Concepts, Techniques, and Models of Computer Programming (P. Roy, S. Harid, PDF, 939p) Mirror
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Concepts, Techniques, and Models of Computer Programming (P. Roy, S. Harid, PDF, 939p) Mirror
Concepts, Techniques, and Models of Computer Programming (P. Roy, S. Harid, PDF, 939p) Mirror
This book covers the following
topics: Introduction to Programming,
General Computation Models, Declarative Programming Techniques, Declarative
Concurrency, Relational Programming, Object-Oriented Programming, Encapsulated
State, Concurrency and State, Specialized Computation Models, Semantics and
Virtual Machines.
This note covers the following
topics: Sphere Packing and Shannon’s Theorem, Linear Codes, Hamming Codes,
Generalized Reed-Solomon Codes, Modifying Codes, Codes over Subfields, Cyclic
Codes, Weight and Distance Enumeration.
Coding theory includes the study of compression codes which enable us
to send messages cheaply and error correcting codes which ensure that messages
remain legible even in the presence of errors. Topics covered includes: Codes
and alphabets, Huffman’s algorithm, Shannon’s noiseless coding theorem , Hamming’s breakthrough, Shannon’s noisy coding theorem , Linear codes,
Polynomials and fields , Cyclic codes, Stream ciphers, Asymmetric systems,
Commutative public key systems, Trapdoors and signatures.
This note covers the following
topics: Basic codes and constructions, Algebraic Geometry Codes, Limits on
Performance of Codes, Algebraic decoding, Algebraic decoding, Linear time
decoding, Decoding from random errors and erasures, Applications in complexity
theory and Complexity results in coding theory.
This note introduces the theory of
error-correcting codes to computer scientists. This theory, dating back to the
works of Shannon and Hamming from the late 40's, overflows with theorems,
techniques, and notions of interest to theoretical computer scientists. The
course will focus on results of asymptotic or algorithmic significance.
Principal topics include: Construction and existence results for
error-correcting codes, Limitations on the combinatorial performance of
error-correcting codes, Decoding algorithms, Applications in computer science.
This book
emphasizes the role of computer languages as vehicles for expressing knowledge
and it presents basic principles of abstraction and modularity, together with
essential techniques for designing and implementing computer languages.
This book provides a practitioner's guide for students, programmers,
engineers, and scientists who wish to design and build efficient and
cost-effective programs for parallel and distributed computer systems. It covers
the following topics: Parallel Computers and Computation, Designing Parallel
Algorithms, Quantitative Basis for Design, Putting Components Together, Tools,
Fortran M, High Performance Fortran, Message Passing Interface and Performance
Tools.