This note covers
the following topics: Functions, Values and Side Effects, Control and
Higher-Order Functions, Environments and Lambda, Newton's Method and Recursion,
Data Abstraction, Sequences and Iterables, Objects, Lists, and Dictionaries,
Mutable Data Types, Object-Oriented Programming, Inheritance, Generic Functions,
Coercion and Recursive Data, Functional Programming, Declarative Programming,
Unification, MapReduce, Parallelism.

This note
covers the following topics: Introduction to programming, Use of objects and
variables, Definition of methods and classes, Primitive data types, Conditional
statements, Loop statements, Arrays and matrices, Files and input/output
streams, Program errors and exception handling, Recursion, Dynamic arrays and
linked lists.

This book has been written as
lecture notes for students who need a grasp of the basic principles of linear
codes. Topics covered includes: Shannon theory and coding, Coding theory,
Decoding of linear codes and MacWilliams identity, Coding theory - Constructing
New Codes, Coding theory - Bounds on Codes, Reed-Muller codes, Fast decoding of
RM codes and higher order RM codes.

This note covers
the following topics: Functions, Values and Side Effects, Control and
Higher-Order Functions, Environments and Lambda, Newton's Method and Recursion,
Data Abstraction, Sequences and Iterables, Objects, Lists, and Dictionaries,
Mutable Data Types, Object-Oriented Programming, Inheritance, Generic Functions,
Coercion and Recursive Data, Functional Programming, Declarative Programming,
Unification, MapReduce, Parallelism.

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 note covers the following topics: Basic Theories, Basic Data
Structures, Function Theory, Program Theory, Programming Language, Recursive
Definition, Theory Design and Implementation, Concurrency and Interaction.

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.

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.