Programming is changing briskly, and there is an explosion of new languages like Apple’s Swift, Facebook’s Hack scripting language and many more. Although there are zillion programming languages in the market, there is regular emergence of new languages every now and then, mainly from the corporate world. Some languages are meant to modernize classic languages, some are built for statistical analysis, whereas some are not even languages but are merely processors. There is no single language that fits all, however, computing is fast spreading to new platforms, challenging programmers to build bigger and more connected systems. It is like a quest for smarter and faster programming, with fewer bugs. There is a need for more structure and more abstraction, taking the automation to a new level and offering more leverage to the programmers.
Although it is a tough task to predict the future, however, there are few languages that are lesser-known and could become big over the next few years. Some of the languages that are driving these technological revolution and are shaping the future of coding are:
1. R– Programming language R was designed by the scientists and statisticians, and comes with standard functions that are used in data analysis. It is well suited for data-driven science. R commander and R Studio are two main front ends that allow programmers to load their data and play around with it. Many developers use R inside an IDE as a scratchpad to work with their data. R has clever expressions for selecting and analysing subset of the data.
2. Swift– Swift was introduced by Apple when it became difficult for new programmers to code in Objective C. Swift hides creating header files and juggling pointers, works more like a modern language such as Java or Python, and is ideally suited to write for Mac or the iPhone. In addition to cleaning up of the syntax of Objective C, Swift also offers several new features which helps iPhone coders to spin out code quite quickly with cleaner syntax.
3. Java 8– Although Java has captured the world of computer languages, Java 8 is different. The new features offer functional techniques to unlock parallelism in the code. It helps write faster and cleaner code, with less bugs.
4. GoogleGo– Also known as goland, the language was created by three Google employees in 2009. It is open source, multiplatform and portable, fast and friendly, and has solid concurrency support. However, it is a fairly young language with young ecosystem without many libraries yet. Hence developers need to write libraries themselves. There are also not many learning resources for Go yet.
5. MongoDB– An open source document database written in C++ which works on the concept of collection and document. MySQL has been in extensive use since 1995, but MongoDB can meet the challenging demands of newer applications. It can handle more data types than relational database, and is a powerful aggregation framework for data analysis. This enables developers to build applications faster, manage these applications more efficiently at scale and handle diverse data types.
6. Rust– Developed by Mozilla, Rust was released in 2014 and focuses on parallelisation, performance and memory safety. As the language is built from scratch and incorporates several elements from modern programming language designs, it is free of a lot of baggage as compared to traditional languages.
7. Hack– Built by Facebook, Hack can build complex websites and software at a great speed while keeping the software code organized and relatively free of flaws. Mark Zuckerberg created Facebook using PHP, however as the user base grew to hundreds of millions of people, the limitation of the language became more and more apparent. It became difficult to manage all the code and keep it free of bugs. With the help of HHVM (Hip Hop Virtual machine) and Hack, the team has solved most of their problems as these languages together make it much easier to manage code and eliminate errors.
8. Julia– A high-level, high-performance dynamic language for technical computing that provides sophisticated compiler, numerical accuracy, distributed parallel execution and extensive mathematical function library. There is a large Julia developer community contributing several external packages through built-in package manager of Julia.