Entering the world of testers, a question began to form in my mind: “what is the reason that errors occur?”
And I’m quite positive that you, after reading this article, will find the answers I provide useful to you as testers and QA engineers. Consider these tips that you can easily implement as well.
Also, I decided to share some insights on different mindsets (commonly called mindsets), why they are important for developers, and how they can be important for testers.
So let’s start with our new journey with bugs, developers, testers and knowledge.
People and writing code
The reasons below are so common that in any business industry, they are probably repeated every day. In some workplaces, this can be time-saving, useful, and even inspiring, but for developers, it’s a clear path to constant errors in their code. And also, for testers, these seven reasons tend to cause errors in the testing process and the consequences of test cases. But understanding them can help testers find bugs quickly and point developers to where the bugs are in the code.
- In a hurry
- Too much self-confidence
There are at least two reasons why copy-past produces errors during coding. First of all, the copied part of the main code must exactly match the destination where it is placed. Copy-paste can be a very bad solution for writing code, because the probability of missing a bit of code is almost 100%. When re-reading the written code (with copy-paste parts), the brain keeps jumping over the same words and commands, so it assumes they are good.
The second reason is that code is hard to maintain. And when editing your written code, copy-pasting code with an existing error is something that will happen. One copy is modified and bug-free, and unless you’re very, very careful, the other copy won’t be debugged. That is one explanation of the DRY principle.
Don’t Repeat Yourself (DRY) is a software development principle that aims to reduce repetition of software patterns, replace them with abstractions, or use data normalization to avoid redundancy. (Wikipedia)
When we feel that there is no time to do something to achieve the perfect result, we panic and try to see the finished picture instead of the small parts that make up that picture. It is generally an efficient feature of our brain, as it allows us to complete the most basic tasks with an approximate result. And that’s fair enough if we’re not talking about coding. However, coding is about the accuracy of small tasks (rather than seeing the big picture). So, details are important in coding and developers should spend time on every detail and complete all stages of code generation.
Be careful not to procrastinate on tasks expecting ideas to blossom. You need to allocate the necessary time for each task. It’s best to spend time writing code that works rather than just rushing to code and then spending time fixing bugs.
There are many ways to design software such as Scrum, Kanban and Agile. But one thing should be common for all. you have to design new software without improvisation. Take time to analyze each question in your program and carefully analyze the patterns.
Avoiding improvisation is important when integrating new features into existing software solutions. Carefully analyze the available documentation provided by the developers of this integration. It’s not a waste of time, it saves time to avoid integration problems and system crashes.
Experienced programmers will sometimes use their intuition, such as a rule of thumb, but find improvisation to be a very common cause of errors.
Now something that definitely cannot be used in programming, however popular this phrase is in the work environment. I don’t think multitasking can get any work done properly, but that’s another topic.
Developers need focus. The solution to this may be to plan the workday with hours without meetings, turn off notifications, use headphones, etc. There are some methods of staying focused (such as the Pomodoro method). And one more thing: avoid “asynchronous communication”, that is, stop bothering your colleagues with small questions and work independently.
Treat each project as important and devote your time to developing the best solution. Maybe the developers think that the project is simple, but even the simplest applications have complex solutions.
Developers must understand that things such as the number of users of the application or the records saved, the device on which the application is intended to be used, and its working memory can limit the software that can be created. So keep this in mind and get your calculations right.
One thing that can cause bugs is when you stop to question yourself if your code makes sense. Never stop having healthy doubts about your code and whether it will meet all the implementation requirements. Programmers with a lot of experience creating programs know the importance of this rule.
Describe all features in detail and this should clarify any questions that will arise during implementation.
One more thing, try to balance insecurity and overconfidence. Because both can cause problems. insecurity will keep you stuck and overconfidence will end up with crappy software.
This is something that developers are not the only ones responsible for. Everyone involved in software development needs to be aware of external events. Things like network issues, missing access, and correct resources should be taken into account to prevent errors and run the software successfully.
The importance of writing cleaner code
Programming is 99% teamwork.
Today, teams are changing approaches to writing code and encouraging team members to write cleaner code. The reason for that. if your code is cleaner, it’s easier to read. And it will be more understandable for other developers. And this is important for any programming language you use.
Also, software solutions are constantly being updated, so when a new team member needs to make updates, it will be a problem if the code is messy.
For testers, the reason is obvious. If they are dealing with clean code, it will be easy to find a bug and write a bug report. Also, if a bug occurs and you report it to the development team, everyone on the team will understand the bug better if the code is written with cleaner code writing “rules”.
Here are some points to help you write cleaner code:
- Use descriptive names when defining variable or function names. Try to create a syntax with value variables that other programmers can understand. And not just on your team, but for everyone who will review your code in the future.
- Try to write functions that do only one thing. Yes, once you’ve written your code and have the output in your head, you’ll write a function that does a lot. This complex function is simple for you, but difficult for someone else to understand.
- Try to take some time and write some short functions that do something and are easy to read and understand.
- Another tip, instead of writing too many comments, write code with descriptive names. It may be more difficult, but rest assured that it will be appreciated in the end.
- When writing comments, be clear and have a clear message. Write your comment with useful information. And not only will other developers know what you’ve done, but you’ll need to go back to your code later. And in a few months or a year, you’ll have a hard time understanding what the code is doing if you don’t have a descriptive message.
The most important use of cleanup code is when you write it, testers can easily automate its tests.
Now let’s see why binary search is easier with cleaner code.
Binary search is successful and can only be used when you have a sorted list of products. At each step of the binary search, the data will be truncated by half. This significantly reduces search time and the required information or information will be quickly delivered to the end user.
To have clean code and to write it, you need to have a well-organized structure. An organized structure is easier to read, and as we know, binary search only succeeds on well-structured codes.
This will also reduce testing time and your software will be released without bugs. Your end user will be happy too.
Now you’re probably wondering what eternal knowledge has to do with bugs. I will try to explain it briefly.
The world of programming and software solutions is a fast-changing game. More and more people are driven to start their career in this field and this is the reason for the rapid evolution of coding languages and solutions.
There is so much research going on in the field of programming and software solutions that it is practically impossible to keep up with all the new developments that are happening.
There’s always something hot new hitting the market, and we tend to keep up with it. People don’t just want to be left out, they want to be in the center of the action.
However, one thing tends to be overlooked. And that is the advantage of having eternal knowledge.
What is eternal knowledge and how to discover it?
It can be derived from physical or abstract truths such as graph theory, linear algebra, and other branches of pure mathematics.
It can be time-stable, like storytelling, leadership, and learning how to learn. In the world of programming, try to transfer this to things like operating systems, computer networks, and cryptography.
Learn about operating systems and use knowledge of cryptography to better understand codebases to maintain eternal knowledge. Learning communication skills will help you be a successful team leader and run successful test cycles in the testing and QA world.
For programming, these points are timeless knowledge (you know them as the basics of programming languages):
- Variable declaration
- Basic syntax
- Data type and structures
- Flow control structures (conditions and loops)
- Functional programming
- Object-oriented programming
- IDEs (integrated development environments) and coding environments
And now to summarize.
Why is all this important to testers?
Everything I mentioned in this article are the most important coding basics that testers should know. And testers and QA need to understand this to be included in all phases of software development.
The starting point for understanding software, solutions, machine learning, and automation is to learn algorithm, binary code, and how machine language evolved into today’s “modern” languages. Not to mention that you will easily understand cloud solutions and AI.
What I mean is that in order to test, you need to understand how the software solution you are testing should work, then you can easily find bugs and write an acceptable bug report. Eternal knowledge is the basis for learning new things. Learn the basics and you’ll easily transition from tester to QA team lead to manual test automation.