As an app and browser testing expert with over 10 years of experience validating software on thousands of real devices, I can definitively say test case prioritization is critical for efficient and effective quality assurance.
Prioritizing test cases to execute higher priority tests first directly translates to better defect detection, faster feedback, and higher quality software.
In this comprehensive guide, we will walk step-by-step through everything you need to know to start prioritizing test cases like an expert, including:
- Why test case prioritization matters
- Different techniques to prioritize test cases and how to leverage them
- Specific factors to consider when determining test case priority
- Measuring the effectiveness of your prioritized test suites
- Common challenges and expert-recommended solutions
- Best practices to immediately improve your test efficiency
I will explain each concept in a beginner-friendly manner with real-world examples you can apply based on my own extensive experience.
If you‘re ready, let‘s get started exploring the incredible benefits of test case prioritization!
Why Proper Test Case Prioritization Matters
Many testing teams do not prioritize test case execution, either running scripts in the order created or based on simplistic sorting like alphabetical name.
This causes slower defect detection, longer feedback loops, and lower quality software.
Studies analyzing the same test suites show prioritizing test cases can detect 30% more defects in a given test cycle.
Other benefits of effective test case prioritization include:
- Faster time-to-market by front-loading critical test coverage
- More efficient use of limited testing time and resources
- Increased test coverage and script execution pace
- Detecting regressions quicker by focusing on impacted areas
How Does Test Case Prioritization Work?
Test case prioritization refers to strategically ordering test cases to execute based on priority factors like:
- Risk – Will defects have high user/business impact?
- Test criticality – Which test cases are most important?
- Recent changes – What code was just added or modified?
- Usage frequency – What features have high usage?
- Historical defects – Which areas had past issues?
By thoughtfully assessing each test area across these dimensions, tests can be staged in priority groupings that focus execution on highly critical areas first.
Types of Test Case Prioritization Techniques
There are several different types of techniques used to determine intelligent test case priorities:
1. Coverage-Based Prioritization
Coverage-based means using code coverage amount or metrics to determine test case priorities:
- Statement Coverage: First test cases that execute higher numbers of code statements
- Branch Coverage: First test cases that hit more logic branches
- Modified Condition Coverage: First test cases that execute more decision outcomes
For example, here is a simple comparison of test cases based on statement coverage amounts:
| Test Case | Code Statements Hit | Priority Order |
|---|---|---|
| Login Tests | 26 | 1 |
| Checkout Tests | 17 | 2 |
| Search Tests | 12 | 3 |
Running test cases hitting larger code footprints first like Login tests maximizes coverage.
2. Risk-Based Prioritization
With risk-based prioritization, test cases that verify higher risk areas like frequently used features or complex workflows get top priority.
We assess risk through metrics and dimensions like:
- Customer usage patterns – Runs on critical journeys
- Past production defects – Hit historically weak spots
- Code complexity – Tests complex logic branches
- Operational sensitivity – Covers payment, login, etc.
By combining risk data points, risky test scenarios bubble up as top priorities.
3. Requirements-Based Prioritization
For requirements-based strategies, we prioritize test cases validating the highest priority requirements first.
To do this, assign priority scores to requirements based on dimensions like:
- Customer priority – What‘s most important to users?
- Requirement complexity – How hard is it to implement and test?
- Requirements volatility – How frequently is this requirement changing?
Then tally cumulative priority for test cases mapping to those capabilities.
For example:
| Test Case | Design Req. | Implementation Req. | Platform Req. | Total (Ascending) |
|---|---|---|---|---|
| Login | P1 | P2 | P3 | 6 = 1 |
| Settings | P2 | P1 | P2 | 5 = 2 |
4. History-Based Prioritization
With history-based strategies, past test case failure rates determine priority. The test cases that have failed most often historically get top billing.
For example, if we assign priority order just based on past failure counts:
| Test Case | Past Failures | Priority Order |
|---|---|---|
| Checkout | 102 fails | 1 |
| Login | 34 fails | 2 |
| Search | 12 fails | 3 |
This quickly surfaces the flakiest areas to provide extra coverage.
5. Cost-Aware Test Prioritization
The cost-aware technique prioritizes test cases based on how expensive they are to run. Cheaper test cases get priority.
Cost dimensions like:
- Execution time – Faster automated checks first
- Environment needs – Tests requiring less resources prioritized
- Maintenance costs – Lower cost scripts preferred
Enables maximizing total testing ROI.
How to Prioritize Test Cases In Practice
Now that you know the types of techniques, let‘s walk through practical examples of assessing test cases across various priority factors:
Critical User Journeys
What key customer workflows bring the highest business value? Targeting these first catches issues impacting important user goals.
For example:
- Signup funnel for subscription app
- Purchase journeys for ecommerce site
- Content consumption flows for media site
Validating these end-to-end brings massive value.
Usage Frequency
What features and areas do users interact with most? Having defects here severely degrades overall experience.
For example:
- Search functionality
- Homepage
- Account management
Fits the 80/20 rule testing what customers actually use.
Past Production Defects
What areas historically had more defects? These tend to be weaker spots still requiring extra testing diligence.
- Lookup past 6-12 months of production incident trends
- Identify components with chronic issues
- Use risk-based testing on these components
Reduces regression of known systemic issues.
Code Churn and Recent Changes
What underlying code has been recently added or modified? New and altered code poses high regression risk.
- Static code analysis highlights recent git commits
- Call graph analysis identifies impacted test coverage areas
- Focus test debt paydown in these sections
Catches inadvertent side effects early.
Feature Complexity
What test cases exercise more complex application logic? Complexity leads to undetected corner case bugs.
Assess areas like:
- Algorithm efficiency
- Multithreading deadlocks
- Race condition handling
- State management logic
Forces higher test scrutiny for trickier code.
Measuring Test Case Prioritization Effectiveness
We can leverage metrics to measure how well our test case prioritization is working.
Average Percentage of Faults Detected (APFD)
APFD measures the weighted average of when defects are detected during a test run.
The higher the APFD metric, the earlier critical defects are being detected. Values from 50%-100% are good.
As shown above, Test Suite 2 detected defects much earlier leading to far higher APFD score. Its prioritization works better.
This quantifiable metric confirms when our prioritization technique improvements are working.
Common Test Case Prioritization Challenges
While extremely beneficial, test case prioritization does introduce some challenges:
1. Analysis Paralysis
Continually re-calculating priority metrics leads to "analysis paralysis". This slows down capability testing velocity.
Mitigation: Define frequency cadence for reassessments balancing speed vs optimization.
2. Test Dependencies
Many test cases build on earlier steps, so failures block additional execution:
Mitigation: Structure independent test cases when possible. Also sequence test dependencies properly in priority order.
3. Optimization Complexity
Complicated algorithms to programmatically optimize 1000s of combinatorial test paths:
Mitigation: Start simple with core prioritization dimensions. Add incremental complexity over time and leverage ML.
4. Manual Effort Overhead
Manually re-ordering test cases repeatedly requires significant toil:
Mitigation: Automate test mapping analytics to priority factors so ordering updates automatically.
By understanding common challenges upfront, we can make informed tradeoffs while maximizing value.
Best Practices for High-Impact Test Case Prioritization
Based on hands-on experience boosting test efficiency, here are my top tips:
1. Clarify Prioritization Dimensions
- Outline 4-5 core prioritization factors aligned to your quality goals
- Get stakeholder input to grade relevance
- Distill into an easy to interpret checklist
2. Automate Prioritization Where Possible
- Score tests programmatically based on code, requirements, history data
- Output spreadsheet with sortable priority order
- Refresh regularly to enable frequent iteration
3. Validate with APFD Measurement
- Use APFD to measure improvements from prioritization
- If score too low, reassess dimension weighting
- Provides continuous improvement feedback loop
4. Incorporate Tester Feedback
- Solicit additional priority considerations from actual testers
- They often have specialized domain insights
- Fine tune prioritization checklist
Adopting these best practices will help you maximize return from test case prioritization in your organization.
Key Takeaways
Here are the big lessons I want you to remember about test case prioritization:
🔹 Extremely effective for lowering defects and raising release quality
🔹 Multiple techniques to determine logical test ordering
🔹 Assess priority across risk, coverage, usage, complexity, history
🔹 Validate impact with APFD metrics
🔹 Continually refine prioritization checklists
Defining an expertly-crafted test case prioritization approach tailored to your unique project needs can transform efficiency.
By starting to prioritize what test cases your team executes and when, you will accelerate your capability delivery, time-to-market, and release quality.
I hope this deep dive has demystified this critical testing strategy – happy prioritizing!
Let me know if any questions pop up on your test case prioritization journey.
