This PDF Programming Fundamentals covers the following topics related to Programing Theory : Introduction to Programming Systems, Data and Operators, Functions, Conditions, Loops, Arrays, Strings and Files, Object-Oriented Programming.

**Author(s):** Kenneth Leroy Busbee, Dave
Braunschweig

This note explains the following topics: Text Compression, Error Detection and Correction, Cryptography, Finite State Machines, Recursion and Induction, Relational Database.

**Author(s):** Jayadev Misra

This note explains the following topics: Linear Codes, Bounds, Asymptotic Bounds and Shannon’s Theorem, Constructing Codes from Other Codes, Generalized Reed-Solomon Codes, Asymptotically Good Codes, Local Decodability, List Decoding, Hard Problems in Coding Theory, The Nearest Codeword Problem and NP-Completeness.

**Author(s):** Yehuda Lindell

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.

**Author(s):** J.I.Hall

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

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

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.

**Author(s):** Enes Pasalic

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.

**Author(s):** Madhu Sudan

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

This book explains the following topics: Linear Codes, Probability as Fancy Counting and the q-ary Entropy Function, Combinatorics, The Greatest Code of Them All: Reed-Solomon Codes, What Happens When the Noise is Stochastic: Shannon's Theorem, Bridging the Gap Between Shannon and Hamming: List Decoding, Code Constructions, Code Concatenation, Algorithms, Decoding Concatenated Codes, Efficiently Achieving the Capacity of the BSCp, Efficient Decoding of Reed-Solomon Codes, Efficiently Achieving List Decoding Capacity, Applications.

**Author(s):** Venkatesan Guruswami, Atri Rudra and Madhu
Sudan

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

Covered topics are: Text Compression, Error Detection and Correction, Cryptography, Finite State Machines, Recursion and Induction, Relational Database, String Matching and Parallel Recursion.

**Author(s):** Jayadev Misra

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

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

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

This book covers the following topics: Computer Architecture, Functions, Files, Reading and Writing Simple Records, Developing Robust Programs, Sharing Functions with Code Libraries, Intermediate Memory Topics, High-Level Languages and Optimization.

**Author(s):** Jonathan
Bartlett

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**Author(s):**

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.

**Author(s):** Hal Abelson and Gerald Jay Sussman

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.

**Author(s):** Ian
Foster

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.

**Author(s):** P. Van Roy and S. Haridi

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This book explores and celebrates the Art of Computer Programming. It covers the following topics: Thinking about Thinking, Thinking about Programming, The Programmer at Work, Customs and Practices, Design Principles, Prudence and Safety, Some Weird Stuff.

**Author(s):** Alan
G Carter

Simple Sequences, The Raw Materials, Loops, Branching, Modules & Functions, Handling Files, Handling Text, Error Handling, Regular Expressions, Object Oriented Programming, Event Driven Programming, GUI Programming, Recursion, Python in Practice, Working with Databases, Using the Operating System, Inter-process communications and Network programming.

**Author(s):** Alan
Gauld

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