When you think about the black market, I’m sure the majority of you will think of prohibition days.  When alcohol was made illegal, it did two things: It made the bad guys more money, and it put the average joe in a dangerous position while trying to acquire it.  Bring in the 21^stcentury. Sure, there still is a black market… but come on, who is afraid of mobsters anymore? Today, we have a gaming black market. It has been around for years, but will it survive? With more and more games moving towards auction houses, could game companies “tame” the gaming black market?

In the old days of gaming on the internet, we spent most of our online time playing hearts, spades… whatever we could do while connected to the internet. As the years went by, better and better games came about. Then, suddenly, interactive multiplayer games came into the picture. These interactive games, mainly MMORPGS, allowed for characters to pick up and keep randomly generated objects known as “loot”. This evolution of gaming created the black market.

In the eyes of the software companies, the game is only being leased/rented by the end user. You don’t actually have any rights to the game. This is where the market becomes black.  The software companies don’t want you making money of “virtual” goods that are housed on the software or servers of the game you are playing on.  The software companies, at this point, started to get smarter.

Where there is a demand…

Globalization
Globalization is the fundamental force changing IT service delivery and business's competitive activities in almost every vertical market — and thus economies — in some way, shape or form. One might say that globalization is not a new trend and has been commonplace for quite some time now. Yes, but with the changing economic environment globalizations has special implications for the IT outsourcing industry. With developed countries like the U.S. keeping a strict eye on generating local jobs, IT outsourcing especially in Asian countries such as India and China is expected to see globalization brining in big shifts in business strategy

Potential Impact of Globalization

·         Increase in near shoring in addition to outsourcing. Near shoring essentially refers to existing IT companies setting up development/delivery centers in Nordic and South American regions in order to offer same time zone services and also bypass the laws governing local hiring

·         A truly global delivery model. Service delivery models will have to become more efficient and flexible and work well even if service teams spread across continents

This will mean that large IT outsourcing companies such as TCS will have to expand their presence globally from just having sales offices to actual delivery teams shipping out solutions.

Once again Java tops C as the number one sought after programming language on the internet.  According TIOBE Programming Community Index for February 2013 and five search engines: Google, Bing, Yahoo!, Wikipedia, Amazon, YouTube and Baidu, Java regained its position after being bumped by C in May 2012.

Despite the recent urging by the U.S. Department of Homeland Security of computer users to disable or uninstall Java due to a flaw in Runtime Environment (JRE) 7, Java, has increased its market share of all languages by (+2.03%) in the past six months. The jump in Java’s popularity does not come as a surprise as the Android OS claims massive success in the mobile space.  The top twelve programming languages listed in the index are:

1.  Java
2.  C
3.  Objective-C 
4.  C++
5.  C#
6.  PHP
7.  Python
8.  (Visual) Basic
9.  Perl
10.  Ruby
11. Java Script
12. Visual Basic.NET

Also rising, Python and PHP which are competing to becoming the most popular interpreted language.

Python and Ruby, each with roots going back into the 1990s, are two of the most popular interpreted programming languages today. Ruby is most widely known as the language in which the ubiquitous Ruby on Rails web application framework is written, but it also has legions of fans that use it for things that have nothing to do with the web. Python is a big hit in the numerical and scientific computing communities at the present time, rapidly displacing such longtime stalwarts as R when it comes to these applications. It too, however, is also put to a myriad of other uses, and the two languages probably vie for the title when it comes to how flexible their users find them.

A Matter of Personality...

That isn't to say that there aren't some major, immediately noticeable, differences between the two programming tongues. Ruby is famous for its flexibility and eagerness to please; it is seen by many as a cleaned-up continuation of Perl's "Do What I Mean" philosophy, whereby the interpreter does its best to figure out the meaning of evening non-canonical syntactic constructs. In fact, the language's creator, Yukihiro Matsumoto, chose his brainchild's name in homage to that earlier language's gemstone-inspired moniker.

Python, on the other hand, takes a very different tact. In a famous Python Enhancement Proposal called "The Zen of Python," longtime Pythonista Tim Peters declared it to be preferable that there should only be a single obvious way to do anything. Python enthusiasts and programmers, then, generally prize unanimity of style over syntactic flexibility compared to those who choose Ruby, and this shows in the code they create. Even Python's whitespace-sensitive parsing has a feel of lending clarity through syntactical enforcement that is very much at odds with the much fuzzier style of typical Ruby code.

For example, Python's much-admired list comprehension feature serves as the most obvious way to build up certain kinds of lists according to initial conditions:

a = [x**3 for x in range(10,20)]
b = [y for y in a if y % 2 == 0]

first builds up a list of the cubes of all of the numbers between 10 and 19 (yes, 19), assigning the result to 'a'. A second list of those elements in 'a' which are even is then stored in 'b'. One natural way to do this in Ruby is probably:

a = (10..19).map {|x| x ** 3}
b = a.select {|y| y.even?}

but there are a number of obvious alternatives, such as:

a = (10..19).collect do |x|
x ** 3
end

b = a.find_all do |y|
y % 2 == 0
end

It tends to be a little easier to come up with equally viable, but syntactically distinct, solutions in Ruby compared to Python, even for relatively simple tasks like the above. That is not to say that Ruby is a messy language, either; it is merely that it is somewhat freer and more forgiving than Python is, and many consider Python's relative purity in this regard a real advantage when it comes to writing clear, easily understandable code.

And Somewhat One of Performance