100% bug-free software is a myth. However, the pace, efficiency, and bug discovering capability of the software testing process can be increased very much with the help of efficient software testing best practices.
If you wish to read about them, there are so many blogs out there; but finding ones that work for you would be a daunting task.
What if we tell you that the practices that we penned down here have already been practiced and have worked out magically for us?
Through this blog, we are not just talking about triaging defects and prioritizing them.
We have tried to include what we have done to complement the development process and increase the overall quality of the SDLC.
Let’s dig in
#1 The perfect couple! The automated and manual way of testing
We are all used to the unrealistic and cinematic things about automation. But like the famous quote by Jim Hazen, understand that it’s automation, not automagic! It’s good to have a realistic approach to technology.
Simply automating processes that do not require one will do bad rather than anything good. The key is to identify the processes that are in dire need of automation.
In short, tests that are repetitive and have the same process to follow can be automated.
Understanding the fact that manual testing can never be replaced will also help better. Certain scenarios and testing types such as exploratory, usability, etc. cannot be automated. Why?
Machines at present cannot duplicate human emotion!
When it comes to best practices, we try to do these to attain maximum efficiency for our clients
- Thorough planning and careful consideration have to happen to create a road map from start to finish when it comes to test automation.
- We understand the fact that automation can save time, every organization wishes to finish the QA time to a minimum so that the focus can be given majority on the development side
- But certain procedures cannot be automated. For instance, there is no predefined path to automate when it comes to testing user interaction. So it’s always good to perform exploratory testing manually rather than automating it
- Like it’s mentioned in the beginning, human emotions cannot be automated. So it’s better to check the UX, accessibility, content, etc. of the app/software manually
- We have helped our customers automate repetitive regression tests because that’s the process that direly needs the technology
- Test automation is perfect for CI (continuous integration) environments. It helps in the idea of testing and then coding so that developers will be in the fastest feedback loop ever. Merging test automation to CI will also help in easing the integration efforts and last-time mishaps.
- If the product is changing often it’s not a good practice to automate the tests of products that are still in beta.
- Tests might fail, it’s obvious so the ideal thing to do here is to remove the tests that continuously fail from the regression pack. However, it’s better to keep a detailed log of them
- Adequate reporting procedure and detailed report will be generated after tests.
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#2 How to make your developer test their code?
Let’s admit it, everything does not run based on standards and best practices. Developers are often left alone with tasks rather than requirements. As a result, when the code is put to test they are bombarded with bugs. There starts the back and forth game of bug fix.
To save a lot of time, the unit test must be seen as a necessary standard rather than a time-consuming act.
For unit tests to happen, ordering developers would seldom make any difference, you have to make them understand how unit tests would ease their hardship using relevant examples.
Set a threshold of bugs found. This would make them work on the code as early as possible
Most importantly, make sure that the bugs are logged into a bug tracking tool.
Here are some of the basic good practices good unit tests
- Unit tests should cover all the key paths and scenarios
- The unit should happen as a stand-alone activity
- A good unit test must lead to the problem if it fails
- It should be well-factored
- Go for one assertion per unit test
- Integration and unit tests must be always separate
#3 Security testing, beyond cloud
More than 50% of internet traffic is now through mobile devices which is very vulnerable to threats. That means, in this era of heightened security breaches security testing must be given high priority in every phase of development.
At Present availing cloud service for creating test environments and testing, applications have become a common practice. However, from the attacks that have been and are happening across the globe, it has to be concluded that detailed security testing is imminent.
Tool-based penetration testing can only reveal to an extent and is majorly focussing on vulnerabilities. On the other hand, red-team intervention would bring a detailed picture of the security defenses against major cyber-attacks.
#4 Data privacy paradox and test data management
2020-2021 was a time where people talked greatly about AI intervention in the software development life cycle and in software testing too. However, the pace of intervention seems to be slower than expected.
But still, the emergence of many tools was indeed an awakening for the industry.
However, there exists a paradox of keeping data privacy when AI or third-party tools are brought to the picture.
So the key here is not to just rely on results projected by such tools.
A clear understanding of the fact that tools are meant to support the process must be spread across the team.
And when it comes to testing data management, make sure that
- Systematics of the data is right
- Unit test the test data generator
- Mask the sensitive data
- Identify data sets that no longer serve
- As the volume of test data rises, it’s better to audit and maintain them periodically
- Automate the test data production
#5 Big data testing! It’s the need of the hour
Traditional testing would not work in the case of big data testing. Because a humongous amount of data and processing integrity has to be tested to make sure that BI ( business intelligence ) is fed with quality data to drive the right insights.
Automation is the key to big data testing since testing a large set of data manually is not humanly possible.
Let’s go through the main goals of big data testing
- To ensure all the data is complete
- To make sure that the data formats have been converted to a relevant form that is compatible with the business specification and application design
- To make sure that ETL (Extract/Transform/Load) application correctly rejects invalid data, substitutes default values, etc.
- To ensure the performance and scalability of data handling applications and devices are right.
- To ensure ETL applications process and functions are performing as it is supposed to be.
- Regression testing can make sure that the application is intact after new enhancements.
- Achieve data regulation law, standards and security set out by the government or concerned authorities.
- Amount of data that can disrupt the system
- To find out the specificity of data sets
The best practices that we have followed are,
- Maintaining a data spreadsheet for a better understanding of flow inside the system
- Modify the data order from time to time.
- Review the column mapping
- Writing queries that can check the source and target data
- Check for duplicates in tables
- Ensure the deployment of adequate configuration management tools and processes
- Taking time in setting up a reporting standard and format
- When it comes to decisions, put analytics and pre-defined data sets to use
#6 Better Reports for a better fix
A poorly written bug report is a nightmare for developers. They have to ponder a lot before concluding the nature of the bug.
To avoid such a situation,
- Developers majorly look for 3 things in a report. Steps to reproduce the bug, expected result, and actual result. Make sure that it’s there in the report
- Attach relevant evidence in the form of screenshots and video to substantiate the bug
- If the bug is environment-specific, mention that too.
- Before writing the anticipated result be aware of the actual result too
- Provide complete system information ( hardware and software )
- You must have a better understanding of the audience of the report
- Have a creative/good online summary/title for the issues
- Description of the issue must be concise and precise
- If you do not have strong evidence it’s better not to speculate
- Avoid issue duplication in the report
- If you found out multiple issues in one single step raise them separately
- Do not log feature requests as a bug
- Even if testers think that the bug is unimportant it should be logged
- Before sending the report to developers it’s better to have a triage meeting to have a short discussion
- Mention the severity and priority of the issues after the triage meeting
#7 Shift-left + continuous testing is the way!
Shift left means including the QA process from the early stages and often in SDLC.
To make it happen we followed these from the very start
- TDD (test-driven development), pair programming, and unit tests are good ways to incorporate testing from the beginning.
- Question the requirement and design so that bugs were found from the very beginning. Questions in the early stages will also help in finding ambiguity in the requirement.
- Started devising a test plan and wrote test cases from the very beginning
- For automation also we did the same.
- By doing all these, we were able to bring the quality factor in all the team members of SDLC
- Including all these practices in the delivery, the pipeline would make the testing process very effective
#8 How to think like an end-user in testing?
You might have one sequence in mind while operating the software. What if the user follows an entirely different flow for instance in submitting a form?
This is the reason why testers must learn how to think like an end-user. Even though it is one of the fundamentals of testing, it’s rarely practiced in the real world.
This is what we did to make it happen
- We did a thorough study about the users and got into the process of thinking like them
- Empathy was brought to the picture so that testers would learn to see the software from another angle rather than data sets
- No matter whatever innovation we tried, it was clear we can only act like users, not become the real one
- User interaction with a raw version of the software is recorded to get insights
- Fictional characters were created ( persona-based testing) to enact various scenarios
#9 The ever-evolving mobile apps. How to keep up?
- By critical evaluation of requirement have a clear idea about the right device and OS version to test
- The functionality and architecture of the app must be understood before testing
- Include real environment as much as possible
- Inputs of manual testers have of utmost importance. Manual tester feedback about the UX (user experience) and other vital information of the app is crucial.
- When it comes to selecting the right tool for app testing, factors such as team collaboration capability, Android and iOS support, test management capability, data-driven automation support, etc. must be taken into consideration.
- Perform root cause analysis for a better picture of the issues
- Always keep in mind that 100% test coverage is not possible. However, an effort to increase the test coverage must be done
- Even though prime importance must be given in writing valid conditions, invalid conditions should also be considered.
- Write test cases from the requirement phase itself and give them to developers for reference
- The previous bug graphs can reveal probable bug-ridden areas of the application
- Prioritize tasks and then execute
If you wish to get highly efficient mobile app testing services, we are happy to help.
#10 Regression testing is always cool
Development pace is at present on par with the speed of flash. To make sure that everything is right, regression testing is a necessity. However, building tests that do not become obsolete is the key.
Here is how
- Always map your controls in one single place so that changes will be limited to that single place
- Discuss with the developer for design changes that will help in maintaining the tests
- Most importantly keep in mind that regression tests cannot be made maintenance-free. However, limiting it is possible
- Embed the test automation framework within the development framework
- The development process should be fast and agile.
- Complement the automation test suite with risk-based manual testing
- Remember, automation might not be able to find new bugs but they can be used to find out many faults in the regression tests
- Update your regression tests regularly
- Automated regression tests must be considered as the sprint.
Software testing best practices is more of a trial and error method. Basically what works for you is the right way to go. However, detection of ineffective/ wrong ones must be done.
We have always made sure that our software testing projects are efficient with software testing best practices that have worked for us or that have completed our client SDLC. Get in touch and we will be able to work out a plan that will complement your software product development process and significantly increase the quality.