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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
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
NA 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
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
A Gentle Introduction to Programming (A. Cumming)
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Author(s):
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
How to Think Like a Computer Scientist
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Author(s):
Pages
Patterns for Adaptive Programming (AP)
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Author(s):
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