5 Programming Languages Defining the Future of Coding

Programming Languages Defining the FutureWhichever field are you working in, you will come across software and web apps, sooner or later. In the past, the software was considered to be an enabler, but in the digital era of Artificial Intelligence and Machine learning, coding means a safe jump into the valley of opportunities. So, if you are thinking of learning to code, now is the right time to do so.

Software development is a dynamic field. Developers are always on their feet for learning new skills to stay relevant in the industry. Smart, faster software with minimum bugs is the goal of every programmer.

The future of coding requires good practices and stability for innovations to work. This approach ensures that there is more structure, providing the programmer with more leverage to concentrate on more significant issues in comparison to other traditional languages. In many cases, these languages also produce improved performance as the automated mechanisms can find better opportunities for efficiency and parallel computation along with eliminating some of the simple mistakes that might lead to errors.

Even though there is no correct answer to “what is the best programming language to learn”, we have compiled a list of 5 programming languages that are high in demand currently and will undoubtedly play an active role in defining the future of coding.

Programming languages that are defining the future of coding

Java 8

Java is not a new programming language. Billions of JAR files are floating around on the internet running the world. But, Java8 is a bit different. It comes with new features offering functional techniques that can help to unlock parallelism to your code. It provides Java virtual machine(JVM) providing more structure to your code execution. If you restrain yourself from using this language, then you might miss out on something that is cleaner, faster, and less buggy.

R

R is a programming language that uses statistics to unlock the patterns on large blocks of data. This language was designed by statisticians and scientists to make their work painless. This language comes with standard functions used in data analysis, and many statistical algorithms used in distributed libraries. Many programmers use R inside an IDE as a high-powered scratchpad for playing with extensive data.

Go

To power its server farms, Google set out to build a new language that was simple enough rather than being complex which most other languages are. They wanted to keep everything simple enough to remain in programmers head. This language does not include any complex abstractions or requires clever metaprogramming; the basic features are defined in a straightforward syntax.  This feature makes it easier for everyone as there is no intricacy in this language and no one has to be bothered to understand the complicated code.

Swift

When new programmers complained about the difficulties they faced while writing in Objective C, Apple saw this as an opportunity of introducing a new language which would replace Objective C when writing for Mac and iPhone. The specifications of this language are quite broad and are not just a syntactic cleanup of Objective C. It supports plenty of new features with a cleaner syntax. Some coders might even object that there’s too much to grasp, and Swift makes their work more complicated especially for programmers who need to read each other’s code. But let’s not aim too much on that. iPhone coders can now spin out their code as quickly as others.

MATLAB

Previously, MATLAB was considered as a hardcore language for scientists and mathematicians who required to juggle between complex systems of equations and had to find their solutions. This language still serves this purpose for those new projects that need complex skills. This language is fast, stable, and has stable algorithms for complicated math.MATLAB toolboxes are developed professionally along with being rigorously tested and fully documented. MATLAB applications allow you to see how different algorithms work with your data. This process is continued until you’ve achieved the results you desired, then a MATLAB program is automatically generated to automate your work. You can scale your analyses function them to run on clusters, GPUs, and clouds with only making minor changes in the code. There’s no need to rewrite your entire system code or to learn big data programming and out-of-memory techniques.

Deriving much about the new programming languages is hard as some of these languages stretch back years, even decades. They seem new as the larger world is just discovering them.

Contributor Bio

The article is presented by Sharda University. Sharda University is one of the largest universities in Delhi National Capital Region (NCR) offering 216 varied

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