Sometimes we have to repeat ourselves before we are heard. Then again there are times where we have to perform a certain action the same way several times before we can carry on with what we want to do.

Repetition is the keyword here and for humans that is something we generally try to avoid. Yet our digital friends love repetition. They never get tired and they never get bored of doing the same thing over and over again countless times.

So it’s little wonder then that all modern programming languages give us various ways in which we can perform a certain action as many times as we need.

In python we have the for statement which gives us the power to loop over large collections of data very quickly and efficiently.

For those newly moving into the realm of programming, the important question to mull over is what programming language or technology to specialize in. On the other hand, those who are already working as a software developer, the constant worry remains whether their current technology would become obsolete very soon.

Both these concerns could be easily addressed by checking the list of programming languages that are highly in demand and formulating the career by modifying your specialization accordingly. The supply for the developers have not met with the demand in these programming languages yet, making them most viable options for career.

Popular Programming Languages Based on TIOBE Index

The top 10 list of programming languages which are highly in demand in 2014 is listed below in the order of popularity. These languages are identified from the TIOBE Programming Community index which consists of 20 top programming languages. TIOBE index is an indicator of the popularity of programming languages and is updated once in every month.  This index is calculated using multiple search engines, and the ratings are based on the number of skilled engineers world-wide, courses and third party vendors.

Recently, I asked my friend, Ray, to list those he believes are the top 10 most forward thinkers in the IT industry.  Below is the list he generated. 

Like most smart people, Ray gets his information from institutions such as the New York Times, the Wall Street Journal, the Huffington Post, Ted Talks ...  Ray is not an IT expert; he is, however, a marketer: the type that has an opinion on everything and is all too willing to share it.  Unfortunately, many of his opinions are based upon the writings/editorials of those attempting to appeal to the reading level of an 8th grader.  I suppose it could be worse.  He could be referencing Yahoo News, where important stories get priority placement such as when the voluptuous Kate Upton holds a computer close to her breasts.

Before you read further, note that missing from this list and not credited are innovators: Bill Joy, Dennis Ritchie, Linus Torvalds, Alan Turing, Edward Howard Armstrong, Peter Andreas Grunberg and Albert Fent, Gottfried Wilhelm Leibniz/Hermann Grassmann ... You know the type:  the type of individual who burns the midnight oil and rarely, if ever, guffaws over their discoveries or achievements.

I suspect that many of you are familiar with the term "hard coding a value" whereby the age of an individual or their location is written into the condition (or action) of a business rule (in this case) as shown below:

if customer.age > 21 and customer.city == 'denver'

then ...

Such coding practices are perfectly expectable provided that the conditional values, age and city, never change. They become entirely unacceptable if a need for different values could be anticipated. A classic example of where this practice occurred that caused considerable heartache in the IT industry was the Y2K issue where dates were updated using only the last 2 digits of a four digit number because the first 2 digits were hard-coded to 19 i.e. 1998, 1999. All was well provided that the date did not advance to a time beyond the 1900’s since no one could be certain of what would happen when the millennia arrived (2000). A considerably amount of work (albeit boring) and money, approximately $200 billion, went into revising systems by way of software rewrites and computer chip replacements in order to thwart any detrimental outcomes. It is obvious how a simple change or an assumption can have sweeping consequences.

You may wonder what Y2K has to do with Business Rule Management Systems (BRMS). Well, what if we considered rules themselves to be hard-coded. If we were to write 100s of rules in Java, .NET or whatever language that only worked for a given scenario or assumption, would that not constitute hard-coded logic? By hard-coded, we obviously mean compiled. For example, if a credit card company has a variety of bonus campaigns, each with their own unique list of rules that may change within a week’s time, what would be the most effective way of writing software to deal with these responsibilities?