"Computer Science Logo Style: Beyond Programming" by Brian Harvey is an innovative approach to teaching computer science using the Logo programming language. This book emphasizes the importance of understanding fundamental concepts over rote programming skills. It introduces readers to problem-solving, abstraction, and the principles of programming through fun and engaging exercises. With a focus on graphics, animation, and interactive projects, it encourages creativity and exploration. The book is ideal for learners of all ages, fostering a deeper appreciation for computing and its possibilities, while building a solid foundation in computational thinking. Harvey's educational philosophy challenges traditional paradigms, making learning enjoyable and accessible. [Generated by language model - please report any problems].

This book features in the following series: Computer Science Logo Style, Exploring With Logo .

There are 344 pages in this book.

It is aimed at Young Adult readers. The term Young Adult (YA) is used for books which have the following characteristics: (1) aimed at ages 12-18 years, US grades 7-12, UK school years 8-15, (2) around 50-75k words long, (3) main character is aged 12-18 years, (4) topics include self-reflection, internal conflict vs external, analyzing life and its meaning, (5) point of view is often in the first person, and (6) swearing, violence, romance and sexuality are allowed.

This book was published in 1997 by MIT Press Ltd .

This book has the following chapters: Part 1 Automata theory: what is a computation? finite-state machines; nondeterministic machines; representing machines as Logo lists; text editors - a use for acceptors; regular expressions; rules that aren't regular; regular expressions and finite-state machines; how to translate; making the machine deterministic eliminating redundant states; a finite-state adder; counting and finite-state machines; Turing machines; Turing's thesis; the Halting theorem; proving the Halting theorem in Logo; program listing. Part 2 Discrete mathematics: propositional logic; an inference system; problems with ordering; data structure; program structure - recording simple propositions; program structure - recording implications; using implications to represent orderings; backtracking; generalized inference systems and predicate Logic; Logic and computer hardware; combinatorics; inductive and closed-form definition; Pascal's triangle; simulation; the Simplex Lock problem; an inductive solution; multinominal coefficients; program listing. Part 3 Algorithms and data structure: local optimization versus efficient algorithms; memorization; sorting algorithms; sorting by selection; sorting by particition; order of growth; data structures; data structures in real life; trees; improving the data representation; trees as an abstract data type; tree modification; searching algorithms and trees; Logo's underlying data structure; program listing. Part 4 Programming language design: programming paradigms; interactive and non-interactive languages; block structure; statement types; shuffling a deck using arrays; lexical scope; typed variables; additional types in Standard Pascal; critique of typed variables; procedures and functions; call by value and call by reference; parameters in Logo - call by binding. Part 5 Programming language implementation: formal syntax definition; tokenization; lookahead; parsing; expressions and precedence; the two-stack algorithm for expressions; the simulated machine; stack frames; data structures; code generation; program listing. Part 6 Artificial intelligence: microworlds - Student; how Student translates English algebra; pattern matching; solving the equations; age problem; AI and education; combining sentences into one equation; allowing flexible phrasing; using background knowledge; optional substitutions; if All Else fails; limitations of pattern matching; context-free languages; augmented transition networks; program listing; appendices; bibliography: read these! - automata theory: automata theory; discrete mathematics; algorithms and data structures; programming language design; programming language implementation; artificial intelligence; computers and peoples.