How Bug Analysis Improves Software Engineering Postmortems 2023
So, after countless hours of coding, testing, and debugging, your software project has finally been released into the wild. It’s an exciting milestone, but as a diligent software engineer, you know that the work doesn’t end there. Now it’s time to conduct a post-mortem analysis to extract valuable insights for the next phase of your project. But wait, there’s one crucial piece you might be missing – a bug analysis postmortem.
What Is A Bug Analysis Postmortem?
Bug analysis, a systematic examination of software defects that occur during development and testing, holds the key to dissecting software failures, understanding their underlying causes, and setting the stage for improvement. In this blog, we’ll embark on a journey to explore the significance of bug analysis and how it can shape the future of software engineering.
Why Bug Analysis For Software Development Matters
Bug analysis is pivotal in software engineering post-mortems, where failures are analyzed and transformed into learning opportunities. By meticulously examining each reported bug, its root causes, and its impact on the system, developers and project teams can extract invaluable insights. Let’s take a closer look at why bug analysis matters.
Bug Analysis Through The Power of Data
Within your bug database lies a goldmine of information waiting to be explored. One facet of bug analysis involves delving into this treasure trove of data, crunching the bug classifications, and discovering the areas where the largest number of bugs originate. By unraveling these patterns, you gain a deeper understanding of the issues at hand, enabling you to implement targeted processes that reduce the occurrence of similar bugs in the next phase of your project.
Identification and Classification of Bugs
During bug analysis, each reported issue undergoes careful examination, identification, and classification based on its severity, impact, and priority. This step allows you to prioritize bug resolution and allocate appropriate resources to fix critical issues promptly. Furthermore, bug classification provides a window into the patterns and trends of bugs that surface during software development, empowering you to anticipate and tackle them proactively.
Understanding Root Causes
Bug analysis goes beyond quick fixes by aiming to uncover the root causes behind reported issues. Through code examination, tests, and system behavior analysis, developers can trace the origins of bugs. Understanding these underlying causes allows you to address core issues rather than merely treating the symptoms. By doing so, you can significantly reduce the likelihood of recurrence, paving the way for more stable and reliable software.
Improving Testing and Quality Assurance Processes
Analyzing bugs opens the door to evaluating and enhancing testing and quality assurance processes. By scrutinizing bugs that manage to slip through testing, teams can identify gaps in test coverage, insufficient test cases, or ineffective testing methodologies. Bug analysis sheds light on areas that require improvement, ultimately leading to more robust testing practices and higher-quality software releases.
Enhancing Software Documentation and Knowledge Sharing
Bugs often expose gaps in software documentation, such as incomplete or outdated instructions, unclear requirements, or a lack of user guidance. Bug analysis can serve as a catalyst for identifying these documentation deficiencies, prompting the team to update and improve documentation accordingly. Moreover, the insights gained from bug analysis can be shared with the broader development community through knowledge sharing platforms, fostering collective learning and growth.
Implementing Preventive Measures
The ultimate goal of bug analysis is to implement preventive measures that minimize the occurrence of similar bugs in future software releases. By analyzing patterns, trends, and commonalities among reported bugs, developers can identify areas that require code refactoring, architectural improvements, or additional testing measures. Bug analysis acts as a feedback loop, allowing teams to continuously iterate and enhance their software development processes, ultimately elevating the overall quality of their products.
It’s not just our team at SPK that emphasizes the importance of post-mortems for software engineering; industry leaders like Atlassian also stress their significance. Atlassian highlights the critical role post-mortems play in learning from failures, improving processes, and preventing future incidents. Here are a few recommendations from Atlassian to ensure a successful post-mortem:
1. Set clear objectives: Define the purpose and desired outcomes of the post-mortem to provide a focused direction for the analysis.
2. Assemble the right team: Gather individuals with diverse perspectives and expertise to comprehensively evaluate the failures and their implications.
3. Document incident details: Capture thorough documentation of the incidents, including timelines, actions taken, and their outcomes, to facilitate accurate analysis.
4. Analyze root causes: Dig deep into the root causes of the failures, examining both technical and non-technical factors that contributed to the bugs.
5. Identify action items: Identify actionable steps and recommendations based on the analysis, ensuring that the insights gained lead to tangible improvements.
6. Share lessons learned: Communicate the findings and lessons learned with relevant stakeholders, enabling knowledge dissemination and preventing similar incidents in the future.
What Outputs Should A Bug Analysis Postmortem Drive?
To add value to your bug analysis, we suggest you focus on it driving these outputs:
Address Test Code Coverage Gaps (Examples from Atlassian):
- Function coverage: how many of the functions defined have been called.
- Statement coverage: how many of the statements in the program have been executed?
- Branches coverage: how many of the branches of the control structures (if statements for instance) have been executed.
- Condition coverage: how many of the boolean sub-expressions have been tested for a true and a false value?
- Line coverage: how many lines of source code have been tested.
Add additional Automated Testing in the pipeline such as Static Analysis Tools.
Address Code Complexity.
- See if there is a correlation between the number of bugs found and the code density/complexity.
- Refactor code to create modular sections/blocks.
Enforce coding standards. For example:
- MISRA (Motor Industry Software Reliability Association) (C, C++)
- CWE (Common Weakness Enumeration) – Security Flaws –see C# Handout
- CERT – Carnegie Mellon – Security (C, C++, Java, and Perl)
- DISA STIG v3 and v4 (Defense Information Systems Agency- Security Technical Implementation Guides
- CWE/SANS Top 25
- OWASP (Open Web Application Security Project) – Several Languages
- Microsoft’s C# Coding Conventions
- Address Developer Maturity:
- Enforce Code Reviews.
- Ensure shadowing Senior Developer with Junior Developers
How To Complete A Bug Analysis Post Mortem: Methodologies and Insights
Now that we understand the importance of bug analysis and what it should drive, let’s explore how you can complete a bug analysis post-mortem.
Informal vs. Formal or Intensive
You will first need to determine how intensive you want the analysis. For the scenario that follows, the bug analysis was a less intensive or informal review.
In this scenario, we reviewed a random sample of ¼ of the bug database. A more formal review would include reviewing more data. Only one person from the QA team performed the analysis for the informal scenario. For a more formal review, you could include other reviewers such as an outside resource, like an independent auditor.
A Sample Methodology
For the scenario, the QA personnel reviewed each bug from the sample and put it into one of the following classifications:
- Requirements – bugs that are usually caused by non-existent, or unclear requirements
- Code – coding errors and code integration bugs
- Test – this includes incorrectly logged bugs, unclear functionality (which could also be a requirements bug), and issues that can’t be reproduced
- Suggestions – all of the suggestions and requests for new or improved features
You may have different classification systems, but most issues will break down similarly.
A Sample Finding
In this real-life scenario, the analysis included 77 bugs. The number in each classification was as follows:
- Requirements: 10
- Code: 35
- Test: 14
- Suggestions: 18
The initial finding was that the development team was not performing code reviews for all of the features and that some developers were skipping or limiting unit testing. Included in the scope of the next project phase was a re-commitment to unit testing and code reviews.
If there were more requirements bugs, then the team would know to improve its requirements management processes for the next phase or project.
If more test bugs were discovered, then the team would have to determine whether it was getting the documentation and support it needed; if the team members were simply making too many mistakes and needed further training; or if the makeup of the team or its leadership had to be changed.
A large number of suggestion bugs might mean that the project wasn’t really meeting the needs of the customer. In that case, you should again review the scope and features of the application with your customers.
Bug Analysis: A Springboard to Success
Bug analysis is not just an optional step in the software development process; it’s an indispensable tool for continuous improvement and success. By diving deep into each bug, classifying them, understanding their root causes, and leveraging the insights gained to improve processes, you pave the way for more reliable, robust, and high-quality software.
Remember, the journey doesn’t end with the release of your project; it’s only the beginning. Embrace the power of bug analysis, learn from the failures, and propel your software engineering endeavors to new heights.