You may have bugs due to testing !
This is true.
You can not test 100% of any product or application.
That is you can not claim that you have tested completely.
And also, it is true that you can not claim product is bug free. Product will have bugs. May be they are not uncovered by users too.
That is it.
In my earlier article, I had mentioned about the reasons for a software to have bugs in production.
Just to summarise, from that article, here are the main reasons:
- Requirement issues
- SDLC issues
- Testing issues
We have already seen the issues due to requirements.
In this article, I will explain about the issues due to testing.
Testing issues can be:
- Incomplete test coverage
- Insufficient/wrong test data
- Poorly designed test cases
- Automation challenges
- Regression testing failure
- Lack of exploratory testing
- Miscommunication
- Delay in bug reporting
- Not understanding the user and requirements
- Improper test estimation
- Test environment issues
I will explain them in detail — with examples, impact of those issues. I will also give some mitigations for those issues.
And I will do it for all of the above 11 issues.
If I do that in single article, then this article will be too long to read and digest.
So, I will break them up in to multiple articles.
In today’s article, I will explain 3 issues first.
Let’s dive in.
1. Incomplete test coverage
Poor test coverage.
Incomplete test coverage refers to the situation where certain features or functionalities of the product are not adequately tested.
This can be due to many reasons.
And those reasons can be:
- Oversight
- Time constraints, or
- Lack of awareness about test scenarios
Incomplete testing coverage can extend to various aspects of the product.
These include :
- Different user roles
- Edge cases
- Integrations with other systems.
Example:
Assume you are testing e-commerce application.
You concentrate only on the functionality of placing orders. Because this functionality is more important.
But you ignore the account creation process, payment gateways, or the product search functionality.
Then you risk leaving potential issues undiscovered.
Impact of incomplete test coverage:
The impact is significant.
Bugs in production can have following business impact like :
- User dissatisfaction
- Loss of trust
- Financial losses for your business
Uncovered bugs might only surface when users start using product.
What can this lead to ?:
- Increased customer support requests
- Negative product reviews
- Potential damage to the reputation of your product or the company.
How to mitigate ?
You saw the impact of incomplete test coverage.
Now, let me explain how to mitigate this issue.
- Comprehensive test plans
It is crucial to create comprehensive test plans.
Those plans should cover all critical functionalities and scenarios. You should work closely with stakeholders to understand the product requirements thoroughly.
1. Risk based testing
Techniques such as risk-based testing can help you.
Help you to prioritize testing efforts based on the likelihood and impact of potential issues.
2. Regular reviews
Regularly review test plans.
Continuous communicate within the testing team and with developers. This can help you to ensure that you have more testing coverage.
There are many other solutions to this issue.
But the ones I have explained above should be sufficient to achieve more coverage.
2. Insufficient/wrong test data
Test data matters.
Insufficient test data is when your test scenarios don’t cover a wide range of inputs.
This leads to a lack of test coverage for various actual user flows.
Your testing is not thorough enough to account for the variety of data. Data that users might input into the system.
The impact of insufficient test data is that the software may not be adequately prepared to handle a wide range of user inputs.
It can also lead to the bug escapes to production.
Example:
Assume you are testing registration form in a product.
If your test data only includes valid inputs. Such as proper names, email addresses, and standard passwords.
In this scenario, you might miss potential issues related to entering special characters, too long input strings, or data in different languages.
Impact of insufficient/wrong test data:
This can have larger impact.
Impact of insufficient test data is that the product may not behave as expected to handle a wide range of user inputs.
This can lead to bugs in production when users interact with the product using data that was not adequately tested during the testing phase.
Testing with more negative scenarios is key here.
What can this lead to ?:
- Increased customer support requests
- Negative product reviews
How to mitigate ?
Test data you use has major role in your testing.
You can mitigate these issues by following:
1. Collaborate with domain experts
You can collaborate with domain experts.
This collaboration helps you to identify a comprehensive set of test data. Test data that encompasses a variety of inputs, including edge cases and boundary values.
2. Data driven testing
Using data-driven testing techniques and incorporating realistic datasets can enhance the effectiveness of testing.
3. Simulate user data
You can understand how users are using your product ? How are they using the data ?
If you are able to mimic the usage pattern and data, then you should be easily avoiding test data issues in testing.
3. Poorly designed test cases
Most testers depend on test cases.
So, test cases should be of good quality.
Poorly designed test cases are those that :
- Lack clarity
- Lack completeness
- Fail to cover important scenarios
A test case can be considered as well-designed when it can provide clear instructions.
Instructions on:
- What needs to be tested
- How to execute the test
- What the expected outcomes are
Poorly designed test cases can result in ineffective testing.
And this may lead to the potential oversight of critical scenarios.
Example:
Assume you are testing the login functionality of a web application.
A poorly designed test case might look like this: “Check if user can log in.”
This is too generic.
It doesn’t detail the scenarios to be tested.
It doesn’t mention checking for:
- Incorrect passwords
- Account lockouts
- Handling special characters in the password field.
Without clear instructions, you may not cover all the necessary scenarios.
This may lead to incomplete testing.
Impact of insufficient/wrong test data:
Incomplete test cases have major impact on testing.
Specially if your ‘testing’ is only dependent on test case execution. Not performing exploratory testing.
Poorly or wrongly designed test cases overlook critical scenarios. This may lead to the release of software with undiscovered issues. That is buggy product.
You may not effectively validate the application’s functionality, and the quality of the testing process is compromised.
How to mitigate ?
On the first hand, dependency on test cases is risky.
You need to do exploratory testing along with test cases.
Other mitigations for test cases can be:
1. Clear and detailed test cases
Your test cases should be well-structured, clear and cover a variety of scenarios.
You can design positive and negative test cases.
Test data used should be mentioned in the test case.
You can write detailed actions and expected results.
I have written a detailed article on test case template. You can read and use the template.
2. Test case reviews
Regular peer review of test cases is mandatory.
You can have formal test case reviews discussion. Any review comments can be incorporated and can be requested for another cycle of review.
I will try to explain about testing issues in the upcoming articles.
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