C Programming Language Book Pdf Free Download _BEST

Common uses: C# is the go-to language for Microsoft ad Windows application development. It can also be used for mobile devices and video game consoles using an extension of the .NET Framework called Mono.

Benefits: C++ is an extension of C that works well for programming the systems that run applications, as opposed to the applications themselves. C++ also works well for multi-device and multi-platform systems. Over time, programmers have written a large set of libraries and compilers for C++. Being able to use these utilities effectively is just as important to understanding a programming language as writing code, Gorton says.

C Programming Language Book Pdf Free Download

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Benefits: R is heavily used in statistical analytics and machine learning applications. The language is extensible and runs on many operating systems. Many large companies have adopted R in order to analyze their massive data sets, so programmers who know R are in great demand.

Benefits: Also referred to as Golang, Go was developed by Google to be an efficient, readable, and secure language for system-level programming. It works well for distributed systems, in which systems are located on different networks and need to communicate by sending messages to each other. While it is a relatively new language, Go has a large standards library and extensive documentation.

The type of software you want to develop is one consideration for which programming languages to learn. While there are no concrete rules for what language is used to write what software, a few trends offer some guidance:

The term computer language is sometimes used interchangeably with programming language.[2] However, the usage of both terms varies among authors, including the exact scope of each. One usage describes programming languages as a subset of computer languages.[3] Similarly, languages used in computing that have a different goal than expressing computer programs are generically designated computer languages. For instance, markup languages are sometimes referred to as computer languages to emphasize that they are not meant to be used for programming.[4]One way of classifying computer languages is by the computations they are capable of expressing, as described by the theory of computation. The majority of practical programming languages are Turing complete,[5] and all Turing complete languages can implement the same set of algorithms. ANSI/ISO SQL-92 and Charity are examples of languages that are not Turing complete, yet are often called programming languages.[6][7] However, some authors restrict the term "programming language" to Turing complete languages.[1][8]

Another usage regards programming languages as theoretical constructs for programming abstract machines and computer languages as the subset thereof that runs on physical computers, which have finite hardware resources.[9] John C. Reynolds emphasizes that formal specification languages are just as much programming languages as are the languages intended for execution. He also argues that textual and even graphical input formats that affect the behavior of a computer are programming languages, despite the fact they are commonly not Turing-complete, and remarks that ignorance of programming language concepts is the reason for many flaws in input formats.[10]

In most practical contexts, a programming language involves a computer; consequently, programming languages are usually defined and studied this way.[11] Programming languages differ from natural languages in that natural languages are only used for interaction between people, while programming languages also allow humans to communicate instructions to machines.

The domain of the language is also worth consideration. Markup languages like XML, HTML, or troff, which define structured data, are not usually considered programming languages.[12][13][14] Programming languages may, however, share the syntax with markup languages if a computational semantics is defined. XSLT, for example, is a Turing complete language entirely using XML syntax.[15][16][17] Moreover, LaTeX, which is mostly used for structuring documents, also contains a Turing complete subset.[18][19]

Programming languages usually contain abstractions for defining and manipulating data structures or controlling the flow of execution. The practical necessity that a programming language support adequate abstractions is expressed by the abstraction principle.[20] This principle is sometimes formulated as a recommendation to the programmer to make proper use of such abstractions.[21]

Slightly later, programs could be written in machine language, where the programmer writes each instruction in a numeric form the hardware can execute directly. For example, the instruction to add the value in two memory locations might consist of 3 numbers: an "opcode" that selects the "add" operation, and two memory locations. The programs, in decimal or binary form, were read in from punched cards, paper tape, magnetic tape or toggled in on switches on the front panel of the computer. Machine languages were later termed first-generation programming languages (1GL).

The next step was the development of the so-called second-generation programming languages (2GL) or assembly languages, which were still closely tied to the instruction set architecture of the specific computer. These served to make the program much more human-readable and relieved the programmer of tedious and error-prone address calculations.

The first high-level programming languages, or third-generation programming languages (3GL), were written in the 1950s. An early high-level programming language to be designed for a computer was Plankalkl, developed for the German Z3 by Konrad Zuse between 1943 and 1945. However, it was not implemented until 1998 and 2000.[22]

John Mauchly's Short Code, proposed in 1949, was one of the first high-level languages ever developed for an electronic computer.[23] Unlike machine code, Short Code statements represented mathematical expressions in an understandable form. However, the program had to be translated into machine code every time it ran, making the process much slower than running the equivalent machine code.

At the University of Manchester, Alick Glennie developed Autocode in the early 1950s. As a programming language, it used a compiler to automatically convert the language into machine code. The first code and compiler was developed in 1952 for the Mark 1 computer at the University of Manchester and is considered to be the first compiled high-level programming language.[24][25]

The second auto code was developed for the Mark 1 by R. A. Brooker in 1954 and was called the "Mark 1 Autocode". Brooker also developed an auto code for the Ferranti Mercury in the 1950s in conjunction with the University of Manchester. The version for the EDSAC 2 was devised by D. F. Hartley of University of Cambridge Mathematical Laboratory in 1961. Known as EDSAC 2 Autocode, it was a straight development from Mercury Autocode adapted for local circumstances and was noted for its object code optimization and source-language diagnostics which were advanced for the time. A contemporary but separate thread of development, Atlas Autocode was developed for the University of Manchester Atlas 1 machine.

In 1954, FORTRAN was invented at IBM by John Backus. It was the first widely used high-level general-purpose programming language to have a functional implementation, as opposed to just a design on paper.[26][27] It is still a popular language for high-performance computing[28] and is used for programs that benchmark and rank the world's fastest supercomputers.[29]

Another early programming language was devised by Grace Hopper in the US, called FLOW-MATIC. It was developed for the UNIVAC I at Remington Rand during the period from 1955 until 1959. Hopper found that business data processing customers were uncomfortable with mathematical notation, and in early 1955, she and her team wrote a specification for an English programming language and implemented a prototype.[30] The FLOW-MATIC compiler became publicly available in early 1958 and was substantially complete in 1959.[31] FLOW-MATIC was a major influence in the design of COBOL, since only it and its direct descendant AIMACO were in actual use at the time.[32]

The increased use of high-level languages introduced a requirement for low-level programming languages or system programming languages. These languages, to varying degrees, provide facilities between assembly languages and high-level languages. They can be used to perform tasks that require direct access to hardware facilities but still provide higher-level control structures and error-checking.

The 1960s and 1970s also saw considerable debate over the merits of structured programming, and whether programming languages should be designed to support it.[35] Edsger Dijkstra, in a famous 1968 letter published in the Communications of the ACM, argued that Goto statements should be eliminated from all "higher-level" programming languages.[36]

The 1980s were years of relative consolidation. C++ combined object-oriented and systems programming. The United States government standardized Ada, a systems programming language derived from Pascal and intended for use by defense contractors. In Japan and elsewhere, vast sums were spent investigating the so-called "fifth-generation" languages that incorporated logic programming constructs.[37] The functional languages community moved to standardize ML and Lisp. Rather than inventing new paradigms, all of these movements elaborated upon the ideas invented in the previous decades.

One important trend in language design for programming large-scale systems during the 1980s was an increased focus on the use of modules or large-scale organizational units of code. Modula-2, Ada, and ML all developed notable module systems in the 1980s, which were often wedded to generic programming constructs.[38] 2351a5e196