The initiators of the latest series of programming languages are promising lightning fast and much smarter programming with lesser bugs. The goal is to capture the minds of programmers. This isn’t a new concept but the want of innovation should not be a reason for its dismissal. We can rest assured that our innovations would work given due time and the future of coding is in need of stability as well as good practices that bring about results.
The common theme shared by the programming languages mentioned here is that increasing automation can yield a faster, smarter, bug-free code. The fresher moves towards this aim include tactics for allowing the programming languages to work without the need of a programmer. This involves more abstraction and more structure in the automated features, which result in more leverage to the programmer for concentrating on fixing bigger issues.
Also, automated mechanisms generate better performance, as the mechanical functions are capable of finding opportunities for improved efficiency as well as parallel computation. It also eliminates some simple mistakes that a programmer could make and lead to errors.
However, that is the only predominant theme, which earns mutual agreement. Languages are built and used for many different purposes. For instance, one of them is meant for statistical analysis whereas many others are built for modernizing classic languages and many others are merely preprocessors, which cannot strictly be called languages. Even so, all of them are contributing to our advancement in writing code and laying down the base for a solid future of coding. Here are thirteen of these, which are radically changing our commands to the computers. The list comprises some new programming languages; some popular languages that are already used for many applications and some are preprocessors.
This programming language has been around since 1995 but it wasn’t popular at the time of its inception. Scientists and statisticians to perform a highly complex statistical analysis developed it. It is actually quite simple to use and can also be operated by the inexperienced who has little knowledge regarding coding. This is particularly useful for statisticians who don’t require a thorough knowledge of coding and yet can get their results for any kind of research by simple means. The language has standard formulae and functions that might be needed to run data for any research. Data analysis and some of the most useful typical functions are implemented as libraries distributed without any restraint in the language. Basically, it is equipped with everything that that data scientists would need to execute data-driven science.
R is used by many people inside an IDE to convert it into a high-powered scratchpad meant to play with data. The two famous front ends that allow a user to upload data and play with it are R Studio and R Commander. These interfaces make R an interactive platform for doing your work instead of a standard compile and run programming language. R can be used in Back end for Android applications for analytics. Also, command line text-based games can be created using R.
2. Java 8
With due credit to Java’s important role as the common language between the user and the computer for AP Computer Science, Java is often familiar to people as the first language. Many people use JAR files across the globe for a multitude of purposes. However, Java 8 is different as compared to the other versions. Its latest features offer functional techniques, which can unlock the parallelism in any code.
Not using the Java 8 would still work for you, but you would definitely miss out on the chance for offering more structure to the JVM (Java Virtual Machine) for optimizing program execution. Java 8 enables the user to write a cleaner and faster, bug-free code and to think functionally too. All the features of Java 8 such as lambda expressions, method references, default methods, static interface methods, type annotations, repeating annotations, functional interfaces and the Stream API can be used for Android platform.
Apple introduced Swift when they recognized the opportunity in the guise of programming newbies’ complaints. The result was bidding farewell to the endless jumble of writing codes in Objective C language. The introduction of Swift indicated that it would be used for writing code for the Mac and the iPhone as the creation of header files as well as managing pointers was obsolete. Writing in Swift is quite similar to writing in any modern language such as Java and Python as it hides the information and does all the work.
But Swift is not exactly the syntactic cleanup of its predecessor- Objective C. The language specification is quite broad and there is a host of new features. The downside is that the wealth of new knowledge might overwhelm those who need to learn all about it and the teams will also face some complications in reading each other’s code. Besides that possible drawback, the coders for iPhone can keep working on their code as swiftly as others. In fact, they can now work with a dramatically cleaner syntax while letting their language do all the busy work. The lesser volume of low-level pointers juggling is also a plus.
The coders at Google no longer need to worry when a colleague mines out a decent idea from the darker corners of the language specification- all thanks to Go. Google decided to throw out many of the cleverer ideas from other languages to build something simple enough to be held in the head of one programmer. Go was born with the intent of powering Google’s server farms and it has the basic features detailed in an open and uncomplicated syntax without any complex abstractions or astute meta-programming.
The world of C is considered to be very clean and simple by many programmers. This is due to the minimal syntax and the structure, which maps neatly to the CPU. That is also why it is called Portable Assembly. But the newer languages have some advantages built into them, which the C programmers miss out on. That is the reason behind building up D. D is the programming language, which not only retains but also updates the logical purity of its predecessors- C and C++. D also adds modern conveniences like type inference, memory management, as well as bounds checking.
Less.js is also a preprocessor, similar to CoffeeScript and it is meant to simplify the creation of elaborate CSS files. Those who have tried building a list of layout rules for websites, simple or complex, would know that creation of basic CSS necessitates repetition in abundance. Less.js controls all the replications with the help of variables, loops, and other elementary program constructs. For instance, one variable can be used for holding the shade of blue as a background as well as a highlight color. If it needs to be changed later, only one spot would require an update.
Elaborate constructs like nested rules and mixins are also there which efficiently create standard layout commands blocks, which can be integrated into as many CSS classes as the user wants. For instance, if you need to change the font, fixing it at the root using Less.js will ensure that the new rules are pushed into the entire set of definitions.
MATLAB used to be a dedicated an uncompromising programming language for mathematicians and scientists who were often required to work with complex equation systems for finding solutions. But now, it has been upgraded to satisfy the complex needs of projects nowadays. Besides that, MATLAB is also finding use in many applications since developers have started advancing into complicated mathematical as well as statistical analysis. This language’s core has been tried and tested by mathematicians over the years it has been in use and now, MATLAB can also be used by the inexpert too.
With the advancement of the Internet of Things, more and more devices are available with embedded chips which would accept commands more easily. Arduino is prepared to welcome the IoT even though it is not strictly a new language. Arduino is a set of functions in C or C++ that a user can string together and let the compiler do the rest. Most of the function sets are unique for programmers who create user interfaces for typical computers. For instance, one can check the position of pins on a board, read voltages, and influence the flashing of LEDs for sending indecipherable coded messages. In short, it is quite the playground for C and C++ programmers.
The video card juggles many triangles and those who make the effort to look under the hood would find lots of power, which can be instantly unlocked by the proper programmer. Nvidia has come up with the CUDA programming language in order to unlock the power of the GPUs (graphics processing units) and use it in more ways than just killing and winning video games.
The key challenge presented by CUDA is studying and identifying the parallel parts in the algorithm. Once those are found, the CUDA code can be set up in such a way that it can blast through all the parallel sections by using the intrinsic parallel power in the video card. This can be simple as is the case with mining Bitcoins, or it could be complicated when it comes to stuff like molecular dynamics. Scientists mostly use CUDA for large simulations of multi-dimensions.
The academic world absolutely appreciates the very idea of functional programming. For those who haven’t taken any advanced courses in programming languages, functional programming stipulates that there be well-defined inputs as well as outputs for each function but no way of manipulating other variables. Scala is among the few programming languages, which are known as the best, and has a large user base to boast of. It was built for running on the JVM (Java Virtual Machine), which means that any code written in Scala would run on any platform that runs Java, which is basically everywhere.
Following the functional programming, principles have proven to build stronger code, which can be easily optimized and is also free of some bugs. Scala is your opening to that code.
Granted that Scala is quite popular but Haskell is following close behind as it is a good space for programmers to begin. It is used by many projects already, for example, Facebook. The academic code is not exactly famous for giving a real performance when it comes to real projects but Haskell is turning that around.
A functional language known as XSLT was used during the XML era. As it was the big data format, XSLT was used as a tool for playing with large sets of data in XML code. Now, as JSON has become the next big thing, JOLT is a good option for manipulating and changing a user’s JSON data. Simple filters can be written which will extract the attributes and then JOLT will locate them and transform them into any desirable code.
These thirteen programming languages are used for different devices, platforms, and even video games. For instance, Swift was introduced for Mac and iPhone devices while Google has its own Go programming language. When it comes to gaming coding, the programmer can use Scala or Haskell or any other language, which can fulfill the specifications needed by the user. In case of gaming, it is even possible to harness the power of video cards as proven by CUDA. For some solid futuristic coding, these are showing some promise, especially on the Android and gaming front