Software Testing Optimization: Avoiding the Pitfalls of Over-Testing and Under-Testing The Dilemma of Achieving Optimal Testing in Software Testing Thorough software testing aims to identify and resolve potential issues before they impact users, ensuring a high-quality user experience. However, optimal testing levels can be hard to achieve for most quality assurance (QA) teams. An optimal testing level requires balancing testing thoroughness, coverage, and speed with resource allocation. This formidable challenge is further complicated because what constitutes an “optimal” level varies significantly across projects, teams, and the evolving tech landscape. To achieve optimal testing in software testing, you need to make strategic decisions by assessing risk, prioritizing testing areas, and allocating resources effectively. Both under-testing and over-testing can create risks and carry costs. In this article, we’ll share some tips for avoiding these extremes, finding your optimal testing level, and implementing an optimized, effective software testing strategy. The Risks and Costs of Under-Testing Under-testing offers the path of least resistance, with multiple incentives conspiring to distract your team from hidden risks. Pressure to accelerate development cycles and meet aggressive launch deadlines can tempt teams to cut corners on testing. Resource constraints make another compelling case for development teams strapped by budget limitations and talent shortages of skilled personnel. However, while these pragmatic rationales seem to make sense under pressure, in the long term, under-testing exposes your organization to hidden risks that outweigh any short-term gains. Missed Bugs and Errors First and most obviously, there’s the risk of missing bugs and introducing errors into your code. Overlooked defects can trigger crashes, functionality issues, or user interface glitches, directly affecting user satisfaction and engagement. These issues can escalate into systemic problems if not identified and addressed early through shaft-left testing, requiring more complex and costly fixes later. You can spend more time and effort to fix bugs than you would have if they were caught early on, ultimately resulting in delays you tried to avoid by under-testing. Increased Technical Debt and Maintenance Costs A “build now, fix later” mentality can put your development team in growing technical debt. Untested temporary fixes and workarounds accumulate over time, making future modifications more difficult and time-consuming. What you put off today must be fixed tomorrow. As technical debt builds, so do your long-term software maintenance costs. First, there is the direct expense of paying personnel to perform the tests that should have been done already. Less obviously and more insidiously, you must pay indirect costs, including productivity losses from downtime, compensation to affected customers, and potential legal liabilities arising from software failures. Instead of your customers paying you, you may end up paying them. Additionally, the time constraints from a growing technical debt can keep you from developing new and much-needed features. Impact on Customer Trust and Brand Reputation If your brand gains a reputation for releasing buggy software, you risk losing customer trust and turning away new prospective customers. Remember, Cyberpunk 2077’s disastrous launch, where glitchy experiences and game-breaking issues forced the company to refund customers and resulted in their game being removed from the PlayStation store? Employees felt they were stretched too thin from all the testing demands, a situation that could’ve been avoided with an efficient testing strategy. When products fail to meet quality expectations, customer sentiment immediately suffers damage. This generates decreased loyalty and negative reviews, achieving the opposite of what you need for brand growth. Missed bugs, high costs, and lost trust outweigh any benefits you gain from under-testing. Simply put, there is no scenario where under-testing makes strategic sense. The Dilemmas of Over-Testing To avoid under-testing, some brands fall into the opposite extreme of over-testing. This carries its own dilemmas. While initial testing phases often identify the most significant bugs, subsequent extensive testing may yield fewer critical discoveries, producing diminishing returns for the time invested. Testing becomes perfectionism, promoting an overly cautious approach where the fear of potential bugs results in excessive testing beyond practical limits. An overemphasis on exhaustive testing across all areas, regardless of impact or risk, misallocates valuable time and staffing resources just as surely as under-testing can. Over-testing tendencies often stem from the absence of well-defined testing goals and measurable success criteria. If you don’t know when to stop testing because you’ve achieved your testing goals, your team can default to over-testing, stretching your resources thin in an attempt to cover all bases. This can trigger significant consequences that mirror the disadvantages of under-testing. Delays in Time-to-Market Where under-testing leads to premature market releases, over-testing delays your time-to-market. Excessive testing unnecessarily extends your software development cycles. This holds back your product releases, which can cause you to miss market opportunities. While you’re still testing, competitors with faster testing strategies are already out there taking your customers. Wasted Resources and Increased Project Costs While under-testing wastes resources and increases costs after product release, over-testing simply shifts the same waste to the development phase of the software life cycle. As with under-testing, you end up paying for testing you wouldn’t need to do if you had a better strategy. In addition to these direct costs, you pay for the opportunity costs of wasting resources that could be deployed more productively elsewhere. You could develop your next software launch and plan company growth instead of wasting time on unnecessary testing. Finding Your Optimal Testing Level So, how do you find the optimal testing level for your software testing needs? QA key performance indicators can help you harmonize your test metrics with your test value and balance manual and automated testing procedures. Key Indicators of Testing QA metrics define your testing goals, enabling you to measure your test effectiveness to see whether you’re testing too much or too little. Vital QA KPIs include absolute numbers such as test cases run, escaped bugs, and test costs, as well as derived numbers such as test coverage, reliability, and test effort. Test Coverage Metrics vs. Test Value When evaluating your test effectiveness, consider not only test coverage but also test value. For your tests to translate into practical value, they must improve functionalities critical to your application’s stability and user experience. Your testing procedures should also save your team time and money. Ensure high-value tests by assessing the impact of potential defects uncovered and prioritizing high-risk areas. Consider other practical criteria such as defect detection rates, product quality improvement, and productivity gains from time saved. Balancing Manual and Automated Testing An optimal testing strategy should achieve a strategic balance of manual testing and automated testing. Automated tests increase efficiency for repetitive, high-volume tests. Manual tests enable you to catch bugs missed by automation tools, uncover hidden defects through exploratory testing, and address the impact on users through user experience testing. To optimize your testing, develop guidelines for determining where your team will use automated testing and where you’ll use manual testing. Strategies to Ensure Optimal Testing Once you’ve determined your optimal test level, you can deploy proven strategies to achieve optimized testing. Vital best practices include taking a risk-based approach, running continuous testing, implementing a test pyramid defined below, focusing on critical user journeys, and constantly updating your testing strategy. Risk-Based Approach to Testing Risk-based testing prioritizes components, features, and functions that carry the highest risk of impacting system stability and user satisfaction when they fail. To implement a risk-based approach, identify critical business functionalities that can affect your customers and your company in the event of failure, as well as potential failure points that can trigger failure events. For example, a brand selling software to financial services providers might prioritize bugs impacting customer security. Continuous Testing and Integration Continuous testing reduces bugs by promoting early and ongoing detection and resolution of software defects. A continuous testing strategy encompasses both continuous integration (CI) of software updates into code repositories and continuous deployment (CD) of code updates into production environments. A continuously updated CI/CD pipeline optimizes your testing by reducing the proliferation of bugs in your pre-production and post-production code. Implementing a Test Pyramid Strategy A software test pyramid visually depicts levels of testing according to increasing levels of abstraction, typically placing unit tests at the bottom of the pyramid and ascending to UI tests. A test pyramid strategy can help you optimize your testing level by serving as a guide to allocate your efforts across varying levels. This enables you to concentrate higher-volume tests at lower levels where they will have the most impact on maximizing efficiency and coverage. For example, you might deploy automation to help you perform more frequent tests on the unit level so your manual testing team can focus on other levels or follow up on the unit level as needed. Tailor your pyramid strategy to your specific technology stack and project requirements. Focusing on Critical Paths and User Scenarios Focusing on your most critical user paths that impact user experience can optimize your efforts. This ensures that your testing addresses the functionalities most likely to impact your end user. You can also optimize critical path testing by using techniques such as customer journey mapping, monitoring analytics data on user behavior, and consulting with product managers and UX designers. Regularly Reviewing and Adjusting the Testing Strategy Just as continuous testing helps optimize your software, continuous updating optimizes your testing strategy. Review your testing strategy and performance regularly to ensure your approach stays aligned with your project goals. Conduct periodic reviews of how your testing strategy is incorporating emerging technological advancements and best practices. Establish a standard routine and schedule for testing strategy reviews. Your review should involve critical stakeholders who can help assess the effectiveness of your current practices and suggest informed adjustments. Cultivating a Balanced Testing Culture Optimized testing must become part of your company’s QA culture to achieve and maintain a balance between under-testing and over-testing. QA should resist “build now, fix later” pressures and foster a quality-first mindset, prioritizing project timelines to allow adequate time for thorough testing without over-testing. At the same time, they should appreciate that it’s impossible to staff QA and meet all their testing requirements without significant costs and hiring burdens. The changing nature of tools and technologies requires constant learning, which can be difficult for in-house staff to pursue while keeping up with testing workloads. To overcome this dilemma, crowdsourcing or outsourcing your testing offers strategic options to extend in-house testing capabilities. These strategies are especially valuable for projects requiring diverse environments or specialized expertise, enhancing test coverage and efficiency. Consider whether crowdsourced or outsourced testing can help you achieve a more balanced QA testing culture and optimize your testing level.