Theoretical Aspects of Computing

This volume contains the proceedings of the 28th international conference on the Foundations of Software Technology and Theoretical Computer Science (FSTTCS 2008), organized under the auspices of the Indian Association for Research in Computing Science (IARCS). This year's conference attracted 117 submissions. Each submission was reviewed by at least three independent referees. The nal selection of the papers making up the programme was done through an electronic discussion on EasyChair, spanning two weeks, without a physical meeting of the Programme Committee (PC).

Science and technology have been improving rapidly, and it changed everything. Today, very seldom we can find a super computer as in the late 1970s. The computing, processing of data rely on a server or multiple servers depending on the need of a firm or a company. Everything became smaller, a server is just a little bigger than a personal computer (PC), and we have many different programming languages for developing software applications. The subject, concept of Automata and Computing Theories was introduced in 1979, and in those early years, Automata, Computing Theory, and Language Theory were still listed as an area of active research, based heavily in Mathematics and largely a graduate course [1].

2016

Computer science is the study of computers and programs, the collections of instructions that direct the activity of computers. Although computers are made of simple elements, the tasks they perform are often very complex. The great disparity between the simplicity of computers and the complexity of computational tasks offers intellectual challenges of the highest order. It is the models and methods of analysis developed by computer science to meet these challenges that are the subject of theoretical computer science. Computer scientists have developed models for machines, such as the random-access and Turing machines; for languages, such as regular and context-free languages; for programs, such as straight-line and branching programs; and for systems of programs, such as compilers and operating systems. Models have also been developed for data structures, such as heaps, and for databases, such as the relational and object-oriented databases. Methods of analysis have been developed to study the efficiency of algorithms and their data structures, the expressibility of languages and the capacity of computer architectures to recognize them, the classification of problems by the time and space required to solve them, their inherent complexity, and limits that hold simultaneously on computational resources for particular problems. This book examines each of these topics in detail except for the first, analysis of algorithms and data structures, which it covers only briefly. This chapter provides an overview of the book. Except for the mathematical preliminaries, the topics introduced here are revisited later.

The objective of CACIC is to provide a forum within which to promote the development of Computer Science as an academic discipline with industrial applications, trying to extend the frontier of both the state of the art and the state of the practice. The main audience for, and participants in, CACIC are seen as researchers in academic departments, laboratories and industrial software organizations. CACIC started in 1995 as a Congress organized by the Network of National Universities with courses of study in Computer Science (RedUNCI), and each year it is hosted by one of these Universities. RedUNCI has a permanent Web site where its history and organization are described: http:// redunci.info.unlp.edu.ar. CACIC 2011 in La Plata CACIC'11 was the seventeenth Congress in the CACIC series. It was organized by the School of Computer Science of the University of La Plata. The Congress included 11 Workshops with 148 accepted papers, 3 main Conference, 4 invited tutorials, different meetings related with Computer Science Education (Professors, PhD students, Curricula) and an International School with 5 courses. (http://www.cacic2011.edu.ar/). CACIC 2011 was organized following the traditional Congress format, with 11 Workshops covering a diversity of dimensions of Computer Science Research. Each topic was supervised by a committee of three chairs of different Universities. The call for papers attracted a total of 281 submissions. An average of 2.5 review reports were collected for each paper, for a grand total of 702 review reports that involved about 400 different reviewers. A total of 148 full papers, involving 393 authors and 77 Universities, were accepted and 25 of them were selected for this book.

GRIN Verlag Publications., Munich, Germany, E-book, 22 pages, ISBN #, 9783668980433, July, 2019, https://m.grin.com/document/491407, 2019

The paper presented an analytical exposition, critical context and integrative conclusion on the discussion on the meaning, significance and potential applications of theoretical foundations of computer science with respect to Algorithms Design and Analysis; Complexity Theory; Turing Machines; Finite Automata; Cryptography; and Machine Learning. An algorithm is any well-defined computational procedure that takes some value or sets of values as input and produces some values or sets of values as output. A Turing machine consists of a finite program, called the finite control, capable of manipulating a linear list of cells, called the tape, using one access pointer, called the head.Cellular automata is an array of finite state machines (inter-related). A universal Turing machine U is a Turing machine that can imitate the behavior of any other Turing machine T. Automata are a particularly simple, but useful, model of computation which were were initially proposed as a simple model for the behavior of neurons. A model of computation is a mathematical abstraction of computers which is used by computer scientists to perform a rigorous study of computation. An automaton with a finite number of states is called a Finite Automaton (FA) or Finite State Machine (FSM). The Church-Turing Thesis states that the Turing machine is equivalent in computational ability to any general mathematical device for computation, including digital computers. The important themes in Theoretical Computer Science (TCS) are efficiency, impossibility results, approximation, central role of randomness, and reductions (NP-completeness and other intractability results).

16th European symposium on programming, ESOP, 2007

16th European Symposium on Programming, ESOP 2007 Held as Part of the Joint European Conferences on Theory and Practics of Software, ETAPS 2007 Braga, Portugal, March 24 - April 1, 2007 Proceedings ... Rocco De Nicola Dipartimento di Sistemi e Informatica Università di Firenze Viale Morgagni 65 50134 Firenze, Italy E-mail: denicola@dsi.unifi.it ... CR Subject Classification (1998): D.3, D.1, D.2, F.3, F.4, E.1 ... LNCS Sublibrary: SL 1 – Theoretical Computer Science and General Issues ... ISSN 0302-9743 ISBN-10 3-540-71314-X Springer Berlin ...

2004

Lecture Notes in Computer Science, 2004

Springer eBooks, 1997

Science has always been used both to explain phenomena in the world and to master everyday problems. A scientific approach to explaining the world and to solving real problems requires systematic foundations -otherwise a field of knowledge should not be called a science. Accordingly, computer science is motivated by the need to explain the nature of information, knowledge, computation, and computers. The field is also strongly influenced by technological progress and commercial impacts. More than in other disciplines, foundations are required to allow for systematic approaches, to introduce formal methods, to verify results, to integrate various fields of application, and last but not least, to operationalize the concepts developed. This volume presents new contributions to the foundations of computer science, with a focus on * theory of formal languages and automata, * computational structures and complexity theory, * distributed systems and Petri nets, * software engineering and verification, * knowledge representation and cognition, * machine learning and neural networks, * robotics, planning, and decision making, * computer science and its social implications. By their contributions to this volume the authors acknowledge the work of Wilfried Brauer on the occasion of his sixtieth birthday. Wilfried Brauer has devoted his scientific life to improving the foundations of computer science by opening up the view to new developments in the area and by critically reviewing the existing foundations. Having a background in pure mathematics (algebra and group theory), he belonged to the first authors contributing to the emerging field of computer science in the 1960s by publishing on the theory of finite automata (transition monoid, cascade decomposition). This work is documented in his well known monograph on automata theory published in 1984. In the 1970s, Brauer pursued his scientific work by studying various types of (nonfinite) automata and formal languages. In those days he extended his field of interest to distributed systems, in particular to Petri nets. Already during his stay in Hamburg in the 1970s and early 1980s, and with enhanced emphasis after moving to Munich in 1985, he contributed to the foundations of artificial intelligence with numerous publications, ambitious research projects, and valuable advice to other researchers in the field. From a methodological perspective, this research includes symbolic representation of knowledge and of processes as well as connectionist and neural net approaches. The topics treated include mathematical foundations and questions of theoretical language

Philosophy of Computing. Themes from IACAP 2019, 2022

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