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.

The world of technology moves faster than the speed of light it seems. Devices are updated and software upgraded annually and sometimes more frequent than that.  Society wants to be able to function and be as productive as they can be as well as be entertained “now”.

Software companies must be ready to meet the demands of their loyal customers while increasing their market share among new customers. These companies are always looking to the ingenuity and creativity of their colleagues to keep them in the consumer’s focus. But, who are these “colleagues”? Are they required to be young, twenty-somethings that are fresh out of college with a host of ideas and energy about software and hardware that the consumer may enjoy? Or can they be more mature with a little more experience in the working world and may know a bit more about the consumer’s needs and some knowledge of today’s devices?

Older candidates for IT positions face many challenges when competing with their younger counterparts. The primary challenge that most will face is the ability to prove their knowledge of current hardware and the development and application of software used by consumers. Candidates will have to prove that although they may be older, their knowledge and experience is very current. They will have to make more of an effort to show that they are on pace with the younger candidates.

Another challenge will be marketing what should be considered prized assets; maturity and work experience. More mature candidates bring along a history of work experience and a level of maturity that can be utilized as a resource for most companies. They are more experienced with time management, organization and communication skills as well as balancing home and work. They can quickly become role models for younger colleagues within the company.

Unfortunately, some mature candidates can be seen as a threat to existing leadership, especially if that leadership is younger. Younger members of a leadership team may be concerned that the older candidate may be able to move them out of their position. If the candidate has a considerably robust technological background this will be a special concern and could cause the candidate to lose the opportunity.

Demonstrating that their knowledge or training is current, marketing their experience and maturity, and not being seen as a threat to existing leadership make job hunting an even more daunting task for the mature candidate. There are often times that they are overlooked for positions for these very reasons. But, software companies who know what they need and how to utilize talent will not pass up the opportunity to hire these jewels.

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Net Neutrality

You may have heard about net neutrality over the years. Recently, the concept has gone through some changes, and many would consider its underlying principles to be in danger of corruption or dissolution. However, the technical nature of net neutrality ethics makes it difficult to understand for the layperson. Read on, and the central themes and controversies surrounding the principle will be outlined and explained for your convenience.

The Theme

Learning SQL development can seem like an overwhelming task at first. However, mastering just a few key points will help ease your way through 80 percent of the day-to-day challenges when writing stored procedures and solving common problems. Here are three important SQL development factors to keep in mind:

Outer Joins
One of the most crucial things to understand in SQL server are joins. Joins are a way to retrieve data from two or more tables based on logical relationships between them. Joins dictate how Microsoft SQL Server ought to use data from one table to select the rows in another table.

In my experience inner joins are intuitive while outer joins can present additional hours of grief by overlooking associations in the other table(s). The outer join is the key to answering questions about what the database does not have. For example, if you need to make a query to display all the students who are without report-cards, you’ll need a left join to get all students coupled with a “where clause” to return the ones who have nulls for their report card table columns in the results.

Many talented Java script programmers have muddled through the SQL Server by deficient coding around the inner join. As a result, their queries can take five hours to run, whereas, properly written left joins, can take only two seconds to run.

Aggregation
Grouping results comes up in SQL a lot more than you might think. Knowing how to write a query when answering questions such as, “What’s the average grade for each teacher’s student list?” is invaluable. This kind of question cannot be answered with a single table or solely by joins.  You’ll often find you need to use joins in conjunction with group by statements. Always write the raw query first and then look at the results. Next, you have to figure out the best way to group them, rewrite your select clause and add a group by clause in the end.

Digging Through Data
I find this is the most lacking skill in many programmers. In fact, many otherwise-talented programmers holding Master’s Degrees fail to get jobs because they couldn’t analyze rows of data objectively during interviews. It’s just something that’s not taught but is crucial to get under you belt. Why? Eventually, some query is not going to perform as you may expect. And, the only way to find discrepancies is to look at rows of data, identify what join isn’t finding a match or where bad data is throwing things into chaos. Get familiar with how joins actually work, even if you have to manually walk through the logic of a large stored procedure’s tree of joins. It’s boring and time-consuming but absolutely necessary.

Take the time to master the core skills that will make you a successful SQL Programmer and avoid queries that run for five hours!