There are normally two sides to the story when it comes to employment. On one hand, employers hold the view that the right candidate is a hard find; while on the other, job hunters think that it’s a tasking affair to land a decent job out there.

Regardless of which side of the divide you lay, landing good work or workers is a tedious endeavor. For those looking to hire, a single job opening could attract hundreds or thousands of applicants. Sifting through the lot in hope of finding the right fit is no doubt time consuming. Conversely, a job seeker may hold the opinion that he or she is submitting resumes into the big black hole of the Internet, never really anticipating a response, but nevertheless sending them out rather than sit back doing nothing.

A recruitment agency normally keeps an internal database of applicants and resumes for current and future opportunities. They first do a database search to try and identify qualified and screened candidates from their existing crop of talent. Most often the case, they’ll also post open positions online through industry websites and job boards so as to net other possible applicants.

When it comes to IT staffing needs, HR managers even find a more challenging process in their hands. This is because the IT department is one of the most sensitive in any given organization where a single slip-up could be disastrous for the company (think data security, think finances when the IT guys are working in tandem with accounts). You get the picture, right?

The original article was posted by Michael Veksler on Quora

A very well known fact is that code is written once, but it is read many times. This means that a good developer, in any language, writes understandable code. Writing understandable code is not always easy, and takes practice. The difficult part, is that you read what you have just written and it makes perfect sense to you, but a year later you curse the idiot who wrote that code, without realizing it was you.

The best way to learn how to write readable code, is to collaborate with others. Other people will spot badly written code, faster than the author. There are plenty of open source projects, which you can start working on and learn from more experienced programmers.

Readability is a tricky thing, and involves several aspects:

1. Never surprise the reader of your code, even if it will be you a year from now. For example, don’t call a function max() when sometimes it returns the minimum().
2. Be consistent, and use the same conventions throughout your code. Not only the same naming conventions, and the same indentation, but also the same semantics. If, for example, most of your functions return a negative value for failure and a positive for success, then avoid writing functions that return false on failure.
3. Write short functions, so that they fit your screen. I hate strict rules, since there are always exceptions, but from my experience you can almost always write functions short enough to fit your screen. Throughout my carrier I had only a few cases when writing short function was either impossible, or resulted in much worse code.
4. Use descriptive names, unless this is one of those standard names, such as i or it in a loop. Don’t make the name too long, on one hand, but don’t make it cryptic on the other.
5. Define function names by what they do, not by what they are used for or how they are implemented. If you name functions by what they do, then code will be much more readable, and much more reusable.
6. Avoid global state as much as you can. Global variables, and sometimes attributes in an object, are difficult to reason about. It is difficult to understand why such global state changes, when it does, and requires a lot of debugging.
7. As Donald Knuth wrote in one of his papers: “Early optimization is the root of all evil”. Meaning, write for readability first, optimize later.
8. The opposite of the previous rule: if you have an alternative which has similar readability, but lower complexity, use it. Also, if you have a polynomial alternative to your exponential algorithm (when N > 10), you should use that.

Use standard library whenever it makes your code shorter; don’t implement everything yourself. External libraries are more problematic, and are both good and bad. With external libraries, such as boost, you can save a lot of work. You should really learn boost, with the added benefit that the c++ standard gets more and more form boost. The negative with boost is that it changes over time, and code that works today may break tomorrow. Also, if you try to combine a third-party library, which uses a specific version of boost, it may break with your current version of boost. This does not happen often, but it may.

Don’t blindly use C++ standard library without understanding what it does - learn it. You look at std::vector::push_back() documentation at it tells you that its complexity is O(1), amortized. What does that mean? How does it work? What are benefits and what are the costs? Same with std::map, and with std::unordered_map. Knowing the difference between these two maps, you’d know when to use each one of them.

Never call new or delete directly, use std::make_unique and [cost c++]std::make_shared[/code] instead. Try to implement usique_ptr, shared_ptr, weak_ptr yourself, in order to understand what they actually do. People do dumb things with these types, since they don’t understand what these pointers are.

Every time you look at a new class or function, in boost or in std, ask yourself “why is it done this way and not another?”. It will help you understand trade-offs in software development, and will help you use the right tool for your job. Don’t be afraid to peek into the source of boost and the std, and try to understand how it works. It will not be easy, at first, but you will learn a lot.

Know what complexity is, and how to calculate it. Avoid exponential and cubic complexity, unless you know your N is very low, and will always stay low.

Learn data-structures and algorithms, and know them. Many people think that it is simply a wasted time, since all data-structures are implemented in standard libraries, but this is not as simple as that. By understanding data-structures, you’d find it easier to pick the right library. Also, believe it or now, after 25 years since I learned data-structures, I still use this knowledge. Half a year ago I had to implemented a hash table, since I needed fast serialization capability which the available libraries did not provide. Now I am writing some sort of interval-btree, since using std::map, for the same purpose, turned up to be very very slow, and the performance bottleneck of my code.

Notice that you can’t just find interval-btree on Wikipedia, or stack-overflow. The closest thing you can find is Interval tree, but it has some performance drawbacks. So how can you implement an interval-btree, unless you know what a btree is and what an interval-tree is? I strongly suggest, again, that you learn and remember data-structures.

These are the most important things, which will make you a better programmer. The other things will follow.

Communication is one of the main objectives that an organization needs to have in place to stay efficient and productive. A breakdown in accurate and efficient communication between departments at any point in the organization can result in conflict or loss of business.  Sadly, the efficiency between different departments in an organization becomes most evident when communication breaks down. As an example, David Grossman reported in “The Cost of Poor Communications” that a survey of 400 companies with 100,000 employees each cited an average loss per company of $62.4 million per year because of inadequate communication to and between employees.

With the dawning of the big-data era and the global competition that Machine Learning algorithms has sparked, it’s more vital than ever for companies of all sizes to prioritize departmental communication mishaps. Perhaps, today, as a result of the many emerging markets, the most essential of these connections are between IT and the business units. CMO’s and CIO’s are becoming natural partners in the sense that CMO’s, in order to capture revenue opportunities, are expected to master not just the art of strategy and creativity but also the science of analytics. The CIO, on the other hand, is accountable for using technical groundwork to enable and accelerate revenue growth. Since business and technology people speak very different languages, there’s a need on both sides to start sharing the vocabulary or understanding of what is expected in order to avoid gridlock.

In the McKinsey article, Getting the CMO and CIO to work as partners, the author speaks to five prerequisite steps that the CMO and the CIO can take in order to be successful in their new roles.

--- Be clear on decision governance
Teams should define when decisions are needed, what must be decided, and who is responsible for making them.

In May 2012 Google Chrome hit a milestone. It kicked Microsoft's Internet Explorer into excess phone oh that oh that second place as the most used browser on planet Earth.
With Microsoft being in second place, it makes a dark hole for Firefox coming in at number three. Google likes to trumpet three key reasons: security, simplicity and speed.
Available for free on Android, Linux, Mac, and Windows. It gets its speed from the open source JavaScript engine written in C++ known as V8.
In my daily use I use Microsoft's Internet Explorer version 10, Apple's Safari (on OS X) and chrome on both Windows 8 and OS X.

Admittedly people do not know anything about Internet Explorer version 10 since you can only get it on Windows 8/RT.

I do not need a crystal ball to know that the Mother of All Browser Battles is set to begin in the fall of 2012 and beyond.

I have said this before and I'm going to say it again.