Computer Programming is defined as the process of creating
computer software using programming languages.
Just like we speak and understand English or Spanish or French,
computers can understand programs written in certain languages. These are called programming languages. In the beginning there were just a few
programming languages and they were really easy to learn and comprehend. But as computers and software became more and
more sophisticated, programming languages evolved fast, gathering more complex
concepts along the way. As a result most
modern programming languages and their concepts are pretty challenging to grasp
by a beginner. This fact has started
discouraging people from learning or attempting computer programming.
The development of complex software systems such as operating systems, network software, and the vast array of application software available today would likely be impossible if humans were forced to write programs in machine language. Dealing with the intricate detail associated with such languages while trying to organize complex systems would be a taxing experience, to say the least. Consequently, programming languages similar to our pseudocode have been developed that allow algorithms to be expressed in a form that is both palatable to humans and easily convertible into machine language instructions. Our goal
in this chapter is to explore the sphere of computer science that deals with the design and implementation of these languages.
Programming is the process of taking an algorithm and encoding it into a notation, a programming language, so that it can be executed by a computer. Although many programming languages and many different types of computers exist, the important first step is the need to have the solution. Without an algorithm there can be no program.
Computer science is not the study of programming. Programming, however, is an important part of what a computer scientist does. Programming is often the way that we create a representation for our solutions. Therefore, this language representation and the process of creating it becomes a fundamental part of the discipline.
Our ranking system is driven by weighting and combining 12 metrics from 10 data sources. We believe these sources—such as the IEEE Xplore digital library, GitHub, and CareerBuilder—are good proxies for the popularity of 48 languages along a number of different dimensions. The weighting of these sources can be adjusted in our interactive Web app to give, say, more importance to languages that have turned up in job ads. Filters can be applied so that you can see only languages relevant to mobile or embedded development, for example. (Access to the Web app is US $0.99.)
We put a number of preset weightings into the app for convenience; the default is the IEEE Spectrum ranking, with weights chosen to broadly represent the interests of IEEE members, and here are this year’s top 10 languages from that weighting. (The column on the left is the 2015 ranking; the column on the right is the 2014 ranking for comparison.)
in this chapter is to explore the sphere of computer science that deals with the design and implementation of these languages.
Programming is the process of taking an algorithm and encoding it into a notation, a programming language, so that it can be executed by a computer. Although many programming languages and many different types of computers exist, the important first step is the need to have the solution. Without an algorithm there can be no program.
Computer science is not the study of programming. Programming, however, is an important part of what a computer scientist does. Programming is often the way that we create a representation for our solutions. Therefore, this language representation and the process of creating it becomes a fundamental part of the discipline.
Programming Languages: -
A programming language is a formal constructed language designed to communicate instructions to a machine, particularly a computer. Programming languages can be used to create programs to control the behavior of a machine or to express algorithms.
Most Famous Programming languages are here..
- SQL
- JAVA
- JAVASCRIPT
- C#
- PYTHON
- C++
- PHP
- IOS
- RUBY/RAILS
Our ranking system is driven by weighting and combining 12 metrics from 10 data sources. We believe these sources—such as the IEEE Xplore digital library, GitHub, and CareerBuilder—are good proxies for the popularity of 48 languages along a number of different dimensions. The weighting of these sources can be adjusted in our interactive Web app to give, say, more importance to languages that have turned up in job ads. Filters can be applied so that you can see only languages relevant to mobile or embedded development, for example. (Access to the Web app is US $0.99.)
The big five—Java, C, C++, Python, and C#—remain on top, with their ranking undisturbed, but C has edged to within a whisper of knocking Java off the top spot. The big mover is R, a statistical computing language that’s handy for analyzing and visualizing big data, which comes in at sixth place. Last year it was in ninth place, and its move reflects the growing importance of big data to a number of fields. A significant amount of movement has occurred further down in the rankings, as languages like Go, Perl, and even Assembly jockey for position.
A few languages have dropped off the rankings compared with last year’s. Mostly this is due to an insufficient presence in this year’s data to justify keeping them in. But in one case, an entry was dropped because we agreed with comments on last year’s ranking that said we had made a mistake in categorizing it as a language rather than just a framework. This was ASP.NET, and we had originally included it because of our pragmatic approach to the definition of programming language—a lack of Turing completeness is not an absolute bar, and we make no apologies for including things like HTML—but we were too broad on that one.
A few languages have dropped off the rankings compared with last year’s. Mostly this is due to an insufficient presence in this year’s data to justify keeping them in. But in one case, an entry was dropped because we agreed with comments on last year’s ranking that said we had made a mistake in categorizing it as a language rather than just a framework. This was ASP.NET, and we had originally included it because of our pragmatic approach to the definition of programming language—a lack of Turing completeness is not an absolute bar, and we make no apologies for including things like HTML—but we were too broad on that one.
A number of languages have entered the rankings for the first time. Swift, Apple’s new language, has already gained enough traction to make a strong appearance despite being released only 13 months ago. Cuda is another interesting entry—it’s a language created by graphics chip company Nvidia that’s designed for general-purpose computing using the company’s powerful but specialized graphics processors, which can be found in many desktop and mobile devices. Seven languages in all are appearing for the first time.
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