You know what OAuth login is, right? It's when your users click "login" and get redirected to Facebook, Twitter, Google, or some other website which then identifies them. Then they go back to your website and you know who they are. It's very convenient for them. It's convenient for you too, since you don't need to implement the login functionality and don't need to keep their credentials in a database. I created a simple Ruby gem to simplify this operation for GitHub only. Here is how it works.

I said earlier that constructors must be code-free and do nothing aside from attribute initialization. Since then, the most frequently asked question is: What about validation of arguments? If they are "broken," what is the point of creating an object in an "invalid" state? Such an object will fail later, at an unexpected moment. Isn't it better to throw an exception at the very moment of instantiation? To fail fast, so to speak? Here is what I think.

You know what NULL is, right? It's evil. In OOP, your method can return NULL, it can accept NULL as an argument, your object can encapsulate it as an attribute, or you can assign it to a variable. All four scenarios are bad for the maintainability of your code—there are no doubts about that. The question is what to do instead. Let's discuss the "return it" part and I will suggest one more "best practice" on top of what was discussed a few years ago.

A few weeks ago someone suggested I should try to integrate IntelliJ IDEA's static analysis rules into Qulice, our aggregator of Checkstyle, PMD, FindBugs, and some other analyzers. I do love IDEA's rules—some of them are unique and very useful. I asked whether I could find them somewhere in Maven Central (they are written in Java) and the answer was "You'll have to figure out yourself how to use them, but they are open source." Here comes my opinion about this situation: I believe that open source doesn't just mean the code is readable without authorization. It means something much bigger.

You know, at Zerocracy, either you are a programmer or a tester, and we pay for each bug you find and report. Well, not quite. We pay for each bug report a project architect considers good enough to pay for. The architect's decision is totally subjective and non-disputable, according to §29 of the Policy. Some of our developers find this unfair and ask me to explain how they can report bugs such that they are definitely paid. Here is a non-exhaustive list of my recommendations.

What frustrates me most in my profession of software development is the regular necessity to understand large problem scopes before fixing small bugs, especially if the code is legacy and not mine. Actually, it's even more frustrating when the code is mine. The "deep thinking," as they call it, which is always required before even a small issue can be resolved, seriously turns me away from programming. Or did turn me away. Until I started to think differently and encourage myself to be lazy. Here is how.

I was asked on Twitter recently how is it possible to refactor if one doesn't understand how the code works. I replied that it is "learning by refactoring." Then I tried to Google it and found nothing. I was surprised. To me refactoring seems to be the most effective and obvious way to study the source code. Here is how I usually do it, in nine object-oriented steps.

Open source is free, as in beer: you write code, nobody pays you. Of course, there are many ways to monetize your efforts, but there will be no direct cash payments from your users, usually. There are ways to collect money, which include an obvious "tip jar" button on your GitHub project page. The chances anyone will pay are low though. In my opinion, this is mostly because nobody trusts you enough—they are not sure you will use the money to make the product better. Most likely you will just spend it and nothing will change. But they want the product, not to make you happier. At least that's what I feel when I see a Patreon button.

I touched on this problem in one of my recent webinars, now it's time to explain it in writing. Thread-safety is an important quality of classes in languages/platforms like Java, where we frequently share objects between threads. The issues caused by lack of thread-safety are very difficult to debug, since they are sporadic and almost impossible to reproduce on purpose. How do you test your objects to make sure they are thread-safe? Here is how I'm doing it.

I've been in the software business for almost 30 years. I wrote my first piece of code when I was 12. Since then I have been programming and managing other programmers, hiring and firing them, planning projects and their budgets, finding and losing customers, investing into software teams and losing my investments, even teaching others how to manage software projects. What is my overall impression? It's a pain. I think I've found a solution though.

Fluent interface, first coined as a term by Martin Fowler, is a very convenient way of communicating with objects in OOP. It makes their facades easier to use and understand. However, it ruins their internal design, making them more difficult to maintain. A few words were said about that by Marco Pivetta in his blog post Fluent Interfaces are Evil; now I will add my few cents.

I decided to write this blog post after reviewing this pull request. What happened there? The author of the PR wasn't able to figure out the "right" way to implement it, and the code reviewer was waiting and waiting. Eventually, the reviewer came to me, since I was an architect, and complained that it was taking too long and he wasn't able to earn his money for the review he had done. Then the author of the changes explained that he couldn't finish since there were impediments and design inconsistencies; he also couldn't earn the money he deserved for fixing the issue. What did I say? I said: Forget the quality, just finish it any way possible.

The traditional way of integrating object-oriented back-end with an external system is through data transfer objects, which are serialized into JSON before going out and deserialized when coming back. This way is as much popular as it is wrong. The serialization part should be replaced by printers, which I explained earlier. Here is my take on deserialization, which should be done by—guess what—objects.

Most startups don't have enough cash to pay programmers as much as they deserve, unfortunately (or maybe not). Instead of cash, startups give their early employees shares of stock, which they will be able to either 1) sell in a few years and become millionaires billionaires, or 2) throw away and remain nobodies. It's a common practice. The question, however, is what is the right procedure, and the optimal algorithm, to transfer those shares to programmers. When exactly do they become shareholders? What is the formula?

A bug is something we find in a software product that "doesn't look right" (this is my personal definition). A bug can be hidden or visible; it can be "already fixed" or "still present"; it can be critical or cosmetic; it can be urgent or of a low priority. What is important is that the more bugs we are able to find and fix before our customers see them, the higher the perceived quality of the software. Simply put, bugs are a very good thing, if they are found by us, not our customers. We pay our programmers for each bug they find. Here is a cheat sheet for them, showing where and how they can find those bugs, to make more money.

Software development and coding are two different things. Usually, the former includes the latter, but not always. Coding produces lines of code, while software development creates products. Unfortunately, the majority of programmers joining Zerocracy now are coders. Even though they claim to be developers, in reality they are lacking the very important sociotechnical skills that differentiate product creators from lines-of-code writers.