Taking Your First Steps with GenAI in Quality Engineering

Generative AI (GenAI) is increasingly being recognized for its potential to enhance quality engineering by generating content from existing information to achieve known outcomes. However, determining where to begin can be challenging.

Key Activities for GenAI Implementation

• Reviewing Requirements/User Stories – Use GenAI to analyze and refine requirements, ensuring clarity and completeness.
• Generating Test Cases/Scenarios – GenAI can quickly generate diverse scenarios, reducing the manual effort involved.
• Generating Test Scripts – Generate test scripts, or agile session sheets, that can be used for manual testing.
• Generating Automation Code – Focus on small functions rather than entire frameworks to incrementally enhance your automation suite.
• Generating Bug Reports – GenAI can help standardize bug reports, making them more useful for developers and save you time during the execution process.

Choosing the Right Starting Point

When choosing where to start, identify the activity that causes the most pain or time loss and poses the least risk if the outcome isn’t perfect. This strategic choice will free up time to invest in other areas of the lifecycle.

Start Small and Scale Gradually

Remember, the key to successful GenAI implementation is to start small. Master one activity before scaling to others. By doing so, you can gradually build confidence and expertise, ultimately enhancing your quality engineering processes with GenAI.

Which GenAI tool to use?

There are many free or low cost GenAI tools that are available today. Here are some tools you can consider:

• ChatGPT
• Gemini
• Claude
• Microsoft Copilot

In most cases you can use the free versions of these tools, but be aware that there may be limits on transaction rates, and your data may be used for training. Speaking of which…

Security & Privacy

Data security & privacy is a critical concern for GenAI usage. Some vendors offer paid versions that provide greater data security and privacy features.

Evaluate the data privacy policies associated services to ensure they align with your organizational requirements.

NEVER Put Sensitive or PII Information Into GenAI Tools!

Quick Start guide to Prompt Engineering

So you’ve identified the activity you want to automate, you’ve selected the GenAI tool of preference…Now to write your first prompt!

Use a robust prompt engineering pattern like R.I.S.E. (Role, Input, Steps, Expected Output) to help guide GenAI to produce the desired results. The following is an example prompt for creating high-level test scenarios:

# Role: You are a software tester
 
# Input: I will provide a requirement
 
# Steps: I want you to generate high-level test scenarios. You should ensure that you generate positive and negative test cases, using equivalence partitioning and boundary analysis.
 
# Expected Output: The response should be in a table with the following headings: 
- TS-ID: A unique test scenario identifier starting with "TS-" 
- Description: A description of the test scenario 
- Type: A value of "Positive" or "Negative" that indicates if the test case is a positive or negative scenario. 
- Expected Outcome: The expected outcome from the test scenario

R.I.S.E is just one pattern, so try experimenting with different ones to see what works best for your input & output.

Experiment and Have Fun!

Author

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