Automated Test Failure-Triage System

“As a tool team, we initiated this project as part of our Shift Left Initiatives. Our goal was to streamline the process of handling test failures to reduce turnaround time.”

Mentored By: Dhaval Parikh

Proactive Feedback Provided By: Sudhindrasridharan

Landing Page Of Centerized System

Introduction

In the dynamic world of software development, efficiency and reliability are paramount. Continuous integration and delivery (CI/CD) rely heavily on automated testing to ensure the integrity of applications. Jenkins, a cornerstone in orchestrating test runs, simplifies these processes, yet navigating through jobs and tabs can be time-consuming. This challenge is where our innovative Triage System shines.

The Triage System serves as a critical bridge between identifying and resolving test failures swiftly. It employs a structured approach, analyzing logs, screenshots, and diagnostic data to categorize issues stemming from code defects, test script glitches, or environmental factors. By automating this triage process, teams accelerate problem resolution, minimize errors, and reduce downtime in development cycles.

The primary focus of the Triage System is to streamline the triage process for test failures. As automated testing detects issues, the Triage System plays a pivotal role in categorizing, analyzing, and offering valuable insights into failures. These insights include identifying the root cause, analyzing previous occurrences, identifying potential bugs, pinpointing offending microservices/components, and ensuring test consistency.

Problem Statement:

Aligning test failures with corresponding bugs is crucial yet challenging, primarily due to factors such as distinguishing genuine failures from flaky test issues. The triage process is essential for differentiating between failures caused directly by tests and those indicating actual software issues. Moreover, it accelerates the conversion of test failures into actionable bugs.

Automating Test Failure Triage Process

The Refinement Process:

Refers to the systematic steps taken to enhance the accuracy, reliability, and relevance of identified issues or failures.

Challenges in the Current Process

The current triage process involves several manual steps to identify and categorize test failures, including ignoring flaky tests and determining genuine failures. However, this manual approach can be time-consuming, error-prone, and inefficient, especially as the scale of testing increases.

What to Automate?

Focus on automating the following aspects of the triage process:

• Flaky Test Detection: Identify and exclude flaky tests from further consideration automatically.

Flaky GRU Data Model

• Failure Type Identification: Categorize failures based on predefined criteria (infra issues, API latency, UI issues, etc.).
• Root Cause Analysis: Automate the process of determining the underlying cause of each failure.
• Predictive Bug Analysis: Automate the process of assigning a bug to test failures based on Machine Learning and Anomaly detection algorithm.
• Issue Reporting: Automatically generate reports or notifications for identified issues, integrating with existing tools and workflows.
• Failure Trend: Historical Trends of failures in a job.

• Execution Time Trend: Each job time taken trend.

• Execution Count Trend: Each Job test execution count trend.

• Test Consistency View: What all tests are consistent (Pass, Fail, Flaky) actress releasees.

• Health Check and Circuit Breaker: Each Services health check and breaker.

• Test Comparision View: Compare tests with any historical date or run.

Any time we can have two date tests comparison with diff

Top Failures:

• Rerun of Failure Test: Effective and Faster run of failure tests at any moment.

Rerun dashboard and Tracker:

Rerun Result to Cross Check rerun triggered by Hub-Spoke

Stack Trace Classification: Test Impacted due to unique stack trace.

Test failed due to unique stack traces

Why Automate the Refinement Part?

Automating the refinement part of the triage process offers several advantages:

1. Efficiency: Automation reduces the time spent on manual review and decision-making, allowing teams to focus more on productive tasks.

2. Consistency: Automated processes ensure that each test failure is assessed using the same criteria and algorithms, reducing variability in triage decisions.

3. Scalability: As the number of tests and frequency of test executions increase, automation can handle larger volumes of data more effectively than manual methods.

4. Accuracy: Automated tools can leverage machine learning algorithms or predefined rules to make more accurate assessments of test failures, distinguishing between flaky tests and genuine issues.

5.Last but not least: Data in today’s world data is the source of all solutions, based on data collected during the process makes base for future enhancements of Predicative and AI/ML based models to further improve triage process.

How to Implement Automated Test Failure Triage System?

To effectively automate the triage process, consider the following steps:

1. Data Collection: Implement robust logging and data collection mechanisms during test executions. Capture relevant information such as logs, screenshots, performance metrics, and test environment details.
2. Flaky Test Identification: Develop algorithms to detect and flag flaky tests. This may involve statistical analysis of test results over multiple runs to identify inconsistencies.
3. Failure Categorization: Use machine learning models and rule-based systems to categorize test failures into different types (e.g., infrastructure issues, API latency, UI rendering, business logic errors).
4. Root Cause Analysis: Automate the analysis of failure patterns to determine the root cause. This could involve examining historical data, comparing current failures with known issues, or correlating failures with recent code changes.
5. Integration with Issue Tracking Systems: Automatically create or update issues in bug tracking systems (e.g., Jira) based on automated triage results. Link test failures to corresponding bugs or issues for further investigation and resolution.

Best Practices for Implementing a Triage System

Implementing an effective triage system for automation test failures requires a strategic approach that balances technical proficiency with operational efficiency. To start, fostering a culture of collaboration and communication among development, QA, and operations teams is crucial. This ensures that when a failure occurs, the necessary knowledge and expertise are immediately accessible for swift resolution.

Central to the triage process is the establishment of clear criteria for prioritizing issues. This involves categorizing failures based on their impact on the product and business objectives. High-impact issues that affect critical functionalities should be addressed first, while less critical ones can be scheduled for later analysis.

Automation in data collection is another best practice. Leveraging tools to automatically gather logs, screenshots, and system states at the point of failure can significantly reduce manual effort and speed up diagnosis. Additionally, integrating these tools with your Continuous Integration/Continuous Deployment (CI/CD) pipeline ensures that failures are detected as early as possible.

Regularly updating and refining your test cases based on historical data from triaged incidents can prevent recurring issues. Finally, documentation plays a vital role, maintaining comprehensive records of past failures and resolutions aids in quicker troubleshooting in future incidents. By embedding these practices into your triage system, you ensure not only rapid response but also continuous improvement in your testing processes.

Valuable Teammates:

Having reliable and dedicated teammates purely freshers and interns is crucial when building any system. Each member brings a unique set of skills and perspectives to the project, contributing to its success. Working together efficiently, they can overcome challenges and achieve goals effectively.