DEV Community: Pavel Novik

QC, QA, and QE: What's the difference, and what does your software really need?

Pavel Novik — Mon, 25 Aug 2025 18:03:57 +0000

Quality isn't a one-size-fits-all concept in software. Different teams talk about quality control (QC), quality assurance (QA), or quality engineering (QE) – sometimes interchangeably, often confusingly. Imagine a startup's app launch goes awry due to a critical bug. One engineer says, "Our testing (QC) failed." Another asks, "Did we even have the right process (QA) to catch this?" A seasoned DevOps lead chimes in: "We need to build quality into development from the start (QE)." All three viewpoints aim for the same goal – better software – but approach it in different ways.

This article breaks down QC, QA, and QE in plain terms, illustrates them with real-world examples, and helps you decide what your software team truly needs.

Quality control (QC): catching defects at the end

Quality control is about inspecting and testing the product itself for defects. In traditional terms, QC happens after development: it's the practice of finding bugs or deviations in the finished software before it ships. ISO 9000 (the global quality management standard) defines QC as "part of quality management focused on fulfilling quality requirements". In other words, QC is a reactive process – it kicks in once code is written, aiming to identify any problems by testing the software against the requirements.

Think of QC as the safety net or the last line of defense. For example, a QC activity might be running a suite of tests on a new app release to ensure all features work as expected, or a human tester performing final checks on critical user flows. In a manufacturing analogy, QC is akin to a factory inspection line where finished products are examined for flaws. If an e-commerce website's checkout feature has a bug, QC is what catches it before customers do.

Key characteristics of QC include being product-oriented and defect-focused. It's about validation: Does the software meet the specifications? Inspection and test execution are major QC components. For instance, testers (or automated test scripts) verify that a bug fix actually resolves the issue and doesn't break anything else. Because QC is typically done late in the development cycle, it's inherently reactive – issues are found and fixed after they've been introduced. This makes QC essential, but if relied on alone, it can be costly and slow (bugs discovered late may delay releases or require rushed fixes).

Quality assurance (QA): building the proper process

Quality assurance shifts the focus from the product to the process. It's about formulating the quality gates that software would need to pass to be released and designing and following a process that prevents defects from entering into the final product. For example, ISO 9000 defines quality assurance as "part of quality management focused on providing confidence that quality requirements will be fulfilled." In practice, QA encompasses all the proactive measures – standards, reviews, methodologies – that ensure you're building the product right. Rather than catching bugs at the end, QA asks: How do we avoid injecting bugs to begin with?

QA is process oriented and proactive. It starts at project kickoff, not after code is written. The QA lead works with product and engineering to plan the test strategy across the entire SDLC, detailing what will be tested, when each layer of testing will run, and how results will be recorded. The team agrees on how formal test documentation must be, pinpoints quality risks early, and sets out preventive actions.

Clear requirements with objective acceptance criteria give everyone a shared definition of done. QA also defines the test environments and data needed, so every build is exercised under realistic conditions. Throughout delivery, metrics such as defect escape rate and time to repair are tracked to drive continuous improvement. By treating quality as a planned, measurable workflow built into the process, teams avoid bolting on fixes at the end and keep defects from reaching users in the first place.

To illustrate, imagine a restaurant kitchen: QA is like the head chef, ensuring that recipes and cooking processes are well-defined and followed diligently, so that each dish is consistently of excellent quality. In software, QA could mean instituting a rule that every new feature must include unit tests, undergo peer code review, be tested by QA engineers, pass integration checks, and confirm it doesn’t break existing functionality before being merged. These steps don't directly test the software (that's the role of QC), but they ensure quality by making defects less likely to occur.

Importantly, QA and QC work hand-in-hand. QA sets up a framework for quality, and QC verifies the results. A helpful way to distinguish between them is that QA is proactive, while QC is reactive; QA focuses on the process, while QC focuses on the final product (the outcome of production). QA might prevent a typo in requirements from ever reaching code, whereas QC might catch a typo in the UI before release. In many organizations, QC is actually considered a subset of QA – one of the activities within a broader quality assurance program. Both are needed: without QC, you can't be sure the final software is good; without QA, you're doomed to keep catching the same bugs over and over in QC.

Quality engineering (QE): quality built into development

Quality engineering takes quality to the next level by embedding it throughout the entire development lifecycle. Quality engineering can be described as a proactive strategy for building quality into products from inception to production. QE can be thought of as a technical branch of QA that builds product‑specific automation frameworks and supporting toolsets. Instead of handing quality off to a separate phase or team, QE embeds automated tests, data‑generation scripts, and deployment hooks directly into the daily workflow.

To make that happen, QE relies on reusable automated test frameworks and tight CI/CD integrations. Unit, API, and UI checks run on every commit, blocking unstable builds and enabling continuous delivery without sacrificing quality. In essence, QE is a holistic, integrated approach that folds quality into every step of the SDLC.

Teams practicing QE focus on shift left testing—exercising code early and often—along with shift right practices such as monitoring and feedback from production. The goal is to find and fix issues as soon as possible, or prevent them altogether, accelerating delivery while keeping the product stable.

QC vs. QA vs. QE : making the right choice

With clear definitions in hand, it's time to answer the big question: What does your software really need – QC, QA, or QE? The unsatisfying but honest answer is almost certainly a mix, depending on your context and maturity. These concepts build upon one another more than they replace each other. Here's how to think about it:

Every team needs basic QC. At a minimum, you must have a mechanism to test your software (whether manual testing, automated tests, or ideally both) before it reaches users. If you have zero QC – no testing or review – defects will escape. For example, in a very early-stage startup, you might not have a formal QA department, but you still perform QC (e.g., running the app and fixing obvious bugs before release). As your team grows, you might dedicate specialists to testing or use QA outsourcing for extra QC. No matter what, ensure you have a safety net to catch critical issues.

Invest in QA processes as you grow. When you find your team frequently firefighting bugs or experiencing inconsistent quality, it's a sign to bolster your quality assurance. This could mean introducing QA plans and test strategies, code reviews, linters, CI builds that run tests, or adopting a formal testing framework. QA is about preventing bugs from entering the finished product and improving consistency. For example, a mid-sized product company might establish a QA role to design test plans, improve developer–tester workflows, and maintain quality standards. If your industry is regulated (finance, healthcare, aerospace), robust QA is non-negotiable – you need formal processes (requirements traceability, documentation, audits) to ensure compliance and reliability. QA will help you sleep better at night, knowing there's a structured process in place to guard quality, not just ad-hoc efforts.

Embrace QE for speed and scale. If your organization is aiming for continuous delivery, rapid iterations, or simply the next level of efficiency and quality, quality engineering is the key. For example, QE has been shown to prevent defects early in the lifecycle, resulting in higher-quality products and reduced development costs. QE is most beneficial for more mature teams or those adopting a DevOps culture. Ask yourself: Are separate QA handoffs causing delays or friction? Are your testers overwhelmed with repetitive checks? If so, start moving toward QE: encourage developers to write and run unit tests as they code, integrate testing into your CI/CD pipeline, and upskill your QA staff to become automation engineers or quality coaches who build and maintain the test automation framework and automated test scripts. This doesn't happen overnight – it's a journey of changing culture and implementing new tools. Start small: for instance, have developers fix bugs found in production along with adding an automated test to catch that class of bug in the future (a QE practice). Or embed a QA engineer into the development team to work on test automation in tandem with coding. Over time, you can achieve the agility of a Google or Microsoft, where quality is integrated deeply and doesn't solely rely on a final QC checkpoint. However, be mindful of your team's maturity – developers may need training and time to take on these responsibilities effectively. Management must also foster an environment where quality isn't sacrificed for speed; rather, speed is achieved because of quality practices.

Context matters. A small startup might lean heavily on QE-style developer ownership simply because it lacks a QA team – that can work if the team is disciplined about testing. A large enterprise with legacy systems may still require a dedicated QA/QC phase for some time due to risk but can gradually automate and push quality earlier. Consider the cost of failure in your domain. If you're deploying software to pacemakers or aerospace controls, you will need exhaustive QA and QC on top of any QE practices. If you're deploying a mobile game update, you can afford more iterative "test in production" (with QE/DevOps practices). In short, align your quality strategy with the criticality of your software's reliability and the speed at which you need to move.

Conclusion: finding your balance

In summary, QC, QA, and QE are three perspectives on the same goal – high-quality software – each suited to different needs and stages:

QC is about verification: testing the end product to identify and correct defects. It's absolutely necessary, but it comes at the end, so don't rely on it alone.

QA is about prevention: establishing a process that yields quality outcomes. It's the foundation for consistently good software, and it makes QC's job more efficient.

QE is about integration: weaving quality into every step of the development process. It's the modern way to achieve both speed and quality, but it requires cultural commitment and intelligent automation.

Rather than picking one, successful teams use all three in harmony. Start by ensuring you have solid QC in place (you know what to test, and you do test it). Build out QA practices to reduce the injection of bugs (get your process under control). And when you're ready to accelerate, adopt QE principles so that quality enablement becomes part of your engineering DNA. As the saying goes, "build quality in, don't bolt it on." If you understand the differences and strengths of QC, QA, and QE, you can apply the right mix for your context. The result will be software that not only meets standards on paper but also delights users in practice, shipped on time with confidence in its quality.

Test automation to accelerate the release of eLearning software without compromising quality

Pavel Novik — Tue, 10 Jun 2025 13:16:42 +0000

Imagine a student preparing for an exam but being locked out of a courseware due to system errors. Or another example. A visually impaired learner is struggling because an accessibility feature isn’t working. As eLearning platforms expand and their complexity rises, such issues can become disruptive and costly.

QA plays a pivotal role in maintaining the effectiveness of educational software, helping avoid technical glitches, accessibility issues, or poor performance that can frustrate learners and undermine the credibility of an educational provider. Specifically, test automation allows project teams to continuously validate software functionality, improve scalability, and *speed up deployments without sacrificing quality. *

Let’s examine why automated testing is so essential for eLearning software, highlight types of tests to automate, and discuss best practices for implementation.

Test automation role in building error-free classrooms

Unlike a live coaching session where a mentor can instantly spot and correct a user’s mistakes, online platforms rely on flawless functionality to provide a smooth learning journey. Test automation helps tackle any software-related problems, offering a range of benefits:

Optimized velocity

Test automation speeds up the testing process, which is confirmed by the latest World Quality Report 2024-25 (WQR) participants, 59% of whom agreed with this fact. Automated tests can run continuously, contribute to faster releases, and provide quick feedback on code changes. For instance, by creating an automation framework from scratch, implementing it into QA processes, and performing test automation activities, a developer of tech-powered learning solutions achieved 7.5 boost in smoke testing and 10.4 speed-up in regression testing.

Boosted testing scope

The WQR states that 61% of its respondents achieved this benefit after implementing automated workflows. It’s not surprising. Automated testing allows the execution of more tests in less time across different devices and OSs, confirming that various modules of eLearning software (quizzes, assessments, multimedia content. etc.) are consistently validated.

Enhanced cost-effectiveness

Although the initial investment in test automation may seem high, long-term benefits outweigh the costs. This is backed up by the WQR interviewees, 58% of whom agreed that test automation became a game-changer for minimizing expenses. Once implemented, it reduces the amount of manual testing and ensures cheaper fixing of glitches by catching them early before they become expensive to resolve after release.

Better accuracy

Test automation executes predefined scripts and prevents mistakes caused by human oversight (e.g. missed test cases), ensuring precise validation of the entire system functionality. For example, a developer of eLearning IT products managed to increase the technical health of a flagship website, 20+ web apps, and a CMS as a result of implementing test automation.

The best candidates to automate during eLearning software testing

Modern educational platforms are sophisticated and incorporate AI-driven features that personalize education experiences and streamline assessments. They process extensive data to tailor course material, deliver instant feedback, and offer interactive chat-based tutoring.

To ensure their thorough testing and simultaneously expedite QA workflows, project teams can consider automating the following tests:

1 Regression

Regression testing ensures that everything that previously worked continues to do so after numerous and frequent software updates. This becomes even more critical for AI-powered components (automated grading systems, chatbots, tools to detect cheating), where small tweaks to models, algorithms, or data can create ripple effects. With automated regression testing, QA teams can minimize the number of issues and streamline time-consuming, repetitive QA activities.

2 Performance

eLearning platforms serve thousands of students simultaneously. Extensive traffic spikes provoke risks of lower software speed and freezes, forcing users to opt for competitors. Automated performance tests confirm the software can cope with a high number of concurrent visitors for a particular period without disruptions. For example, they verify that AI chatbots manage numerous parallel talks or that AI personalization for recommending courses works effectively under high demand.

3 Security

eLearning platforms collect and manage user data, encompassing personal details, academic history, and payment credentials, that’s why they must be 100% secure.

In comparison with manual one-time security testing, automated vulnerability assessment or penetration testing not only detect weak spots and potential entry points for cyber threats but do it continuously during the entire development life cycle. They quickly execute complex test cases, such as failed login attempts or injection attacks, and validate whether software responds appropriately without introducing new problems.

This is crucial for AI-powered chatbots, recommendation engines, and biometric authentication, which handle confidential data.

4 Functional

Functional testing verifies that eLearning software performs its core tasks as intended. Automation of these tests validates the entire application flow — from user login and permissions to learner progress and certifications. It helps identify issues early, ensures consistency across updates, and enhances software stability while reducing manual effort.

5 UI

Verifications of software interface guarantees visually cohesive and user-friendly experiences across devices. By automating such tests, project teams can spend less time on checking the proper alignment and visibility of interface elements, responsiveness of interactive components like buttons, forms, menus, and consistency in themes, colors, and fonts.

6 Third-party integrations

Third-party integrations enable smooth interaction between educational products, error-free connections with payment gateways, communication tools, content providers, and other external services.

Their automated testing ensures that systems interact reliably, endpoints return correct responses, authentication and authorization mechanisms work securely, and data exchange remains efficient. It allows organizations to detect issues early, prevent disruptions, and attain consistent user experience while streamlining testing workflows.

7 Accessibility

eLearning software should be inclusive for everyone, including people with special needs. Automated testing helps quickly and continuously verify color contrast, text readability, alternative text for images, chatbot accessibility, adaptive learning interfaces, AI-generated quizzes, and multimedia content to ensure compatibility with assistive technologies. This helps confirm the software meets standards, such as WCAG, ADA, Section 508, and others.

8 Database

Databases are the backbone of eLearning software, managing everything — from user profiles and course content to progress tracking and payment. Automated database testing goes beyond manual QA, establishing continuous and repeatable checking of data integrity and query operation.

With its help, QA engineers can swiftly detect problems related to data corruption, slow performance of queries, erroneous data structure, and others, confirming users won’t be affected by them. This approach not only accelerates testing time but also *minimizes the risk of human errors. *

Bumps in the road to be ready for

Test automation is a challenging process itself, but when performed within a project dedicated to testing eLearning software, it becomes even trickier.

First, educational solutions have highly dynamic content, including quizzes, videos, audio, animations, to make the learning experience more engaging for users. QA engineers may face issues, as these elements load asynchronously, require user simulation, and can behave inconsistently across various browsers and devices. This may lead to false negatives. The solution? QA teams should thoughtfully design resilient automated scripts capable of managing dynamic content loading and complex user interactions.

Second, educational software supports complex user roles such as students, instructors, admins, each with distinct access and workflows. Testers may encounter challenges ensuring that each role experiences correct interface, permissions, and features. This may lead to gaps in test coverage. The solution? QA teams can implement role-based test scenarios within their automation suite to simulate and validate behavior across multiple user profiles.

Third, educational platforms evolve, user interface may undergo changes, as new features appear, or layouts alter. This can cause frequent test script failures, increased maintenance, and reduced test reliability. The solution? QA teams can utilize Page Object Model to update tests more easily in response to any UI changes.

Boosting effectiveness of automated educational software testing

Here’s a combination of advanced approaches that can assist project teams in accelerating delivery cycles while attaining software excellence:

Embark early. Remember: the sooner you start QA activities, the more chances you detect glitches when they are easier and cheaper to resolve, improving time-to-benefits and minimizing accumulation of technical debt.
Introduce AI. It can help with prioritizing high-risk test cases, analyzing root cause of test failures, and enabling self-healing test scripts that adapt to UI changes, reducing maintenance and increasing test resilience in dynamic educational platforms.
Analyze continuously. Use tools like Allure or TestRail to track test execution, monitor results, and ensure consistent feedback throughout the development life cycle.

Striking a balance

Without a doubt, test automation can’t fully replace manual QA activities, as lots of tasks still require a mandatory presence of a human, especially if we are talking about exploratory or ad hoc testing. But by wisely combining manual efforts with an automated approach, organizations developing eLearning IT products can do it quicker, more accurately, and with less expenses.

Cloud migration testing to support modern enterprises

Pavel Novik — Wed, 24 Jul 2024 17:51:49 +0000

In the modern, fast-paced digitization era, more and more organizations are converting their IT products to the cloud. This is due to the diverse advantages it provides for businesses. For context, a professionally performed migration can significantly optimize budgets by eliminating the need to upgrade and maintain hardware. It allows for more efficient storage of sensitive data protected by built-in recovery mechanisms, enhances collaboration by enabling team members to access data from any device anywhere, and provides round-the-clock analytics for streamlined decision-making. Given these benefits, it’s no surprise that within just one year, IT spending on public cloud services is expected to surpass spending on conventional IT.

Unfortunately, migration paths aren’t that easy to navigate and involve diverse complications, specifically related to **software based on legacy code, **the upgrade of IT products, and multiple software dependencies. With professional quality assurance delivered from the early stages, it may be easier for enterprises to ensure successful migration without data loss or corruption, enable high software performance in the cloud environment, avoid team overload, and prevent any interruptions to crucial business processes.

In this article, I’ll focus on the benefits of cloud migration testing, its vital activities, and valuable tips for its effective execution.

Why QA plays a crucial role in cloud migration process

Despite the widespread nature of cloud migration, C-level executives globally still confront problems that lead to the complete failure or deceleration of half of all such projects. These issues arise from multiple factors, including data security and compliance risks, inadequate planning, the need for comprehensive skill-building across the organization, budget constraints, resistance to change among team members, and challenges in ensuring business continuity.

That is why the contribution of QA in supporting the migration workflows is so significant. When performed from the onset of a transition and supplemented with test automation, QA activities can bring the following benefits:

Boosted confidence. Thorough planning and quality control help detect and rectify software glitches early in the process, thus decreasing the probability of any disruptions or negative influence on business workflows.
Increased effectiveness. When issues of varying severity levels are identified before escalating into full-scale problems, their resolution becomes much faster and cheaper. This proactive approach reduces the number of regression issues, simplifies problem-solving, optimizes resources, and helps meet deadlines.
Mitigated performance risks. With proper testing and identification of issues that have potential to exacerbate in the future, QA engineers confirm that migrated IT products have preserved the same performance rates and deliver a similarly positive user experience regardless of the load.
Improved optimization capabilities. Meticulous testing provides valuable feedback that can be used to unlock the full potential of the cloud environment and ensure adherence to business objectives.

4 essential phases of cloud migration testing to bear in mind

When working on a migration project, I suggest that QA teams split their testing efforts into 4 distinct phases:

1. Get ready

Before the transition itself, it’s vital that QA engineers perform crucial initial activities to confirm that all the information and the application can be seamlessly moved to a new environment. Therefore, it’s a good idea to:

Think about the overall migration pattern (e.g. re-platform, re-factor, re-host), the choice of the platform (e.g. Oracle, IBM Cloud, Salesforce), and service model (e.g. IaaS, PaaS, SaaS) to adjust your testing strategy accordingly.
Consider all functional and non-functional software requirements to enable extensive test coverage and make sure that your test cases include possible risks.
The migration process can be long, especially if the application has complex business logic, multiple intricate functionalities, and gigabytes of data to move. To accelerate the transition and boost testing precision, QA teams should make use of automated scripts.
Pay specific attention to software performance in advance to make sure that after the transition no deteriorations have occurred.
Proactively analyze your software data to make certain it has no issues, discrepancies, or redundancies to enable as accurate migration as possible.

2. Supervise the transition

When migration has started, it’s important that QA engineers are always on alert to swiftly identify and fix arising problems. They should also focus on confirming that moved data is identical to that from the source system and occupies the same position, *no inconsistencies, duplications, or missed data have occurred. *

3. Provide subsequent QA support

After the transition is over, QA specialists should execute diverse tests to ensure failsafe software operation and confirm that no setbacks have appeared. I think the most crucial verifications are:

Functional testing

QA specialists check that all business functionalities don’t deviate from requirements and work exactly as they did in the on-premises environment, meeting user expectations. By running end-to-end scenarios of the required functional testing types, QA teams identify and rectify any errors, verify that all the information has been completely moved and is accurate, complete, and consistent, the application can seamlessly handle errors, and more.

Performance testing

Regardless of the industry, any software application must be able to cope with a high influx of end users, remain operable in the long run, and be effectively scaled as the business grows. Otherwise, the target audience may confront slow operation, freezes, and even crashes.

Therefore, QA specialists conduct server-side performance testing and check the RT for critical business transactions, gauge performance of API calls and database queries, verify software ability to withstand high loads, monitor CPU utilization, memory usage, network latency, and other aspects to ascertain that after migration software performance remains on the same high level.

Cybersecurity testing

Another important aspect to consider is software security, as the application must remain resistant to fraudulent attacks or sensitive data theft and stay compliant with a range of significant industry-specific regulations.

Thus, QA specialists perform cybersecurity verifications, including penetration testing and vulnerability analysis, and check data, infrastructure, and application security (e.g. data encryption, access controls, authentication and authorization) to detect post-migration security breaches and confirm the software is fully protected.

Integration testing

Regardless of the type of software architecture, ensuring the correct functioning of its multiple modules and interactions with external systems (e.g., payment gateways, CRM, ERP) is essential. Therefore, testing experts conduct integration verifications after moving to the cloud to check data flow between various components and other IT solutions, verify API integrations, assess how the UI communicates with the back-end, and more.

Compatibility testing

Successful cloud migration is nearly impossible without compatibility testing, during which QA specialists confirm that migrated systems work correctly across various browsers, devices, and platforms, regardless of their screen sizes, resolutions, or hardware configurations.

Usability testing

It’s difficult to provide smooth and intuitive digital experience without focusing on usability verifications. During testing, QA engineers should make sure that the overall layout and design remain as aesthetically pleasing as they were before the transition, navigation is simple, and users can easily reach their objectives with migrated software as before.

As I’ve already mentioned, migration to the cloud is a highly complex process that can’t be performed overnight. Therefore, I’d recommend QA teams to implement automated workflows. With their help, it’s possible to successfully handle a wide range of time-consuming, repetitive testing activities (e.g. regression, performance, security), speed up QA cycles, minimize risks of human mistakes, and simplify the process of verifying software operation after transition to the cloud.

4. Ensure continuous software efficiency in the new environment

You’ve successfully migrated the entire IT product to the cloud, congrats! However, the work is not finished yet. Establishing a comprehensive monitoring and optimization plan is one more essential component of the process. It provides your QA teams with valuable insights into crucial performance metrics (RT, CPU, memory, network, error rates), overall software health, and probable security vulnerabilities. In addition, with real-time analytics QA engineers can identify areas for improved resource utilization leading to probable cost reduction.

Tried-and-true hacks to simplify QA during transition

To increase the effectiveness of cloud migration testing, I suggest that companies consider some useful tips, namely:

Set up a QA environment that closely mirrors your cloud environment to ensure real-life testing conditions and identify as many defects as possible.
Create a detailed roadmap with objectives, responsibilities, deadlines, and KPIs to make sure everyone is abreast of significant milestones.
Establish effective communication processes so that all involved team members can have clear interaction channels and quickly receive data on any updates or changes.
Don’t forget documentation and reporting to provide extensive test coverage, ensure effective defect management, enable informed decision-making, and support knowledge transfer for new team members.
If organizations feel that they lack solid QA processes and specific knowledge related to cloud migration testing or have problems with in-house team performance, they can engage QA consultants who can support with improving testing workflows and mitigating arising issues.

Conclusion

Transitioning digital solutions to a cloud environment is a rewarding practice that provides business owners with multiple benefits, among which I’d mention better security, agility, interaction, cost-saving, among others.

However, this process isn’t a walk in the park and should be supported by meticulous software testing to make sure the entire application is fully migrated without any deteriorations in its operation.

Test debt 101: practical advice on how QA teams can contribute to its minimization on projects

Pavel Novik — Wed, 24 Jul 2024 17:35:24 +0000

I think almost everyone can remember situations related to their day-to-day life when they postponed some activities until a more opportune moment showed itself or because of other higher priority tasks, and then ended up with a myriad of notifications in the calendar signaling unfinished business. Finally catching up on missed activities can be overwhelming, thus demanding more energy and resources.

Just like in private life, negative consequences can appear within software development projects if teams postpone, miss, or decide not to do necessary tasks, such as running testing activities to meet deadlines. This contributes to the accumulation of large amounts of test debt, making it very difficult to reduce the occurrence of missed defects.

Therefore, in this article I’ll explain what test debt is, how it impacts project results, and share practical tips on how QA specialists can help reduce it for the greater good.

Delving into the definitions and core reasons of test debt

According to a well-known technological research and consulting organization, technical debt is an accumulated, inevitable number of activities that project teams need to fulfill as a result of prioritizing meeting release schedules instead of focusing on software quality.

Test debt, in turn, is identical to technical debt and appears when QA activities are missed, postponed, incomplete, or not maintained in due time. It often presupposes activities related to fixing and enhancing existing tests or creating new tests. The main reasons for test debt include:

Shortage of resources. Insufficient number of testing experts can bring a lot of headaches down the line, such as limited test coverage, lack of automated testing, or skipping vital tests because of low team capacity.
High software complexity. Complex IT products with diverse functionalities and intricate dependencies may make it complicated to create required tests. Also, sometimes QA engineers simply don’t have enough time to run holistic test cases.
Existing technical debt. When this also exists in the project, QA engineers may have challenges with creating new tests for poorly written code or maintaining existing tests.
Running few tests. When under high release pressure or confronting budget constraints, QA specialists sometimes have to disregard holistic system examination and only perform a small number of checks, which, of course, increases the probability of defects in the production environment.
Poorly designed verifications. Sometimes, QA specialists may write tests without considering many variations of needed data, not cover particular functionality with tests, or rely on poor test design and models. In addition, when running them, they may follow only positive scenarios, which leads to unstable software functionality after the release.
Skipping verifying tests. If QA engineers prefer to omit the vital role of scrutinizing their tests or missed some requirements, chances are high that their quality will be low and further maintenance will require a lot of extra effort down the line.
Sticking to an unsuitable environment. If QA specialists run verifications in an environment that differs greatly from that of the end user or client, the failsafe operation of the final IT product version isn’t completely guaranteed.
Missing best practices. Automated tests are written with different programming languages depending on project specifics and clients’ requirements. If QA automation engineers don’t follow set standards, such scripts can be very challenging to update in the future, which can result in lowered test coverage.
Neglecting test update. Over time, the IT product inevitably evolves, new functionality is added, which means that tests must be altered accordingly, and new tests must be written as well. Otherwise, it will be challenging to maintain them.
Skills shortage. If software testing engineers lack competencies related to industrial, technical, and process aspects, in the future the project can face missed tests and insufficient coverage.
Low managerial capabilities. If project workflows are inefficient and are characterized by interaction gaps, inadequate scheduling, poor planning, lack of proper testing strategies, issues with defining what activities should come first then problems with quality won’t be far behind. For instance, performance testing should be done in a separate environment when the software is almost ready to avoid interference by other testing types.

Why unresolved test debt can turn into a real problem

If organizations prefer to postpone problem resolution, they face a higher risk of defects in the production environment, including those affecting critical business functionality, leading to low customer satisfaction and reputational concerns.

One more probable problem relates to higher maintenance costs. Without scrutinizing IT products, more defects at late SDLC stages can appear, and fixing them may take more time and resources. In addition, if test documentation on the project is poor and the team lacks knowledge on the operation of existing software, the accretion of features can be complicated, which decelerates development and hinders cost-effectiveness.

Test debt can also often lead to project delays. When teams spend a lot of time fixing multiple issues, lack solid test automation practices, and write many missing tests, delivery dates are pushed back.

Compromised security is another serious consequence I’d like to focus on. By skipping security testing or missing some vulnerabilities, QA teams increase the risk of breaches and data losses, which can negatively impact the company’s brand image.

What’s more, project teammates are very unlikely to be quite happy resolving test debt instead of upgrading their skills or learning something new, which contributes to low team morale.

How software testing specialists can make a difference

In order to effectively manage test debt on a project, QA manual and automation engineers can consider some tried-and-true practical steps:

Do not bail on automated testing

Test automation introduction can contribute to alleviating test debt on the project. How? With automated testing, QA teams find flaws early in the development process, significantly improve test coverage, cut testing time, ensure ongoing quality control workflows, and receive rapid feedback on the functioning of the IT product. This approach also helps teams meet tight release deadlines, diminish the probability of human error, and decreases testing costs. I’d also recommend executing tests in parallel to achieve desired outcomes even faster.

Keep your test documentation in order

Having a relevant test model that describes the current software state and parts covered by tests, relying on test design techniques, creating detailed, consistent test artifacts, such as test cases, plans, scenarios, reports, checklists, requirements, and timely updating them is of critical importance for minimizing test debt on any project. Why?

First, it’ll help to reach efficient test coverage and minimize the number of defects. Second, it increases testing efficiency as team members will follow accurate plans and know exactly what, when, and how they should do their tasks, which helps prevent double work. Third, it makes it possible for project newcomers to quickly delve into the nuances of the tested IT product and the current project progress.

Always consider tests prioritization during planning

Regardless of the industry QA specialists cater to, their primary objective is to contribute to delivering failsafe software solutions on time and within budget. During planning and testing, it’s important for them to focus on the most critical business features first (e.g., placing orders, payments, searching through product catalogues, which is crucial for eCommerce projects). This way they can avoid expensive post-release defect fixing, meet set deadlines, decrease the probability of user churn because of software failures, sagely allocate resources, and thus diminish the risks of test debt accumulation.

Perform regular tests maintenance and review

During any project, the software will obtain new features or updates with each release, meaning that some parts of the tests can quickly become obsolete, which can only negatively affect the overall software testing capabilities of the team and lead to test debt. That’s why it’s so important for the QA engineers to make sure tests are relevant, accurate, contain no redundancies, issues (ambiguous wording, missed scenarios, etc.), and are written in line with set standards regularly. What’s more, this activity fosters education within a team, as new members can learn from their more experienced colleagues and delve more quickly into software specifics.

Raise awareness

I’d suggest that QA leads educate their teams on the essence of the test debt and its probable adverse impact. As well as ways of preventing or effectively addressing it throughout the entire development process. Thus, it’s possible to minimize its influence in the future, avoid team overload, and manage available resources in a more efficient way. In addition, when teams bear test debt in mind, dedicate some time in each sprint to deal with test debt, and continuously perform audits to find areas with test debt, they can approach testing in a more responsible way and avoid compromising software quality.

Final thoughts

Postponing test activities for the sake of increased speed may bring more harm than good in the long run, causing intricate problems with delivery velocity, software operation, security, team satisfaction, and budget.

To prevent these negative consequences, QA specialists can introduce test automation, take care of test documentation, prioritize and maintain tests, and educate project members on the importance of test debt minimization.