How to Determine Bug Severity vs. Priority in Testing
Automation Testing with cucumber framework Finding and removing defects from their applications is a constant challenge for testers in the world of mobile app testing. One of the most crucial stages of the software development life cycle is determining the severity and priority of testing.
Sometimes, the terms “bug severity” and “bug priority” are used interchangeably to describe the process of finding and eliminating bugs. Bug severity and priority, on the other hand, are more complex phrases with distinct meanings.
We will examine the relationship between problem severity and priority in testing in this blog post, as well as how they complement one another to improve testing efficiency and application performance.
What Is the Level of a Bug?
The term “bug severity” describes the impact that a bug (or defect) has on an app’s overall usability.
On a scale, bug severity is determined:
- Low severity – The flaw or error won’t have a big influence on how well the program works overall.
- Minor severity – The issue or flaw may interrupt the app and cause it to act less than optimally, but it won’t prevent it from performing all of its functions.
- Major severity – The flaw or issue will affect a significant number of the app’s features and capabilities.
- Critical severity – The flaw or error will be so severe that it will seriously impair the app’s general usability and cause a total breakdown of the system.
The severity of the bug will determine how much of an effect it has on the app. Determining bug priority is the next step in the bug severity vs. priority analysis.
What Is a Priority Bug?
The urgency with which a bug must be fixed is referred to as bug priority.
The severity of a bug is taken into account when determining the priority with which it needs to be fixed. Similar to bug severity, bug priority also has a scale:
- Low priority: The bug need not be promptly rectified. Bugs with a high or medium importance should be fixed first.
- Medium priority: Medium-priority bugs may usually be fixed during regular testing and development because they don’t immediately impact customers.
- High priority – High-priority defects need to be fixed right now. They frequently have an impact on the app’s usability, customers, and user experience. They have to come first.
The perception of a bug’s severity in relation to other potential bugs makes it difficult to objectively assess its level of severity. The optimum course of action must be decided by considering testing severity and priority as a whole.
Bug Severity vs. Testing Priority
Establishing bug severity vs. priority, taken together, refers to the overall impact of issues and the order in which they must be fixed. Priority and severity in testing aid testing teams in creating a schedule-compatible plan of action for finding and resolving defects while also enabling them to address the bugs with the highest impact first.- Automation Testing with Python
1. Execution Process:
- Automated Testing: In automated testing, test scripts and testing tools are used to perform tests on the software. The tests are executed by the testing tool, not a human tester. Automation involves creating scripts that simulate user interactions with the application.
- Manual Testing: Manual testing, on the other hand, is performed by human testers who execute test cases manually. Testers interact with the software, exploring it like end-users, and report defects and issues.
2. Speed and Efficiency:
- Automated Testing: Automated tests are typically much faster than manual tests. They can execute a large number of test cases quickly and efficiently, making them suitable for regression testing, repetitive tasks, and time-critical projects.
- Manual Testing: Manual testing is inherently slower and can be time-consuming, especially when conducting repetitive tests. It’s often best suited for exploratory testing and tasks that require human judgment and intuition.
- Automated Testing: Automated tests provide repeatable and consistent results. The same set of automated tests will produce the same outcomes each time they are run, which is critical for regression testing.
- Manual Testing: Manual testing can be subject to human error and variability. The results may not be as consistent, and different testers may interpret and execute test cases differently.
4. Exploratory Testing:
- Automated Testing: Automated tests follow predefined scripts and actions. They are less suitable for exploratory testing, where testers need to investigate the software, try different scenarios, and apply creative thinking.
- Manual Testing: Manual testing is the preferred choice for exploratory testing. Testers can use their expertise and creativity to find defects that automated tests might miss.
5. Initial Setup and Maintenance:
- Automated Testing: Setting up and maintaining automated tests can be time-consuming and requires programming skills or scripting knowledge. However, once in place, they can save time and effort in the long run.
- Manual Testing: Manual testing is relatively quick to set up but can be labor-intensive for repetitive testing tasks. It doesn’t require extensive scripting or programming skills.
6. Test Coverage:
- Automated Testing: Automation can efficiently cover a wide range of test cases, including those that are complex, data-driven, or require testing across multiple environments.
- Manual Testing: Manual testing may have limitations in terms of test coverage, especially when it comes to repetitive or time-consuming test scenarios.
- Automated Testing: While there is an initial investment in creating and maintaining automated tests, they can lead to cost savings in the long term due to increased efficiency and repeatability.
- Manual Testing: Manual testing can be cost-effective for small-scale or one-time projects, but it may become expensive and time-consuming for large and ongoing software development efforts.
In practice, the choice between automated and manual testing often depends on project requirements, available resources, and the specific goals of the testing process. Many organizations use a combination of both approaches to leverage their respective strengths and achieve comprehensive test coverage.