Javaprince Embedded

While the default IEEE Spectrum ranking in the Top Programming Languages interactive gives a good aggregate signal of language popularity, here we are taking a deep dive into the metrics related to job demand. Two of our data sources, Dice and CareerBuilder, measure job openings for the languages included in the interactive, and consequently we have a preset for “Jobs” that weighs the rankings heavily toward those metrics. So, if you want to build up your tech chops before looking for a programming job, what languages should you focus on?

Although Python has moved to the top of the default Spectrum ranking, if we instead go purely by the volume of openings that mention a language, we find that C beats Python by a ratio of 3.5 to 1, or about 19,300 job openings versus 5,400 across Dice and CareerBuilder combined. The Swiss army knife of database languages, SQL, is also highly in demand (15,400 openings), as are Web technologies like JavaScript (9,300 openings), HTML (7,000 openings), ASP.NET (2,700 openings), and PHP (2,400 openings). R, the increasingly indispensable language for data scientists, saw its zenith in 2016 but had some light contraction in 2017, shedding about 12 percent, to 353 openings. (As a caveat, we should note these numbers reflect job openings as of mid-June 2017, indexed for a 30-day window.)

In the mobile coding space, one of the clearest trends in the default ranking is the rise of Swift at the cost of Objective-C. We can see this in the jobs numbers too: openings for Objective-C shrank by slightly more than 19 percent, whereas those for Swift rose by almost 19 percent. And for the first time, there were more openings for Swift (439 openings) than for Objective-C (394 openings).

There are some significant changes further down the job rankings that are worth keeping an eye on too, even though the absolute number of job advertisements that cite these language is still relatively small. Both CUDA, a general-purpose language for coding GPUs, and Rust, which would feel familiar to most C / C++ programmers, fall into this category. Since 2016, CUDA has moved up four spots to 23 in the Jobs ranking, while Rust moved up a solid 10 positions to 25. Still, the absolute number of job openings was just 40 for CUDA and 23 for Rust. These are niche languages still, but Rust is growing quickly—going from being used in 10,900 new GitHub repositories in 2016 to almost 17,100 in 2017.

This article wouldn’t be complete without mentioning some of the losers in the programming language jobs calculus. Once a dominant Web programming language, Ruby is still used widely but it is slipping; the number of job openings for Ruby shrank by a full third since 2016, to about 1,600. We aren’t the first to report the slump in popularity of Ruby, and it’s far from dead, but this will be one to keep an eye on in the future as coders may already be shifting to alternatives like Python and Go. Demand for other languages like Clojure, Haskell, and Visual Basic is also on the wane. When we started the rankings in 2014, ActionScript still clocked 87 job openings, but in 2017 it continues the downward spiral, with only 20 openings, and it’s unlikely to make the Top Programming Languages at all next year. RIP, ActionScript.

    Obviously computer engineering and computer science has nothing in common regarding most of the confusions both of them present to each other and to the general public.
How?
     One of such confusions is the unit of measurement for the basic data unit which grew out from bit to bytes to  word and to other higher data units which I do  not really have time to explain here on this post.
It really seems someone is being too technical or someone is trying to deceive people with a unit definition that could literally mean something totally different, and that person could be microsoft which uses the same definition for both memory and disk which is totally wrong.  For all their highly qualified programmers, Microsoft in the early days of computers didn't use the correct units for file sizes and no one cared to stop them till it spread like wanna cry baby, later manufacturers took advantage of that in their intentional misrepresentation the capacity of their disk flash memory devices by using decimal definitions, in which a megabyte is 1,000,000 bytes.
The meomry of computer system which mostly is the RAM is defined in binary terms, with the 2^{n      rule,}
where 8 bits, used as a memory address, can address 256 bytes of memory, 16 bits can address 64 kilobytes of memory which was where early PCs started, 32 bits can address 4 gigabytes and 64 bits can address 16 exabytes.
In the early days of the computer industry, they used "kilo" for 1,024 bytes, then the hard drive industry realised they could put bigger numbers on their drives if they used 1,000, so someone came up with "kibibyte" for 1,024 bytes. It goes kibibyte, mebibyte, gibibyte, tebibyte, pebibyte, exbibyte, zebibyte, and yobibyte, each a factor of 1,024 instead of 1,000. While the hard drive people switched to multiples of 1,000, I don't know if the memory people ever did. But you can see why it was convenient to "round" 1,000 to 1,024 for computers, but then how having more than one definition for metric prefixes was confusing.
There should just be one set of prefixes for everything.
Too bad nobody in the early days of computing thought of making a set a prefixes that are based on some multiple of a power of 2 (1,024 is 2^10 and 10 isn't a power of 2) -- that would be ideal for computers. But it seems to be too late now as Microsoft had ruined everything by following the wrong trend.
Below is the system property of my Fedora Linux and how the memory and disk are defined with differently, binary and decimal respectively.
                                                                                 Linux use Gigabytes correctly
Yottabyte which is currently the largest metric prefix for standard units remains the largest we can think of now for the big data industry, thus these prefixes go kilo, mega, giga, tera, peta, exa, zetta, yotta.
After 64 bits which can address up to can address 16 exabytes 128 bits can address 281,474,976,710,656 yottabytes and we are far from a 128 data bus as of now.
The latest we have heard about is the rumours is the 92-bit bus which will be able to give us an available data of up to 4,096 "yotta"bytes.