Computing

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to very much further sort and understand.

General

A program is many things. It is a piece of text typed by a programmer, it is the directing force that makes the computer do what it does, it is data in the computer's memory, yet it controls the actions performed on this same memory. Analogies that try to compare programs to objects we are familiar with tend to fall short, but a superficially fitting one is that of a machine. The gears of a mechanical watch fit together ingeniously, and if the watchmaker was any good, it will accurately show the time for many years. The elements of a program fit together in a similar way, and if the programmer knows what he is doing, the program will run without crashing.
A computer is a machine built to act as a host for these immaterial machines. Computers themselves can only do stupidly straightforward things. The reason they are so useful is that they do these things at an incredibly high speed. A program can, by ingeniously combining many of these simple actions, do very complicated things. ... When a program works, it is beautiful. The art of programming is the skill of controlling complexity. The great program is subdued, made simple in its complexity.

-- http://eloquentjavascript.net/chapter1.html

Basics

Eric Steven Raymond;

  • Pipe Logic - "In this model, a UNIX pipe acts like a wire, that is, a conductor with parasitic capacitance."
  • Simple Made Easy - Rich Hickey emphasizes simplicity’s virtues over easiness’, showing that while many choose easiness they may end up with complexity, and the better way is to choose easiness along the simplicity path. ]

Reference

Books

News and Blogs

Computation

See also Maths#Logic, Hardware

  • https://en.wikipedia.org/wiki/Theory_of_computation - branch that deals with how efficiently problems can be solved on a model of computation, using an algorithm. The field is divided into three major branches: automata theory and language, computability theory, and computational complexity theory.
  • https://en.wikipedia.org/wiki/Model_of_computation - the definition of the set of allowable operations used in computation and their respective costs. It is used for measuring the complexity of an algorithm in execution time and or memory space: by assuming a certain model of computation, it is possible to analyze the computational resources required or to discuss the limitations of algorithms or computers.
  • https://en.wikipedia.org/wiki/Abstract_machine - abstract machines are often used in thought experiments regarding computability or to analyze the complexity of algorithms (see computational complexity theory). A typical abstract machine consists of a definition in terms of input, output, and the set of allowable operations used to turn the former into the latter. The best-known example is the Turing machine.




People

Automata theory

  • https://en.wikipedia.org/wiki/Automata_theory - the study of abstract machines and automata, as well as the computational problems that can be solved using them. It is a theory in theoretical computer science, under discrete mathematics (a subject of study in both mathematics and computer science). The word automata (the plural of automaton) comes from the Greek word αὐτόματα, which means "self-acting".

Automata theory is closely related to formal language theory. An automaton is a finite representation of a formal language that may be an infinite set. Automata are often classified by the class of formal languages they can recognize. Automata play a major role in theory of computation, compiler construction, artificial intelligence, parsing and formal verification.




  • YouTube: Computers Without Memory - Computerphile - They're called 'Finite State Automata" and occupy the centre of Chomsky's Hierarchy - Professor Brailsford explains the ultimate single purpose computer.



  • https://en.wikipedia.org/wiki/Nested_stack_automaton - a finite automaton that can make use of a stack containing data which can be additional stacks.[1] Like a stack automaton, a nested stack automaton may step up or down in the stack, and read the current symbol; in addition, it may at any place create a new stack, operate on that one, eventually destroy it, and continue operating on the old stack. This way, stacks can be nested recursively to an arbitrary depth; however, the automaton always operates on the innermost stack only.



Cellular automaton

Computability theory

to sort

See also Maths#Type theory

  • https://en.wikipedia.org/wiki/Computability_theory - also called recursion theory, is a branch of mathematical logic, of computer science, and of the theory of computation that originated in the 1930s with the study of computable functions and Turing degrees.

The basic questions addressed by recursion theory are "What does it mean for a function on the natural numbers to be computable?" and "How can noncomputable functions be classified into a hierarchy based on their level of noncomputability?". The answers to these questions have led to a rich theory that is still being actively researched. The field has since grown to include the study of generalized computability and definability.



  • https://en.wikipedia.org/wiki/Recursive_set - a set of natural numbers is called recursive, computable or decidable if there is an algorithm which terminates after a finite amount of time and correctly decides whether or not a given number belongs to the set. A more general class of sets consists of the recursively enumerable sets, also called semidecidable sets. For these sets, it is only required that there is an algorithm that correctly decides when a number is in the set; the algorithm may give no answer (but not the wrong answer) for numbers not in the set. A set which is not computable is called noncomputable or undecidable.
  • https://en.wikipedia.org/wiki/Recursively_enumerable_set - a set S of natural numbers is called recursively enumerable, computably enumerable, semidecidable, provable or Turing-recognizable if: There is an algorithm such that the set of input numbers for which the algorithm halts is exactly S, or equivalently; There is an algorithm that enumerates the members of S. That means that its output is simply a list of the members of S: s1, s2, s3, ... . If necessary, this algorithm may run forever. The first condition suggests why the term semidecidable is sometimes used; the second suggests why computably enumerable is used. The abbreviations r.e. and c.e. are often used, even in print, instead of the full phrase. In computational complexity theory, the complexity class containing all recursively enumerable sets is RE.


  • https://en.wikipedia.org/wiki/Computable_function - the basic objects of study in computability theory. Computable functions are the formalized analogue of the intuitive notion of algorithm. They are used to discuss computability without referring to any concrete model of computation such as Turing machines or register machines. Any definition, however, must make reference to some specific model of computation but all valid definitions yield the same class of functions. Particular models of computability that give rise to the set of computable functions are the Turing-computable functions and the μ-recursive functions.
  • https://en.wikipedia.org/wiki/Turing_degree - or degree of unsolvability of a set of natural numbers measures the level of algorithmic unsolvability of the set. The concept of Turing degree is fundamental in computability theory, where sets of natural numbers are often regarded as decision problems; the Turing degree of a set tells how difficult it is to solve the decision problem associated with the set. That is, to determine whether an arbitrary number is in the given set.



  • The Holy Trinity - "The doctrine of computational trinitarianism holds that computation manifests itself in three forms: proofs of propositions, programs of a type, and mappings between structures. These three aspects give rise to three sects of worship: Logic, which gives primacy to proofs and propositions; Languages, which gives primacy to programs and types; Categories, which gives primacy to mappings and structures. The central dogma of computational trinitarianism holds that Logic, Languages, and Categories are but three manifestations of one divine notion of computation. There is no preferred route to enlightenment: each aspect provides insights that comprise the experience of computation in our lives."
  • Physics, Topology, Logic and Computation: A Rosetta Stone [8] - "In physics, Feynman diagrams are used to reason about quantum processes. In the 1980s, it became clear that underlying these diagrams is a powerful analogy between quantum physics and topology: namely, a linear operator behaves very much like a "cobordism". Similar diagrams can be used to reason about logic, where they represent proofs, and computation, where they represent programs. With the rise of interest in quantum cryptography and quantum computation, it became clear that there is extensive network of analogies between physics, topology, logic and computation. In this expository paper, we make some of these analogies precise using the concept of "closed symmetric monoidal category". We assume no prior knowledge of category theory, proof theory or computer science."




  • https://en.wikipedia.org/wiki/Grzegorczyk_hierarchy - a hierarchy of functions used in computability theory (Wagner and Wechsung 1986:43). Every function in the Grzegorczyk hierarchy is a primitive recursive function, and every primitive recursive function appears in the hierarchy at some level. The hierarchy deals with the rate at which the values of the functions grow; intuitively, functions in lower level of the hierarchy grow slower than functions in the higher levels.





  • Where LISP Fits - [10] - "These simplifications made LISP into a way of describing computable functions much neater than the Turing machines or the general recursive definitions used in recursive function theory. The fact that Turing machines constitute an awkward programming language doesn’t much bother recursive function theorists, because they almost never have any reason to write particular recursive definitions, since the theory concerns recursive functions in general. They often have reason to prove that recursive functions with specific properties exist, but this can be done by an informal argument without having to write them down explicitly. In the early days of computing, some people developed programming languages based on Turing machines; perhaps it seemed more scientific. Anyway, I decided to write a paper describing LISP both as a programming language and as a formalism for doing recursive function theory."



Turing machine

Lambda calculus


Computational complexity



to sort








Architecture

See also Electronics

  • https://www.youtube.com/watch?v=Tg5gJxXBh8s George Dyson on the Origins of the Digital Universe] - The talk focuses on the work done at The Institute for Advanced Study in Princeton New Jersey by such renowned scientists as John von Neumann and Kurt Godel.
  • https://en.wikipedia.org/wiki/Harvard_architecture - a computer architecture with physically separate storage and signal pathways for instructions and data. The term originated from the Harvard Mark I relay-based computer, which stored instructions on punched tape (24 bits wide) and data in electro-mechanical counters. These early machines had data storage entirely contained within the central processing unit, and provided no access to the instruction storage as data. Programs needed to be loaded by an operator; the processor could not initialize itself.


  • https://en.wikipedia.org/wiki/Von_Neumann_architecture - meaning has evolved to be any stored-program computer in which an instruction fetch and a data operation cannot occur at the same time because they share a common bus. This is referred to as the von Neumann bottleneck and often limits the performance of the system. The design of a von Neumann architecture is simpler than the more modern Harvard architecture which is also a stored-program system but has one dedicated set of address and data buses for reading data from and writing data to memory, and another set of address and data buses for fetching instructions.


  • https://en.wikipedia.org/wiki/Modified_Harvard_architecture - a variation of the Harvard computer architecture that allows the contents of the instruction memory to be accessed as if it were data. Most modern computers that are documented as Harvard architecture are, in fact, Modified Harvard architecture.


  • https://en.wikipedia.org/wiki/Flynn's_taxonomy - a classification of computer architectures, proposed by Michael Flynn in 1966.[1][2] The classification system has stuck, and has been used as a tool in design of modern processors and their functionalities.



  • http://opencores.org/projects - main objective is to design and publish core designs under a license for hardware modeled on the Lesser General Public License (LGPL) for software. We are committed to the ideal of freely available, freely usable and re-usable open source hardware.

Instructions

  • https://en.wikipedia.org/wiki/Instruction_set - the part of the computer architecture related to programming, including the native data types, instructions, registers, addressing modes, memory architecture, interrupt and exception handling, and external I/O. An ISA includes a specification of the set of opcodes (machine language), and the native commands implemented by a particular processor.


  • https://en.wikipedia.org/wiki/Machine_code - a set of instructions executed directly by a computer's central processing unit (CPU). Each instruction performs a very specific task, such as a load, a jump, or an ALU operation on a unit of data in a CPU register or memory. Every program directly executed by a CPU is made up of a series of such instructions. Numerical machine code (i.e., not assembly code) may be regarded as the lowest-level representation of a compiled or assembled computer program or as a primitive and hardware-dependent programming language. While it is possible to write programs directly in numerical machine code, it is tedious and error prone to manage individual bits and calculate numerical addresses and constants manually. It is thus rarely done today, except for situations that require extreme optimization or debugging.


  • https://en.wikipedia.org/wiki/Bytecode - also known as p-code (portable code), is a form of instruction set designed for efficient execution by a software interpreter. Unlike human-readable source code, bytecodes are compact numeric codes, constants, and references (normally numeric addresses) which encode the result of parsing and semantic analysis of things like type, scope, and nesting depths of program objects. They therefore allow much better performance than direct interpretation of source code.


  • https://en.wikipedia.org/wiki/Word_(computer_architecture) - term for the natural unit of data used by a particular processor design. A word is basically a fixed-sized group of digits (binary or decimal) that are handled as a unit by the instruction set or the hardware of the processor. The number of digits in a word (the word size, word width, or word length) is an important characteristic of any specific processor design or computer architecture.
  • https://en.wikipedia.org/wiki/Microcode - a layer of hardware-level instructions or data structures involved in the implementation of higher level machine code instructions in central processing units, and in the implementation of the internal logic of many channel controllers, disk controllers, network interface controllers, network processors, graphics processing units, and other hardware. It resides in special high-speed memory and translates machine instructions into sequences of detailed circuit-level operations. It helps separate the machine instructions from the underlying electronics so that instructions can be designed and altered more freely. It also makes it feasible to build complex multi-step instructions while still reducing the complexity of the electronic circuitry compared to other methods. Writing microcode is often called microprogramming and the microcode in a particular processor implementation is sometimes called a microprogram.


  • https://en.wikipedia.org/wiki/Microarchitecture - sometimes abbreviated to µarch or uarch, also called computer organization, is the way a given instruction set architecture (ISA) is implemented on a processor. A given ISA may be implemented with different microarchitectures; implementations may vary due to different goals of a given design or due to shifts in technology. Computer architecture is the combination of microarchitecture and instruction set design.

Processing

  • https://en.wikipedia.org/wiki/Control_unit - a component of a computer's central processing unit (CPU) that directs operation of the processor. It controls communication and co-ordination between input/output devices. It reads and interprets instructions and determines the sequence for processing the data.


  • https://en.wikipedia.org/wiki/Coprocessor - a computer processor used to supplement the functions of the primary processor (the CPU). Operations performed by the coprocessor may be floating point arithmetic, graphics, signal processing, string processing, encryption or I/O Interfacing with peripheral devices. By offloading processor-intensive tasks from the main processor, coprocessors can accelerate system performance. Coprocessors allow a line of computers to be customized, so that customers who do not need the extra performance need not pay for it.
  • https://en.wikipedia.org/wiki/Floating-point_unit - FPU, colloquially a math coprocessor) is a part of a computer system specially designed to carry out operations on floating point numbers. Typical operations are addition, subtraction, multiplication, division, square root, bitshifting. Some systems (particularly older, microcode-based architectures) can also perform various transcendental functions such as exponential or trigonometric calculations, though in most modern processors these are done with software library routines. In a general purpose computer architectures, one or more FPUs may be integrated with the central processing unit; however many embedded processors do not have hardware support for floating-point operations.





DSP

FPGA

ASIC


RISC

RISC-V
  • lowRISC - producing fully open hardware systems. From the processor core to the development board, our goal is to create a completely open computing eco-system. Our open-source SoC (System-on-a-Chip) designs will be based on the 64-bit RISC-V instruction set architecture. Volume silicon manufacture is planned as is a low-cost development board. There are more details on our plans in these slides from a recent talk [31]
  • PULP Platform - What you will get is a competitive, state-of-the-art 32-bit processor based on the RISC-V architecture, with a rich set of peripherals, and full debug support. At ETH Zurich and Universita’ di Bologna we have put many of the ideas that we have developed through our research on ultra-low-power parallel processing (PULP project) into PULPino. It is the little hip brother to its more serious bigger brothers.

CISC

x86



GPU


GPGPU

The Mill

Memory



There are four major storage levels:

  1. Internal – Processor registers and cache.
  2. Main – the system RAM and controller cards.
  3. On-line mass storage – Secondary storage.
  4. Off-line bulk storage – Tertiary and Off-line storage.




  • https://en.wikipedia.org/wiki/Nearline_storage - For example, always-on spinning hard disk drives are online storage, while spinning drives that spin down automatically, such as in massive arrays of idle disks (MAID), are nearline storage.


  • https://en.wikipedia.org/wiki/Address_space - defines a range of discrete addresses, each of which may correspond to a network host, peripheral device, disk sector, a memory cell or other logical or physical entity.





  • https://en.wikipedia.org/wiki/Executable_space_protection - the marking of memory regions as non-executable, such that an attempt to execute machine code in these regions will cause an exception. It makes use of hardware features such as the NX bit, or in some cases software emulation of those features.


  • https://en.wikipedia.org/wiki/Virtual_memory - a memory management technique that is implemented using both hardware and software. It maps memory addresses used by a program, called virtual addresses, into physical addresses in computer memory.


  • https://en.wikipedia.org/wiki/Page_(computer_memory) - memory page, or virtual page is a fixed-length contiguous block of virtual memory, described by a single entry in the page table. It is the smallest unit of data for memory management in a virtual memory operating system.
  • https://en.wikipedia.org/wiki/Page_table - the data structure used by a virtual memory system in a computer operating system to store the mapping between virtual addresses and physical addresses. Virtual addresses are used by the accessing process, while physical addresses are used by the hardware, or more specifically, by the RAM subsystem.
  • https://en.wikipedia.org/wiki/Page_fault - a type of interrupt, called trap, raised by computer hardware when a running program accesses a memory page that is mapped into the virtual address space, but not actually loaded into main memory. When handling a page fault, the operating system generally tries to make the required page accessible at the location in physical memory, or terminates the program in case of an illegal memory access. Contrary to what "fault" might suggest, valid page/hard faults are not errors, and are common and necessary to increase the amount of memory available to programs in any operating system that utilizes virtual memory,


  • http://en.wikipedia.org/wiki/Call_stack - a stack data structure that stores information about the active subroutines of a computer program. This kind of stack is also known as an execution stack, control stack, run-time stack, or machine stack, and is often shortened to just "the stack". Although maintenance of the call stack is important for the proper functioning of most software, the details are normally hidden and automatic in high-level programming languages. Many computer instruction sets provide special instructions for manipulating stacks.

A call stack is used for several related purposes, but the main reason for having one is to keep track of the point to which each active subroutine should return control when it finishes executing.




  • http://en.wikipedia.org/wiki/Pointer_(computer_programming) - a programming language object, whose value refers to (or "points to") another value stored elsewhere in the computer memory using its address. A pointer references a location in memory, and obtaining the value stored at that location is known as dereferencing the pointer.


Storage

Other

Assembly language

  • Rappel - assembly REPL. It works by creating a shell ELF, starting it under ptrace, then continiously rewriting/running the .text section, while showing the register states. It's maybe half done right now, and supports Linux x86, amd64, and armv7 (no thumb) at the moment. [44]


Security

Operating system

See also *nix, Virtualisation, Distros, Android, Windows, Apple

  • OSDev.org - wiki that provides information about the creation of operating systems and serves as a community for those people interested in OS creation

Kernel


  • Mirage OS is a library operating system that constructs unikernels for secure, high-performance network applications across a variety of cloud computing and mobile platforms. Code can be developed on a normal OS such as Linux or MacOS X, and then compiled into a fully-standalone, specialised unikernel that runs under the Xen hypervisor.


Programming




  • Livecoding.tv - A livestreaming platform for coders to share their code and hang out

Syntax


  • https://en.wikipedia.org/wiki/Dyck_language - the language consisting of balanced strings of square brackets [ and ]. It is important in the parsing of expressions that must have a correctly nested sequence of brackets, such as arithmetic or algebraic expressions.
  • https://en.wikipedia.org/wiki/Declaration_(computer_programming) - specifies properties of an identifier: it declares what a word (identifier) means. Declarations are most commonly used for functions, variables, constants, and classes, but can also be used for other entities such as enumerations and type definitions. Beyond the name (the identifier itself) and the kind of entity (function, variable, etc.), declarations typically specify the data type (for variables and constants), or the type signature (for functions); types may also include dimensions, such as for arrays. A declaration is used to announce the existence of the entity to the compiler; this is important in those strongly typed languages that require functions, variables, and constants, and their types to be specified with a declaration before use, and is used in forward declaration. The term "declaration" is frequently contrasted with the term "definition", but meaning and usage varies significantly between languages
  • https://en.wikipedia.org/wiki/Literal_(computer_programming) - a notation for representing a fixed value in source code. Almost all programming languages have notations for atomic values such as integers, floating-point numbers, and strings, and usually for booleans and characters; some also have notations for elements of enumerated types and compound values such as arrays, records, and objects. An anonymous function is a literal for the function type.

In contrast to literals, variables or constants are symbols that can take on one of a class of fixed values, the constant being constrained not to change. Literals are often used to initialize variables, for example, in the following, 1 is an integer literal and the three letter string in "cat" is a string literal: 

int a = 1;
String s = "cat";

In lexical analysis, literals of a given type are generally a token type, with a grammar rule, like "a string of digits" for an integer literal. Some literals are specific keywords, like true for the boolean literal "true". In some object-oriented languages (like ECMAScript), objects can also be represented by literals. Methods of this object can be specified in the object literal using function literals.


Data types

  • https://en.wikipedia.org/wiki/Type_theory - any of a class of formal systems, some of which can serve as alternatives to set theory as a foundation for all mathematics. In type theory, every "term" has a "type" and operations are restricted to terms of a certain type.
  • https://en.wikipedia.org/wiki/Data_type
  • https://en.wikipedia.org/wiki/Type_system - a collection of rules that assign a property called a type to constructs such as variables, expressions, functions or modules—a computer program is composed of. reduces bugs by defining interfaces between different parts of a computer program, and then checking that the parts have been connected in a consistent way. This checking can happen statically (at compile time), dynamically (at run time), or as a combination thereof.


  • https://en.wikipedia.org/wiki/Type_conversion - typecasting, and coercion are different ways of, implicitly or explicitly, changing an entity of one data type into another. This is done to take advantage of certain features of type hierarchies or type representations. One example would be small integers, which can be stored in a compact format and converted to a larger representation when used in arithmetic computations. In object-oriented programming, type conversion allows programs to treat objects of one type as one of their ancestor types to simplify interacting with them.


  • https://en.wikipedia.org/wiki/Type_inference - automatic deduction of the type of an expression in a programming language. If some, but not all, type annotations are already present it is referred to as type reconstruction. The opposite operation of type inference is called type erasure.



  • https://en.wikipedia.org/wiki/Abstract_data_type - a mathematical model for data types where a data type is defined by its behavior (semantics) from the point of view of a user of the data, specifically in terms of possible values, possible operations on data of this type, and the behavior of these operations. This contrasts with data structures, which are concrete representations of data, and are the point of view of an implementer, not a user.


  • https://en.wikipedia.org/wiki/Semaphore_(programming) - a variable or abstract data type that is used for controlling access, by multiple processes, to a common resource in a concurrent system such as a multiprogramming operating system. A trivial semaphore is a plain variable that is changed (for example, incremented or decremented, or toggled) depending on programmer-defined conditions. The variable is then used as a condition to control access to some system resource.


  • https://en.wikipedia.org/wiki/Record_(computer_science) - also called struct or compound data, is a basic data structure. A record is a collection of fields, possibly of different data types, typically in fixed number and sequence. The fields of records may also be called elements, though these risk confusion with elements of a collection, or members, particularly in object-oriented programming. A tuple may or may not be considered a record, and vice versa, depending on conventions and the specific programming language.



  • https://en.wikipedia.org/wiki/Duck_typing - style of typing in which an object's methods and properties determine the valid semantics, rather than its inheritance from a particular class or implementation of a specific interface
  • https://en.wikipedia.org/wiki/Substructural_type_system - family of type systems analogous to substructural logics where one or more of the structural rules are absent or allowed under controlled circumstances. Such systems are useful for constraining access to system resources such as files, locks and memory by keeping track of changes of state that occur and preventing invalid states



Numbers

Data structures

The difference between arrays and linked lists are:

- Arrays are linear data structures. Linked lists are linear and non-linear data structures. - Linked lists are linear for accessing, and non-linear for storing in memory - Array has homogenous values. And each element is independent of each other positions. Each node in the linked list is connected with its previous node which is a pointer to the node. - Array elements can be modified easily by identifying the index value. It is a complex process for modifying the node in a linked list. - Array elements can not be added, deleted once it is declared. The nodes in the linked list can be added and deleted from the list.




Mutability

Polymorphism

Evaluation

An expression evaluates to a value. A statement does something. 

x = 1
y = x + 1     # an expression
print y       # a statement, prints 2

Operators

  • https://en.wikipedia.org/wiki/Operator_(programming) - constructs which behave generally like functions, but which differ syntactically or semantically from usual functions. Common simple examples include arithmetic (addition with +, comparison with >) and logical operations (such as AND or &&). More involved examples include assignment (usually = or :=), field access in a record or object (usually .), and the scope resolution operator (often ::). Languages usually define a set of built-in operators, and in some cases allow user-defined operators.

Functions

  • http://en.wikipedia.org/wiki/Subroutine or function is a sequence of program instructions that perform a specific task, packaged as a unit. This unit can then be used in programs wherever that particular task should be performed. Subprograms may be defined within programs, or separately in libraries that can be used by multiple programs. In different programming languages a subroutine may be called a procedure, a function, a routine, a method, or a subprogram. The generic term callable unit is sometimes used.
  • http://en.wikipedia.org/wiki/Closure_(computer_science) - also lexical closures or function closures are a technique for implementing lexically scoped name binding in languages with first-class functions. Operationally, a closure is a record storing a function[a] together with an environment:[1] a mapping associating each free variable of the function (variables that are used locally, but defined in an enclosing scope) with the value or storage location to which the name was bound when the closure was created.[b] A closure—unlike a plain function—allows the function to access those captured variables through the closure's reference to them, even when the function is invoked outside their scope.


  • http://en.wikipedia.org/wiki/Call_site - a call site of a function or subroutine is the location (line of code) where the function is called (or may be called, through dynamic dispatch). A call site is where zero or more arguments are passed to the function, and zero or more return values are received.


  • http://en.wikipedia.org/wiki/Anonymous_function - also function literal or lambda abstraction is a function definition that is not bound to an identifier. Anonymous functions are often: arguments being passed to higher-order functions, or used for constructing the result of a higher-order function that needs to return a function.

If the function is only used once, or a limited number of times, an anonymous function may be syntactically lighter than using a named function. Anonymous functions are ubiquitous in functional programming languages and other languages with first-class functions, where they fulfill the same role for the function type as literals do for other data types.

  • http://en.wikipedia.org/wiki/Function_type - the type of a variable or parameter to which a function has or can be assigned, or an argument or result type of a higher-order function taking or returning a function.
  • http://en.wikipedia.org/wiki/Function_prototype - or function interface is a declaration of a function that specifies the function's name and type signature (arity, parameter types, and return type), but omits the function body. The term is particularly used in C and C++. While a function definition specifies how the function does what it does (the "implementation"), a function prototype merely specifies its interface, i.e. what data types go in and come out of it.

In a prototype, parameter names are optional (and in C/C++ have function prototype scope, meaning their scope ends at the end of the prototype), however, the type is necessary along with all modifiers (e.g. if it is a pointer or a const parameter). In object-oriented programming, interfaces and abstract methods serve much the same purpose.



  • http://en.wikipedia.org/wiki/Callback_(computer_science) - a piece of executable code that is passed as an argument to other code, which is expected to call back (execute) the argument at some convenient time. The invocation may be immediate as in a synchronous callback, or it might happen at a later time as in an asynchronous callback. In all cases, the intention is to specify a function or subroutine as an entity that is, depending on the language, more or less similar to a variable. Programming languages support callbacks in different ways, often implementing them with subroutines, lambda expressions, blocks, or function pointers.


  • http://en.wikipedia.org/wiki/Tail_call - a subroutine call performed as the final action of a procedure. If a tail call might lead to the same subroutine being called again later in the call chain, the subroutine is said to be tail-recursive, which is a special case of recursion. Tail recursion (or tail-end recursion) is particularly useful, and often easy to handle in implementations.


  • http://en.wikipedia.org/wiki/Function_pointer - Instead of referring to data values, a function pointer points to executable code within memory. When dereferenced, a function pointer can be used to invoke the function it points to and pass it arguments just like a normal function call. Such an invocation is also known as an "indirect" call, because the function is being invoked indirectly through a variable instead of directly through a fixed name or address. Function pointers can be used to simplify code by providing a simple way to select a function to execute based on run-time values.


  • http://en.wikipedia.org/wiki/Funarg_problem - refers to the difficulty in implementing first-class functions (functions as first-class objects) in programming language implementations so as to use stack-based memory allocation of the functions. The difficulty only arises if the body of a nested function refers directly (i.e., not via argument passing) to identifiers defined in the environment in which the function is defined, but not in the environment of the function call. To summarize the discussion below, two standard resolutions are to either forbid such references or to create closures.


Control structures

  • https://en.wikipedia.org/wiki/Generator_(computer_science) - a special routine that can be used to control the iteration behaviour of a loop. In fact, all generators are iterators. A generator is very similar to a function that returns an array, in that a generator has parameters, can be called, and generates a sequence of values. However, instead of building an array containing all the values and returning them all at once, a generator yields the values one at a time, which requires less memory and allows the caller to get started processing the first few values immediately. In short, a generator looks like a function but behaves like an iterator.

Generators can be implemented in terms of more expressive control flow constructs, such as coroutines or first-class continuations. Generators, also known as semicoroutines, are a special case of (and weaker than) coroutines, in that they always yield control back to the caller (when passing a value back), rather than specifying a coroutine to jump to

Algorithms

See also Maths

  • https://en.wikipedia.org/wiki/Algorithmic_information_theory - a subfield of information theory and computer science that concerns itself with the relationship between computation and information. According to Gregory Chaitin, it is "the result of putting Shannon's information theory and Turing's computability theory into a cocktail shaker and shaking vigorously."

Paradigms



Functional

  • λ Lessons - Pattern matching, first-class functions, and abstracting over recursion in Haskell. This is a short, interactive lesson that teaches core functional programming concepts. It was designed to transform the way you think about performing operations on lists of things, by showing you how functions are executed. [89]

Object orientated

Patterns

See also Organisation#Patterns

"ExtremeProgramming -- all programming is maintenance."

MV*

"create your views, express your models or develop a controller"

Libraries

Module pattern

System calls

Process management

Garbage collection

Threads

Concurrency

  • https://en.wikipedia.org/wiki/Concurrent_computing - a form of computing in which several computations are executing during overlapping time periods—concurrently—instead of sequentially (one completing before the next starts). This is a property of a system—this may be an individual program, a computer, or a network—and there is a separate execution point or "thread of control" for each computation ("process"). A concurrent system is one where a computation can make progress without waiting for all other computations to complete—where more than one computation can make progress at "the same time".



  • https://en.wikipedia.org/wiki/Lock_(computer_science) - or mutex (from mutual exclusion) is a synchronization mechanism for enforcing limits on access to a resource in an environment where there are many threads of execution. A lock is designed to enforce a mutual exclusion concurrency control policy.

Macros

Metaprogramming

Monads

Aspect of functional. See Haskell, etc. for related.

Events

Messaging

See also Network#Messaging

  • ØMQ \zeromq\
    •  The socket library that acts as a concurrency framework.
    •   Faster than TCP, for clustered products and supercomputing.
<tef> but glyph is the serialization format really :-)
  • MessagePack is an efficient binary serialization format. It lets you exchange data among multiple languages like JSON but it's faster and smaller. For example, small integers (like flags or error code) are encoded into a single byte, and typical short strings only require an extra byte in addition to the strings themselves.

Futures and promises

Compilation and interpretation

to resort


  • https://en.wikipedia.org/wiki/Preprocessor - a program that processes its input data to produce output that is used as input to another program. The output is said to be a preprocessed form of the input data, which is often used by some subsequent programs like compilers. The amount and kind of processing done depends on the nature of the preprocessor; some preprocessors are only capable of performing relatively simple textual substitutions and macro expansions, while others have the power of full-fledged programming languages.
  • https://en.wikipedia.org/wiki/Relocation_(computing) - the process of assigning load addresses to various parts of a program and adjusting the code and data in the program to reflect the assigned addresses. A linker usually performs relocation in conjunction with symbol resolution, the process of searching files and libraries to replace symbolic references or names of libraries with actual usable addresses in memory before running a program. Relocation is typically done by the linker at link time, but it can also be done at run time by a relocating loader, or by the running program itself. Some architectures avoid relocation entirely by deferring address assignment to run time; this is known as zero address arithmetic.


  • https://en.wikipedia.org/wiki/Assembler_(computing) - creates object code by translating combinations of mnemonics and syntax for operations and addressing modes into their numerical equivalents. This representation typically includes an operation code ("opcode") as well as other control bits. The assembler also calculates constant expressions and resolves symbolic names for memory locations and other entities.[4] The use of symbolic references is a key feature of assemblers, saving tedious calculations and manual address updates after program modifications.



  • https://en.wikipedia.org/wiki/Compiler-compiler - or compiler generator is a programming tool that creates a parser, interpreter, or compiler from some form of formal description of a language and machine. The earliest and still most common form of compiler-compiler is a parser generator, whose input is a grammar (usually in BNF) of a programming language, and whose generated output is the source code of a parser often used as a component of a compiler.

The ideal compiler-compiler takes a description of a programming language and a target instruction set architecture, and automatically generates a usable compiler from them. In practice, the state of the art has yet to reach this degree of sophistication and most compiler generators are not capable of handling semantic or target architecture information.



GCC

  • GNU Compiler Collection includes front ends for C, C++, Objective-C, Fortran, Java, Ada, and Go, as well as libraries for these languages (libstdc++, libgcj,...). GCC was originally written as the compiler for the GNU operating system. The GNU system was developed to be 100% free software, free in the sense that it respects the user's freedom.


Clang

  • http://en.wikipedia.org/wiki/Clang - compiler front end for the C, C++, Objective-C, Objective-C++, OpenCL and CUDA programming languages. It uses LLVM as its back end and has been part of the LLVM release cycle since LLVM 2.6.

It is designed to offer a complete replacement to the GNU Compiler Collection (GCC). It is open-source,[4] and its contributors include Apple, Microsoft, Google, ARM, Sony, Intel and AMD. Its source code is available under the University of Illinois/NCSA License, a permissive free software licence.

LLVM

  • LLVM is a collection of modular and reusable compiler and toolchain technologies. Despite its name, LLVM has little to do with traditional virtual machines, though it does provide helpful libraries that can be used to build them. The name "LLVM" itself is not an acronym; it is the full name of the project.
  • Emscripten is an LLVM to JavaScript compiler. It takes LLVM bitcode (which can be generated from C/C++ using Clang, or any other language that can be converted into LLVM bitcode) and compiles that into JavaScript, which can be run on the web (or anywhere else JavaScript can run).

Other

  • Parrot is a virtual machine designed to efficiently compile and execute bytecode for dynamic languages. Parrot currently hosts a variety of language implementations in various stages of completion, including Tcl, Javascript, Ruby, Lua, Scheme, PHP, Python, Perl 6, APL, and a .NET bytecode translator. Parrot is not about parrots, though we are rather fond of them for obvious reasons.


  • https://en.wikipedia.org/wiki/Yacc - a computer program for the Unix operating system. It is a LALR parser generator, generating a parser, the part of a compiler that tries to make syntactic sense of the source code, specifically a LALR parser, based on an analytic grammar written in a notation similar to BNF. Yacc itself used to be available as the default parser generator on most Unix systems, though it has since been supplanted as the default by more recent, largely compatible, programs.
  • XMLVM is to offer a flexible and extensible cross-compiler toolchain. Instead of cross-compiling on a source code level, XMLVM cross-compiles byte code instructions from Sun Microsystem's virtual machine and Microsoft's Common Language Runtime. The benefit of this approach is that byte code instructions are easier to cross-compile and the difficult parsing of a high-level programming language is left to a regular compiler. In XMLVM, byte code-based programs are represented as XML documents. This allows manipulation and translation of XMLVM-based programs using advanced XML technologies such as XSLT, XQuery, and XPath.



History





  • https://en.wikipedia.org/wiki/Altair_8800 - a microcomputer designed in 1975 based on the Intel 8080 CPU. Interest grew quickly after it was featured on the cover of the January 1975 issue (published in late November 1974) of Popular Electronics, and was sold by mail order through advertisements there, in Radio-Electronics, and in other hobbyist magazines. The designers hoped to sell a few hundred build-it-yourself kits to hobbyists, and were surprised when they sold thousands in the first month.


People

Hacking

https://emily.st/2015/01/27/reverse-engineering/ [126]

Areas

Command-line

GUI


Compression

Network



Graphics

3D

Audio

See also Audio#Programming

Distributed



NLP

Virus

Bots

Machine learning










Artificial intelligence

  • OpenAI is a non-profit artificial intelligence research company. Our goal is to advance digital intelligence in the way that is most likely to benefit humanity as a whole, unconstrained by a need to generate financial return.

Since our research is free from financial obligations, we can better focus on a positive human impact. We believe AI should be an extension of individual human wills and, in the spirit of liberty, as broadly and evenly distributed as is possible safely.

The outcome of this venture is uncertain and the work is difficult, but we believe the goal and the structure are right. We hope this is what matters most to the best in the field. [149]

Gaming

Social


For kids

Future



Performance

Quantum

Cool


Humour

to sort

  • The language of languages - explains grammars and common notations for grammars, such as Backus-Naur Form (BNF), Extended Backus-Naur Form (EBNF) and regular extensions to BNF.




  • RRDtool is the OpenSource industry standard, high performance data logging and graphing system for time series data. RRDtool can be easily integrated in shell scripts, perl, python, ruby, lua or tcl applications.






modelling;

  • QEforge is a web portal offering support to researchers active in the field of computer simulation and numerical modeling of matter and materials at the atomic scale. The most popular source code management (CVS, SVN or Git ) systems, mailing lists, public forums, download space, wiki pages, and much more are provided through the Gforge engine.
  • UbiGraph is a tool for visualizing dynamic graphs. The basic version is free, and talks to Python, Ruby, PHP, Java, C, C++, C#, Haskell, and OCaml.
  • Hunspell is the spell checker of LibreOffice, OpenOffice.org, Mozilla Firefox 3 & Thunderbird, Google Chrome, and it is also used by proprietary software packages, like Mac OS X, InDesign, memoQ, Opera and SDL Trados.


  • NuPIC - the Numenta Platform for Intelligent Computing, comprises a set of learning algorithms that were first described in a white paper published by Numenta in 2009. The learning algorithms faithfully capture how layers of neurons in the neocortex learn.






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