The title of this story is a joke we exchange between colleagues when any of us is on the verge of a nervous breakdown due to a software defect that cannot be solved.
The title of this story is a joke we exchange between colleagues when any of us is on the verge of a nervous breakdown due to a software defect that cannot be solved. Or when, at 5.30 pm on Friday, a customer sends us the list of anomalies found, right in the last useful moment to ruin our weekend. Or better still, when somebody sends us a WhatsApp message like “doesn’t work”, period.
We programmers don’t like (software) bugs, but the reality is that they fill at least half of our time and are an essential part of our work. Moreover, they are perhaps the most effective device for us to grow and become expert programmers. The trick is to deal with them the right way and get the most out of them. And the right way is, in my opinion, the Sherlock Holmes method.
“The ideal reasoner would, when he had once been shown a single fact in all its bearings, deduce from it not only all the chain of events which led up to it but also the results which would follow from it.”
― _**_Arthur Conan Doyle, The Adventures of Sherlock Holmes**
What does it mean? Each effect must have a cause: when dealing with a software bug, if you can see the symptom, you can find a way to discover and remove its cause.
To succeed, however, you must adopt a rational method, avoiding, out of haste or laziness, to fall into errors that humiliate your skills as a problem solver.
Slow down and breathe. Count to 10. If you spit out the code without knowing what happened, you have a 100% chance of doing damage (especially if it’s Friday night).
Is the problem in an intricate piece of code and you don’t have the time or desire to unravel it? Of course, as an emergency, you can remove or deactivate the affected component or function, if you can. But don’t forget that it is not a solution and the cause is still there waiting to do new damage.
It is true. Sometimes, users report problems that do not exist, but, usually, they may be inaccurate in describing them, not crazy. It is unlikely that they tell something completely non-existent.
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