In modern development, software quality isn’t a “nice to have” – it’s mission-critical. In an era of continuous deployment and intense competition to satisfy users, even minor bugs can have significant consequences. For example, a misplaced hyphen once caused NASA to lose a $169 million rocket, while a single miswritten decimal point led to a $475 million product recall. In 2024 alone, businesses worldwide lost an estimated $3.1 trillion due to poor software quality, with 40% of companies reporting at least one critical software failure every quarter. These real-world disasters demonstrate that poor quality practices can result in substantial financial losses, security breaches and irreparable reputational damage.

Yet, despite the high stakes, there is often confusion surrounding the roles and terminology intended to ensure quality. You might hear acronyms such as QA, QC and QE being used interchangeably. Does a “QA team” just comprise testers? What is the role of “Quality Engineering”? Many product leaders and startup founders are unclear about the differences between Quality Assurance, Quality Control and Quality Engineering, and how they work together to prevent costly bugs. This confusion is understandable, as all three are related to ensuring software excellence. However, each plays a distinct role in a mature quality strategy. In fact, misunderstanding these roles can contribute to project failure.

In this article, we will clarify the meaning of QA, QC and QE, explain how they differ in focus and approach, and demonstrate why you likely need all three. We will also explore how these functions complement each other within modern practices such as DevOps and 'shift-left' testing, and how engaging external QA partners (for example, via QA and testing services or software testing outsourcing services) can help to integrate a holistic quality strategy. By the end, you will have gained practical insight into building a comprehensive quality programme that will keep your software (and your business reputation) safe.

Definitions at a Glance

First, let's provide concise definitions of each term. Below, we define quality assurance (QA), quality control (QC) and quality engineering (QE), including their respective focuses, purposes, typical performers and places in the development life cycle.

Quality Assurance (QA)

Quality assurance (QA) is the discipline of establishing processes and standards to ensure that products are built correctly. It is process-oriented and proactive, aiming to prevent defects by improving the development of software. Put simply, QA makes sure you are doing the right things in the right way so that the end product meets quality expectations.

Quality Control (QC)

Quality control (QC) is the practice of verifying that a product meets the required quality standards. It is product-oriented and reactive, focusing on identifying defects in finished products (or increments) through testing and inspection. In other words, QC ensures that the results of the development process meet your expectations by identifying any bugs or deviations from the requirements.

Quality Engineering (QE)

Quality Engineering is a holistic, engineering-driven approach to quality that integrates quality practices throughout the entire development lifecycle. An evolution of QA, QE is proactive and continuous, emphasising that quality is everyone’s responsibility from day one. In practice, QE involves building quality into the product from the outset using technical tools, automation and collaboration to prevent defects rather than merely detecting them later on.

Now that we have a basic idea of each term, let’s compare QA vs QC vs QE side-by-side on key dimensions.

Key Differences Between QA, QC, and QE

Although people sometimes use 'QA' or 'testing' to cover all quality activities, in truth, QA, QC and QE have distinct focuses and mindsets. One useful summary is as follows: QA is process-oriented, ensuring that the right things are done the right way, while QC is product-oriented, verifying that the results match expectations. QE takes this further by ensuring that quality is an integral part of the development process. In other words, QA plans for quality, QC verifies quality, and QE engineers quality into the product from the outset.

To clearly see how they differ, consider their purpose, timing in the development cycle, methods used, mindset, and tools. The comparison table below outlines these differences:

Aspect	Quality Assurance (QA)	Quality Control (QC)	Quality Engineering (QE)
Primary Purpose	Prevent defects by ensuring the process is correct. QA sets up standards and methods so the end product meets requirements. It is about assurance of quality upfront.	Detect defects by inspecting/testing the product. QC validates the software meets specifications and catches issues before release (quality control of outputs).	Build in quality and continuously improve the product and process. QE aims to minimize defects through early involvement and ongoing enhancements, ensuring quality is ingrained at every step.
Timing	Begins early (planning/design) and continues throughout development. QA activities are often done before or alongside development (e.g. defining processes, reviewing designs) and revisited during and after implementation for process improvement.	After development or at milestones. QC typically occurs in the testing phase of each cycle – after code is written. It’s often concentrated toward the end of a sprint or release to verify the product’s quality before shipping.	Integrated from the start to finish. QE practices run throughout the SDLC, from initial design discussions to final deployment. Quality checks (like automated tests) happen continuously during development (every code commit) rather than only at the end.
Methods & Activities	Process-driven techniques: QA uses methodologies like establishing standards, creating test plans, process audits, and reviews (code reviews, design reviews) to improve quality. QA may involve some manual testing planning and oversight of test execution, but its core is defining “how” to test and build (not just doing tests).	Testing and inspection techniques: QC relies on test execution – e.g. running manual test cases, exploratory testing, and using automated tests to find bugs. It uses tools like testing frameworks, bug tracking systems, and checklists to verify the product. Essentially, any activity that examines the actual software (functional testing, performance testing, etc.) to identify defects is QC.	Automation and engineering practices: QE heavily emphasizes automated testing, tools integration, and advanced techniques. This includes setting up CI/CD pipelines with automated test suites, using static code analysis, performance monitoring, and even AI-driven testing. QE also involves practices like infrastructure-as-code for consistent environments and monitoring in production. The QE approach combines development and testing into one continuous workflow.
Mindset	Preventive – “Quality by process.” QA is all about preventing issues by doing things right the first time. The mindset is proactive: eliminate the root causes of bugs (e.g. unclear requirements or bad practices) so that fewer defects are created. It’s often summarized as “prevention over inspection.”	Detective (Reactive) – “Quality through inspection.” QC assumes that even with good processes, bugs can occur, so the mindset is find and fix the defects in the product. It’s reactive in that it deals with output from development, with an eye toward correcting issues before the product reaches the customer. In short, “test it to catch any mistakes.”	Proactive & Continuous – “Quality as everyone’s job.” QE promotes a “shift-left” mindset where quality is considered at every step, by every team member. Rather than waiting for bugs, QE constantly asks: how can we improve quality right now? It combines prevention and detection, emphasizing fast feedback loops and continuous learning. This is aligned with a DevOps mentality of shared responsibility for quality.
Tools	Quality management and planning tools: e.g. requirement management systems, test plan documentation, checklists, process frameworks (like ISO standards or agile testing practices). QA may use tools for tracking process compliance, risk analysis, and reporting (e.g. dashboards for defect trends to improve process). It’s less tool-intensive than QE, focusing more on standards and documentation.	Testing tools: e.g. manual testing templates, test case management software, defect tracking systems (for logging bugs), and possibly automation tools for executing tests (like Selenium, JUnit) – though automation in QC is often script-based and after coding is done. QC might also use specialized tools for performance testing, security scanning, etc., as part of the inspection process.	Integrated toolchains and automation platforms: QE uses the DevOps toolchain – for example, version control + continuous integration servers running automated tests on each commit, containerization for test environments, and monitoring tools for runtime quality. QE teams leverage CI/CD tools, code quality analyzers, performance monitoring (APM), and advanced test automation frameworks. They often build custom tools or scripts to fit quality into the development pipeline seamlessly.

(The above differences illustrate the complementary nature of QA and QC: QA establishes the foundation for quality, while QC verifies the outcome. In contrast, QE is embedded in engineering and DevOps practices.)

It’s important to note that these roles are not mutually exclusive. In fact, a high-performing software team will utilise all three: robust QA processes, diligent QC testing and QE practices to automate and integrate quality. As one QA expert said, it’s time to end the 'versus' mindset – QA, QC and QE each have their own strengths and the goal should be to utilise them all together. In the next section, we will see how these three areas work together as part of a unified quality strategy.

How They Work Together

Despite their differences, QA, QC and QE are all integral parts of the quality process. A mature software organisation does not prioritise one over the other; rather, it uses all three to complement each other and ensure comprehensive quality control. Think of it as a safety net with multiple layers: QA sets up the net, QE incorporates automation into its fabric, and QC catches anything that slips through.

In practical terms, here’s how these roles collaborate in a modern development pipeline:

Planning & Requirements (Upfront QA): At the very start of a project, QA comes into play by establishing quality objectives and processes. For example, a QA lead might define a quality plan that includes coding standards, acceptance criteria for features, and the types of tests needed. They ensure the team agrees on “what good looks like.” This might involve QA facilitating risk assessments or setting up a test strategy for the project. By having QA involved in early design and planning meetings, potential quality issues can be spotted before any code is written (for instance, noticing a requirement that is too vague or a design that might be hard to test – and then refining it). This up-front QA work is aligned with the “shift-left” approach, where quality considerations move closer to the project’s inception. The result: the development starts on the right foot, with preventive measures in place.
Development Phase (QE in action & ongoing QA): As developers start coding, Quality Engineering practices kick in. QE encourages every developer to write unit tests for their code and perhaps use techniques like Test-Driven Development. Quality engineers (or automation QA engineers) may build automated test suites alongside the code. These could include integration tests, API tests, and other checks that run whenever new code is integrated. Modern teams often adopt a CI/CD pipeline – for example, each time code is committed, an automated build and test run is triggered. This is QE’s hallmark: continuous testing embedded in the development pipeline, giving fast feedback on code quality. During this phase, QA folks are not idle either – they might be monitoring the process (ensuring that code reviews are happening, for instance) and preparing high-level test cases or data for later stages. The key here is collaboration: developers, QA, and QE specialists work closely. If an automated test fails, developers fix the issue immediately (a QE mentality of addressing problems in real-time). This tight DevOps integration means quality is being built and verified simultaneously with development, not afterward. It reduces the chances of big surprises at the end of the cycle.
Testing & Validation Phase (QC with support of QE & QA): Once a feature or iteration is fully built, it goes into more formal testing – this is classic Quality Control territory. A QA/QC team (which might simply be the QA team wearing a “tester” hat) now executes detailed test cases on the integrated product. They perform manual exploratory testing to exercise the application in ways automated scripts might not, looking for usability issues or edge-case bugs. They also run any manual test suites needed (for example, specialized tests that are hard to automate). At this stage, QA ensures the test execution aligns with the plan and that all requirements are covered. QE contributes by providing the robust automated test results from CI – for instance, by now there may be a full regression test suite automated, so the QC testers primarily focus on new functionality and edge cases. If any defects are found, they are logged (often in a tracking tool). Importantly, when bugs are identified by QC, it’s not just about fixing them; QA will analyze them to understand if there was a process lapse (e.g., was there a missing unit test or an unclear requirement?) – feeding that insight back as a loop for process improvement. Meanwhile, if everything passes QC, the feature is ready for release. QC thus acts as a critical filter before deployment, but it’s bolstered by all the QA/QE work that came prior, meaning far fewer issues should be found at this late stage in a well-oiled process.
Release & Beyond (Continuous Improvement): After deployment, the quality story isn’t over. QE practices often extend into production monitoring – tracking performance metrics, error rates, and user feedback in real time. For example, a QE approach might involve setting up alerts if a new release causes an unusual spike in errors or a drop in response time, so the team can react quickly. This is sometimes called “shift-right” (applying quality checks in production). The QA role at this point might conduct a post-release review – were there any incidents? What lessons can be applied next time? In agile teams, QA is often involved in sprint retrospectives to suggest process tweaks that enhance quality on the next cycle. This continuous improvement mindset closes the loop, ensuring the learnings from QC (and real-world use) feed back into QA process updates and QE enhancements. Over time, the collaboration of QA, QC, and QE leads to a virtuous cycle: processes get better, automation coverage grows, and fewer defects escape to later stages.

In a highly collaborative environment, the boundaries between QA, QC and QE become more fluid, which is a positive development! For example, developers may take part in testing (a QE principle is that everyone is responsible for quality), and QA analysts may assist in defining automated test scenarios (thus bridging the gap between QA and QE). Modern methodologies such as Agile and DevOps encourage this integration. DevOps, in particular, promotes a culture of shared responsibility, in which developers, QA analysts and operations staff work together towards common quality goals. A QA/QE combined approach is central to DevOps and is often referred to as 'continuous quality'. Techniques such as continuous integration/continuous delivery (CI/CD) rely on QE to automatically test each code change and on QA to ensure that the correct tests and standards are in place for these pipelines. Meanwhile, shift-left testing (a DevOps and Agile trend) means that QA and QE activities occur earlier than in traditional models, catching defects when they are cheapest to fix. Conversely, 'shift-right' practices such as observability testing and chaos engineering can be viewed as QE extending into operations, ensuring quality of service in live environments.

To illustrate how these roles complement each other, imagine a scenario in a sprint: a QA lead starts by outlining acceptance criteria and a test plan for new features (so everyone knows the definition of “done”). During development, a quality engineer on the team helps developers write automated tests and set up a staging environment that mirrors production for testing – by the time the code is done, a battery of automated tests have already validated most of it. Then a QC tester (or the QA lead acting as tester) manually explores the feature, finds a minor edge-case bug the automation didn’t catch, and logs it. The team fixes it immediately. After release, the QA lead holds a brief retrospective and notes that the missed edge-case could be covered by an automated test next time – the quality engineer then adds that to the regression suite. This way, QA, QE, and QC form a feedback loop that drives continuous quality improvement. As one industry handbook put it, all three practices are “crucial, and they complement each other… Quality is a journey, not a one-time activity”. Organizations often mature their quality approach by starting with basic QC (testing), then adding QA process discipline, and eventually embracing QE for full lifecycle quality integration.

In summary, the QA, QC and QE teams work best together. The QA team creates the roadmap and culture for quality, the QE team builds the technical infrastructure and early feedback mechanisms, and the QC team provides the human touch and validation to ensure nothing is overlooked. This collaboration guarantees higher software quality and faster delivery - the ultimate goal for any development team.

The Role of External Partners in QA/QC/QE

For many start-ups and even established companies, setting up this kind of multifaceted quality operation in-house can be challenging. You may not have the resources to hire separate QA leads, a team of testers and automation experts for QE, and this is where external QA partners can help. Working with a specialised software quality assurance partner through QA and testing services can help you to integrate QA, QC and QE practices efficiently into your organisation.

In today's market, outsourcing parts of your quality process is commonplace and often a strategic move. In fact, outsourcing QA tasks has become commonplace among modern companies, as it provides access to expert talent and established best practices without the time-consuming process of building a team from scratch. A capable QA partner can implement a quality framework tailored to your needs quickly, drawing on experience from many projects. This often includes providing QA consulting to establish good processes and documentation, dedicated testers for QC to conduct rigorous manual and automated testing, and engineers for QE to set up automation pipelines and integrate with your development workflow.

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Here are a few ways an external partner can boost QA, QC, and QE in your organization:

When selecting a QA outsourcing partner, look for one that understands the balance between QA, QC and QE, and that can support all three areas. Clear communication and alignment are essential, so the partner’s team should work as an extension of your own, using the same project tracking tools and collaborating in real time. Many companies find that, by outsourcing testing and automation, their internal developers and product managers can focus more on core product innovation, safe in the knowledge that the product’s quality is in good hands.

In essence, leveraging an external QA/QE partner can fast-track your journey to quality maturity. It’s like having a specialized pit crew for your software: they bring the processes, the testing rigour, and the engineering automation needed to ensure quality at speed, which is especially valuable if you’re scaling up or lacking certain expertise in-house. Whether through QA and testing services or broader software testing outsourcing services, an external partner can implement the right mix of QA (process improvement), QC (thorough testing), and QE (automation & integration) to help you deliver a flawless product.

Conclusion

Today, software teams face the dual challenge of delivering quickly and reliably. It is vital to understand the difference between QA, QC and QE, and to use each effectively, in order to meet these demands. Quality Assurance establishes the roadmap and preventive discipline; Quality Control provides checkpoints to identify defects; and Quality Engineering incorporates quality into the product through automation and continuous improvement. These are not just buzzwords; they are complementary facets of a well-rounded quality strategy.

By structuring your team and processes to include all three, or by partnering with experts who can provide them, you can ensure that issues are identified early, costs are reduced (remember that a bug identified in the requirements or coding stage is much cheaper to fix than one identified after release), and user trust is earned through the delivery of a robust product. In practical terms, this results in happier customers, smoother launches and more time for innovation instead of firefighting bugs.

Remember, software quality is not achieved by accident; it’s engineered by design, assured by process and verified by testing. QA, QE and QC each contribute to this mission. By appreciating their differences and orchestrating them together, you can navigate the complex journey of software development with confidence without sacrificing quality for speed. Ultimately, this results in software that works and delights, and a development process that is proactive rather than reactive with regard to quality. This is a win-win situation for your team and your end users.

Guide QA

What is the Difference Between QA, QE, and QC?