical research on the training of teachers of mathematics and informatics is presented. The conceptual contradictions of the educational sector, which are proposed to be resolved through the implementation of the author's concept of preparing future teachers of mathematics and computer science for the use of virtual c

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39

Nguyen, Hung T., and Vladik Kreinovich. "Decision science: Foundations and applications introduction to the special issue." International Journal of Intelligent Systems 24, no. 1 (2009): 1–3. http://dx.doi.org/10.1002/int.20326.

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40

Mateus, P., M. Morais, C. Nunes, A. Pacheco, A. Sernadas, and C. Sernadas. "Categorical foundations for randomly timed automata." Theoretical Computer Science 308, no. 1-3 (2003): 393–427. http://dx.doi.org/10.1016/s0304-3975(02)00894-0.

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41

Bozzelli, Laura, and César Sánchez. "Foundations of Boolean stream runtime verification." Theoretical Computer Science 631 (June 2016): 118–38. http://dx.doi.org/10.1016/j.tcs.2016.04.019.

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42

Bruni, Roberto, and José Meseguer. "Semantic foundations for generalized rewrite theories." Theoretical Computer Science 360, no. 1-3 (2006): 386–414. http://dx.doi.org/10.1016/j.tcs.2006.04.012.

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43

Shatyrko, Andriy. "Some methodological aspects of mathematical modeling in dynamic systems." International Science Journal of Engineering & Agriculture 3, no. 1 (2024): 8–14. http://dx.doi.org/10.46299/j.isjea.20240301.02.

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This paper is devoted to methodologies in the field of mathematical foundations of information technology and computer sciences. The theoretical foundations of mathematical modeling of dynamic systems are briefly presented. Various aspects of the concept of a model are considered. The division into types of models is presented. The steps of the mathematical modeling process are detailed. Basic requirements for mathematical models are formulated. The main approaches used in the process of mathematical modeling are described.

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44

Serik, M., G. Nurbekova, and J. Kultan. "Big data technology in education." Bulletin of the Karaganda University. Pedagogy series 100, no. 4 (2020): 8–15. http://dx.doi.org/10.31489/2020ped4/8-15.

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The article discusses the implementation of big data in the educational process of higher education. The authors, analyzing a large amount of data, referring to the types of services provided by e-government, indicate that there are many pressing problems, many services are not yet automated. In order to improve the professional training of teachers of Computer Science of the L.N. Gumilyov Eurasian National University, educational programs and courses have been developed 7M01514 — «Smart City technologies», «Big Data and cloud computing» and 7М01525 — «STEM-Education», «The Internet of Things

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45

Wu, Ruoqi. "Exploring The Foundations and Applications of Cosmological Simulation." Highlights in Science, Engineering and Technology 112 (August 20, 2024): 297–307. http://dx.doi.org/10.54097/5ybdpm75.

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This paper mainly discusses the theoretical basis of cosmology and the methods and techniques used in cosmological simulations. Based on Einstein’s field equation and RW metric, Friedmann’s equation is derived. People developed many universe models based on Friedmann’s equation and came up with many possibilities for the evolution of the universe. With the development of computer science, now people can study cosmology using simulations. Different numerical techniques, such as the Monte Carlo method, Lagrangian method, etc., are used in the simulations. People can easily get access to data tha

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46

Samylkina, N., and A. Salahova. "Artificial Intelligence in Education (AIEd): from Applied Problems of Informatization to Studying a Topic in a Computer Science Course." Profession-Oriented School 9, no. 5 (2021): 10–24. http://dx.doi.org/10.12737/1998-0744-2021-9-5-10-24.

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The article provides an overview of two main possibilities of using artificial intelligence in education: as new educational tools and as the development of the theoretical and practical foundations of artificial intelligence in the school computer science course. A comparison of approaches to the use in education and the study of artificial intelligence issues at the level of secondary general education in different countries is given. The development of the topic at all levels of general education is considered.

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47

Samylkina, N. N. "The main approaches to making the structure and content of the school course of Computer Science more advanced." Science and School, no. 6, 2019 (2019): 171–82. http://dx.doi.org/10.31862/1819-463x-2019-6-171-182.

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The article substantiates the theoretical foundations of building the structure and content of an in-depth school Computer Science course in the context of global integration processes in education. The analysis is made taking into account the main provisions of the state program “Digital Economy of the Russian Federation” and the proposed cross-cutting digital technologies. Approaches to the selection of content and the identification of the basic concepts of the course based on the fundamental directions of science of information science are proposed. At the same time, the hierarchy of compe

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48

S N, Ashwini, Dr M. N. Nachappa та Dr Geetha Madhusudan. "Inheriting the glory of PāṆinian grammar into computer science". INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 08, № 008 (2024): 1–4. http://dx.doi.org/10.55041/ijsrem37286.

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the integration of Pāṇinian grammar principles into computer science represents a significant advancement in computational linguistics and natural language processing. Pāṇini, an ancient Indian grammarian, formulated an elaborate system of grammar known as Aṣṭādhyāyī around the 4th century BCE, which has been revered for its systematic and concise rules governing Sanskrit language structure. In recent years, there has been a growing interest in adapting Pāṇinian principles to enhance computational frameworks for understanding human languages. This paper explores the theoretical foundations of

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49

Diaconescu, Răzvan. "Foundations of Behavioural Specification in Rewriting Logic." Electronic Notes in Theoretical Computer Science 4 (1996): 226–45. http://dx.doi.org/10.1016/s1571-0661(04)00041-6.

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50

Hirsch, Robin, Marcel Jackson, and Tomasz Kowalski. "Algebraic foundations for qualitative calculi and networks." Theoretical Computer Science 768 (May 2019): 99–116. http://dx.doi.org/10.1016/j.tcs.2019.02.033.

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