In order to have better view of the quality of defects, instead of measure using numbers of defects (which can be manipulated), can I measure the % of root cause. Example codes problems, missing use cases, missing test cases? Please share your experiences and thoughts.
In functional testing services, software testers report bugs every day. It's important to understand in which category the bug belongs. Bugs can be caused by many factors, including: Unclear requirements Poor communication during development Frequent changes to project requirements Bad coding practices Poorly documented code Compromises made to save time Lack of communication between team members Poor requirements, architecture, or design
Bugs can be categorized bugs by analyzing common patterns. These patterns can include:
Code-related issues- Here are some common coding issues: Repetitive code Bad variable names Not using comments Language overload Not backing up code Complicated code Not asking questions Not planning in advance
Missing use cases: A missing use case is a use case that lacks interaction information, which can indicate missing requirements. simple use case name may not sufficiently describe the use case details that affect the derived requirements
Data-related issues: Data-related issues can arise at any stage of the data entry process, from data collection to data integration. Some data related issues include: a.Data quality issues: These include: b.Missing data: Can be caused by intentional or unintentional omissions c.Duplicate data: Can skew business intelligence d.Inaccurate data: Can be caused by human errors, such as misspelled names or wrong ZIP codes e.Ambiguous data: Can be caused by misleading column headings or undetected spelling errors f.Data governance: Poor data governance can lead to quality issues g.Data format issues: Data can come from diverse sources with different formats and structures h.Data security: More data means more opportunity for security breaches i.Inconsistent data: Can be caused by missing data or inefficient data management
4.Out of bound bugs - Out-of-bound bugs are a type of software bug that occurs when a user interacts with the software in an unintended manner. These bugs can happen when a user: Enters a value or parameter outside the limits of unintended use Makes logical and arithmetic errors that exceed the allowable boundaries of a specified operation Interacts with the software in a manner that is outside its logical capabilities
You can also classify bugs into multiple categories based on their nature and impact. These categories include:
- Functional bugs
- Logical bugs
- Workflow bugs
- Unit level bugs
- System-level integration bugs
- Security bugs
- Syntax errors
This is a great idea, but not new. I have seen RCA (Root Cause Analysis) being done in several places, not as a replacement to other processes but as complementary. Most test management tools should easily support such categorization and analysis.
Having said that, this is not an easy task especially if you want it to be properly done. Similar initiatives tend to start with deep investigation of each bug, e.g. by asking five whys, and slowly end as being ignored or a very shallow reason for the failure is chosen.
Finally think of what do you want and can achieve, many times you will find out the the reasons for bugs are organizational and not easy to fix, "missing test cases" is usually a symptom to over stressed development, miscommunication or non aligned development processes.
Absolutely, categorizing the root cause of bugs is a valuable practice in software testing and quality assurance. It helps provide insights into the underlying issues that lead to the occurrence of defects and enables teams to address them effectively. Measuring the percentage of root cause categories can offer a more meaningful and informative perspective on the quality of defects rather than relying solely on the number of defects.
Here is a suggested approach to categorizing root causes:
Analyze Common Patterns: Examine the types of bugs that frequently occur in your projects and identify common patterns. This could include code-related issues, missing use cases, missing or inadequate test cases, configuration problems, data-related issues, or other relevant categories specific to your domain.
Define Root Cause Categories: Based on the identified patterns, establish a set of root cause categories that accurately represent the underlying causes of defects. It's important to have well-defined and mutually exclusive categories to ensure consistent classification.
Assign Root Cause Categories: When a bug is identified, analyze its root cause and assign it to the appropriate category. This can be done by conducting root cause analysis techniques such as reviewing code, analyzing requirements, performing impact analysis, and leveraging testing techniques like regression testing and exploratory testing.
Track and Measure: Maintain a record or database of categorized bugs, along with their respective root causes. This enables you to track the distribution of root causes over time and calculate the percentage of each category.
Use Metrics for Improvement: Utilize the root cause metrics to drive improvements in the software development and testing process. Identify areas that consistently contribute to specific root causes and take proactive measures to address them. For example, if missing use cases are a significant root cause, emphasize the importance of comprehensive requirement gathering and use case analysis.
By categorizing the root cause of bugs, you gain valuable insights into the strengths and weaknesses of your development and testing processes. It helps identify areas for improvement, enables targeted training or process adjustments, and guides decision-making regarding resource allocation and risk mitigation.
Remember, the effectiveness of categorizing root causes depends on the accuracy of the analysis and the consistency of categorization. Regular reviews and refinements of the categorization scheme may be necessary as new patterns and trends emerge.
Overall, by measuring the percentage of root cause categories, you can focus on addressing the underlying causes of defects rather than just the symptoms, leading to more effective quality improvements in the long run.
Here are a few common ways to categorize the root cause of bugs:
- Coding Errors:
- Syntax Errors: Bugs caused by incorrect grammar or syntax in the code.
- Logic Errors: Bugs resulting from mistakes or flaws in the code's logic or algorithms.
- Data Type Errors: Bugs caused by using incorrect data types or performing incorrect type conversions.
- Boundary Errors: Bugs occurring when code does not handle boundary values correctly.
- Design Issues:
- Architectural Flaws: Bugs resulting from design decisions that impact the overall system structure or behavior.
- Poor User Interface Design: Bugs caused by user interface design issues that affect usability or user experience.
- Inadequate Error Handling: Bugs occurring when error conditions are not properly handled or reported.
- Environmental Factors:
- Configuration Issues: Bugs caused by incorrect configuration settings or environment variables.
- Platform Compatibility: Bugs occurring due to incompatibilities between the software and the underlying platform or dependencies.
- Network or Infrastructure Problems: Bugs resulting from network issues, infrastructure failures, or external services not functioning correctly.
- Data Issues:
- Data Corruption: Bugs caused by data corruption or inconsistencies in the system's data storage or databases.
- Invalid or Incomplete Data: Bugs resulting from incorrect or missing data inputs or data not meeting validation rules.
- Data Integration Errors: Bugs occurring when data is not properly synchronized or integrated between different systems or modules.
- Third-Party Dependencies:
- Bugs caused by issues with third-party libraries, frameworks, or APIs used in the software.
- Incompatibilities or Version Conflicts: Bugs arising from using incompatible versions of external dependencies.
- Process or Workflow Problems:
- Inadequate Testing: Bugs resulting from insufficient or ineffective testing practices.
- Communication Issues: Bugs caused by miscommunication or lack of communication between team members or stakeholders.
- Insufficient Documentation: Bugs occurring due to lack of proper documentation or outdated documentation.
You can always think of different ways to categorise.
Although the idea of performing root cause analysis is sound, I have yet to see a good categorization scheme. In my experience, trying to categorize root causes tends to yield categories that are too broad to be meaningful and useful or categories that are so fine-grained that they tend to be difficult to put causes into.
So far, my preferred approach has been to track proposed preventative actions and keep track of the number of RCAs that have proposed a given preventative action. Of course, the action itself may have a different impact on various incidents, but understanding that carrying out a certain preventative action would have mitigated or prevented a specific number of incidents can help prioritize which preventative actions to implement.
With more than 10 years of QA experience and association with a software qa consulting firm, I can certainly say that tracking and classifying the root cause of issues is one of the most beneficial practices in software testing.
- During reporting and investigation, we have been employing this strategy as a drop-down in the JIRA tickets.
- The drop-down is pre-populated with different reasons for DEV team selection.
- Sharing a screenshot for the same with different categorization values for the 'root cause' type.
The tracking of the "root cause" of the issues gives us an understanding of the areas missed by the DEV team and improvements required in the development process.