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Theoretical computer science (TCS) is a subset of general computer science and mathematics Starting from an initial state and initial input (perhaps empty), the instructions describe a computation that, The book prescribes step-by-step procedures for constructing geometric objects like altars using a peg and chord.‎Topics · ‎Automata theory · ‎Computational · ‎Information theory.
Table of contents

All papers introducing or studying mathematical, logic and formal concepts and methods are welcome, provided that their motivation is clearly drawn from the field of computing. Any queries about submissions and peer review should be addressed to the TCS editorial office: tcs elsevier. Papers published in Theoretical Computer Science are grouped in three sections according to their nature. It includes the whole field of abstract complexity i. All formal methods treating these problems are published in this section, including rewriting techniques, abstract data types, automatic theorem proving, calculi such as SCP or CCS, Petri nets, new logic calculi and developments in categorical methods.

The third section, 'Natural Computing', is devoted to the study of computing occurring in nature and computing inspired by nature. In the rapidly evolving field of computer science , natural computing plays an important role as the catalyst for the synergy of human designed computing with the computing going on in nature. This synergy leads to a deeper and broader understanding of the nature of computation. Although natural computing is concerned also with experiments and applications, this section of Theoretical Computer Science is focused on the theoretical aspects of natural computing with clear relevance to computing.

Among others, it will contain papers dealing with the theoretical issues in evolutionary computing, neural networks, molecular computing, and quantum computing. Theoretical Computer Science will now publish high-quality advanced introductions. Advanced introductions should cover a focused topic within the scope of TCS at a level that would be appropriate for a scientist who is new to the topic and wishes to gain an up-to-date understanding.

Sufficient references should be given to provide the reader with entry points to the research literature on the topic as well as the origins of the main ideas. Submissions will be judged on the quality of the content and presentation as well as the timeliness of the topic. Since 1st September , we have made over , archived mathematics articles freely available to the mathematics community.

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Introduction to Programming in Java.

ISSN: Theoretical Computer Science. Editors-in-Chief: D. Spirakis, - TCS-A. View Editorial Board.

Submit Your Paper. Supports Open Access. Forward Looking Huffman Coding. On the Complexity of Restarting. On the Complexity of Mixed Dominating Set. Transition Property for Cube-Free Words. Unpopularity Factor in the Marriage and Roommates Problems. Back Matter Pages Editors and affiliations. Novosibirsk State University Novosibirsk Russia 2. Everybody should have the skill of thinking computationally. Exactly, for kids the easiest way is to use visual software. You drag and drop something and immediately you see the results and what changes.

If we widen this to anybody with an interest in learning how to program, regardless of their age and their higher education background, how hard would you say this is? Would you agree with that or do you think that pursuing a proper university degree will make you a better programmer? If you only want to learn how to program, you can definitely do that by yourself. Even young children can learn how to program.

You need to always expose yourself to that, through coding practice, lectures, chatting with somebody, or visually drawing out ideas. I think a course or something more formal would be necessary to understand algorithms. Another common view is that programming is difficult to learn later in life.

Do you have any experience with people managing to learn it in their fifties or sixties?

Computer Science – Theory and Applications

The biological aspect is obvious of course: it becomes harder to learn anything as you grow older. Biology is one thing, but I think success is more about the person. Is this a nice first step, to check how interested you are in the topic? I picked it because it tells you how a computer works. A lot of times, people think that the monitor is the computer. This book talks about all the chips and the gates, and it goes from a very low level all the way up. It gets you to use your imagination to virtually build a computer. It demystifies the magic of a computer and what it is.

There is no theory involved, rather it presents the components and how they come together. It goes all the way from the chips that make up the computer, up to the peripherals like the screen and keyboard. But the size of things has changed! And then, after this introductory book on programming, if a reader finds they really are interested and want to learn programming, this would be a good point to choose a language. Is that right? Yes, the first book tells you about the hardware. Having eliminated these annoying little things is what makes Python enjoyable to everyone.

European Association for Theoretical Computer Science

The other reason is the push towards data science, and generally working with a lot of data. With Python, you can write easy and quick scripts, without too many pesky language details.


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Usability makes Python a very attractive language. So Python would definitely be your obvious recommendation, or do you see any alternatives out there for beginners? You have a lot more control in those languages and your code becomes much more efficient.

Computational Complexity:

You must have gathered a lot of insights from your experience teaching hundreds of students at MIT. Is there anything in particular that you do in the book, that is sometimes done wrong when it comes to teaching programming?

I focus on getting the reader to understand what computer science is, and getting their head around that way of thinking about things. As humans we can infer things; if someone tells you to make dinner, you know that means going to the kitchen, taking pots and pans, using ingredients, etc. Then the book goes through learning Python, while continuing to stress those points along the way. One final question before we delve into the rest of your selection. Do you think there are still merits to learning computer science with books?

When you have a question, chances are that several people already asked and answered it on sites like StackOverflow. What you can get out of programming books is the thought process behind the ideas. Language takes a back seat to the concepts presented, in the sense that ideas in a book should be universal to any programming language.

They should be relevant to beginners as well as people who have been programming for 20 years, and as relevant today as when people started programming. I tried to focus on books that present this: not books that are language-specific, but books that present ideas you should be aware of, no matter your programming background and what year this is. Your second book is Clean Code by Robert C. This book is going to show you how to write code that is readable by yourself in the future, or by somebody else.

Martin wrote it in a very approachable way, and what I liked when I read it is that it starts talking about code right away.