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Lecture Notes on Programming Theory for Management Information Systems
This note exlains the following toipics: Basic Business Data Analysis, Python as a Basic and Business Calculator, X Y Plots, Simple Data Analysis, Manipulating Data and More Complex Data Analysis, Reading In and Writing Out Text Data, Automating and Managing Information Systems, Managing Files, Managing Collections of Files Directories, Managing Collections of Files Searching and Designing Power Programs.
Author(s): Johnny Wei Bing Lin
140 Pages
Theory in Programming Practice
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
250 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
Coding Theory and Applications
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
154 Pages
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
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
Programming from the Ground Up (J. Bartlett)
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
326 Pages
Designing and Building Parallel Programs (I. Foster)
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
NA Pages
Learning to Program (Alan Gauld)
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
NA Pages
Patterns for Adaptive Programming (AP)
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