Quality Assurance vs Control in Software

Introduction

In 2012, a major software bug cost Knight Capital $440 million in just 45 minutes. The culprit? A failure in quality control. Shocking incidents like these highlight why QA and QC are critical for software success. Yet, these two terms are often confused. While both aim to ensure quality, they do so in fundamentally different ways. In this blog, we’ll break down the core differences between quality assurance and quality control, explain how they fit into the software testing lifecycle, and explore how to implement both for faster, more reliable releases.

What is Quality Assurance in Software Testing?

Quality Assurance (QA) is a proactive, process-oriented approach that aims to prevent bugs before they occur. It focuses on establishing development standards and improving workflows to embed quality into the product from the beginning.

Key QA Activities:

• Creating documentation and standard operating procedures (SOPs)

• Conducting risk assessments to identify failure points

• Training teams on coding best practices

• Running audits and refining processes

By integrating QA early in the lifecycle, teams build better software from the start.

What is Quality Control?

Quality Control (QC) is a reactive, product-focused approach. It identifies defects in the software after it has been developed, ensuring it meets defined requirements.

Key QC Activities:

• Running functional, performance, and compliance tests

• Identifying and fixing bugs

• Improving usability and user satisfaction

QC is about validating the final output, while QA ensures quality throughout the process.

Quality Assurance vs Quality Control: Key Differences

Building a QA + QC Strategy

Combining QA and QC gives you a complete quality framework. Here’s how to build it:

Strategic Planning

• Define KPIs like defect density and test coverage

• Use risk-based testing for high-impact features (e.g., payments)

• Choose the right mix of manual, automated, and exploratory testing

Resource Allocation

• Align QA and QC teams for cross-functional collaboration

• Use tools like Jira, TestRail, or Selenium

• Balance test coverage, timelines, and budgets

Documentation & Processes

• Maintain updated test plans and SOPs

• Regular syncs between QA, Dev, and Product

• Integrate defect feedback into standups

QA and QC in the Software Testing Lifecycle

Implementing quality assurance and quality control effectively requires embedding them throughout the entire software development lifecycle — not just during testing. Here’s how they play out across key phases:

Development Phase: Building in Quality Early

The foundation of effective QA begins during development. At this stage, the focus is on embedding quality into the codebase and workflows.

• Code Reviews and Unit Testing: Every code commit should be peer-reviewed to catch logical or stylistic issues early. Unit tests ensure each component works in isolation, forming the first layer of defense against bugs.

• Standard Enforcement: Establish and enforce internal standards, such as consistent REST API structures, naming conventions, and UI design guidelines. This reduces ambiguity and ensures maintainability.

• Static Code Analysis: Use tools like SonarQube or ESLint to detect code smells, security flaws, and maintainability issues before runtime.

• Developer-Led QA: Encourage devs to run sanity tests locally, and use tools like Prettier or linters to auto-fix small issues.

Testing Phase: Validating the Product Thoroughly

This is where traditional quality control efforts come into play — ensuring the product behaves as expected and meets all functional and non-functional requirements.

• Exploratory Testing: QA teams test without predefined scripts to identify UX gaps and usability issues. For example, confusing navigation during checkout or unexpected button behavior.

• Error Guessing: Based on experience, testers try likely failure points—such as entering invalid inputs or simulating flaky network conditions—to catch bugs that scripted tests might miss.

• Functional, Regression, and Compliance Testing: Cover core business flows, ensure new changes don’t break existing features, and verify adherence to standards like GDPR or WCAG where applicable.

CI/CD Integration: Enabling Continuous Quality

Modern QA/QC practices thrive when deeply integrated into CI/CD pipelines — ensuring fast, automated feedback loops.

• Automated Regression Testing: Set up test suites to run automatically on each pull request or nightly build. These cover critical flows like login, payments, and onboarding to avoid release blockers.

• Performance and Stability Monitoring: Post-deployment, use tools like New Relic, Firebase, or Sentry to monitor crashes, slow interactions, or resource bottlenecks.

• Flaky Test Detection: Identify and isolate tests that fail intermittently, which could erode developer trust in automation and delay releases.

• Shift-Left Testing & Feedback Loops: Integrate test results and defect reports into sprint standups. This enables faster resolution and makes quality a shared responsibility.

Measuring QA & QC Success

Measuring the success of quality assurance and quality control initiatives is essential to continuously improving software quality and development efficiency. Teams should use both quality metrics and process metrics to gauge the effectiveness of their testing strategies and workflows.

Quality Metrics:

• Defect Density: Number of confirmed defects divided by the size of the software (e.g., per 1,000 lines of code).

• Time to Detect and Fix Bugs: The average time between identifying a defect and resolving it.

• User Satisfaction Scores: Ratings collected through feedback forms, surveys, or support channels reflecting end-user experience.

• Test Coverage: The percentage of code, paths, or requirements covered by automated and manual test cases.

Process Metrics:

• Testing Cycle Time: The duration of each testing phase within the release cycle.

• Test Case Reusability: How often test cases are reused across versions or projects, indicating process maturity.

• Defect Leakage Rate: The percentage of defects that escape from QA into production.

• QA/QC Team Collaboration: Frequency and quality of cross-functional communication, often measured through retrospectives or collaboration tools.

Tracking these metrics consistently allows teams to identify bottlenecks, reduce inefficiencies, and raise the overall quality bar for software releases.

Real-World Examples

• Success Story: Google scaled its mobile testing using a blend of QA and automation-first QC, cutting release cycles by 40%.

• Failure: Knight Capital’s $440M crash due to lack of test validation—a cautionary tale of ignoring QC.

Future Trends in Quality Assurance and Quality Control

• AI in Testing: Tools like Testim or Autify help auto-generate test cases and prioritize based on code changes

• Self-healing tests: Maintain stability with changing UI/UX

• Shift-left testing: Push testing earlier into CI/CD pipelines

• Visual regression testing: Catch UI bugs with pixel-level accuracy

Getting Started with QA + QC

Here are 5 steps to begin implementing quality assurance and quality control today:

1. Define quality KPIs aligned with your business goals

2. Conduct a process audit to find current QA/QC gaps

3. Choose the right tools for collaboration and automation

4. Start shift-left testing with unit tests and code reviews

5. Monitor performance post-deployment and iterate

Final Thoughts

Understanding the difference between quality assurance vs quality control is crucial for high-performing software teams. QA helps you build better products by embedding quality in the process. QC validates those products before they reach users. When done right, they reduce bugs, save costs, and boost user confidence.

Want to get started? Reach out to us for a consultation on scaling your mobile testing pipeline.

See Also:

• Software Testing Lifecycle (STLC)

• How to write a Test Plan

• Traceability Matrix