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Algorithmic Introduction to 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.
Author(s): Madhu Sudan
NA Pages 
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.
Author(s): T. W. Korner
104 Pages
Introduction to Programming Lectures Notes
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.
Author(s): Prof. Diego Calvanese
NA Pages
Programming Language Concepts Lecture Notes
This note explains the following topics: Object-oriented programming, Data encapsulation with classes, Subclasses and inheritance, Abstract classes, Exception handling, Reflection, Concurrent programming, Functional programming, Logic programming, Scripting languages.
Author(s): Madhavan Mukund
182 Pages
Structure and Interpretation of Computer Programs
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.
Author(s): Amir Kamil
NA Pages
How To Design Programs An Introduction To Programming and Computing (M. Felleisen, et al)
The main focus of this book is the design process that leads from problem statements to well-organized solutions; it deemphasizes the study of programming language details, algorithmic minutiae, and specific application domains. It covers the following topics: Processing Simple Forms of Data, Processing Arbitrarily Large Data, Abstracting Designs, Generative Recursion, Accumulating Knowledge, Changing the State of Variables, Changing Compound Values.
Author(s): Matthias Felleisen, Robert Bruce Findler, Matthew Flatt and Shriram Krishnamurthi
NA Pages
A Practical Theory of Programming (E. Hehner)
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.
Author(s): Eric C.R. Hehner
242 Pages
The Programmers Stone (Alan Colston)
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Learn to Program A Tutorial for the Future Programmer (Chris Pine)
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Programming from Specifications (Carroll Morgan)
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Patterns for Adaptive Programming (AP)
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