Companies prioritizing speed over software quality risk facing extensive technical debt that can cause other serious problems preventing them from reaching set business goals. Luckily, QA teams can contribute to the mitigation of TD impact with a set of priority measures described in the article.
Technical debt (TD) can hugely affect project performance, overall software functioning, and even a team’s mental health. A desire to roll out IT products quicker than competitors forces companies to prioritize deadlines rather than focus on writing clean code. As a result, businesses pay for this choice with their financial and time resources.
But it doesn’t have to always be like that. In this article, I’ll walk you through what TD means, where it comes from, its consequences, and how QA teams can contribute to its successful mitigation. So, without further ado, let’s get into it.
Understanding the concept
TD is a term used to describe all the accumulated rework that must be done due to framework updates, code changes for future architectural improvements, or postponement of fixes due to tight deadlines.
Typical TD examples include work required to fix repeated code, optimize inefficiently structured code, handle issues with performance, fulfill postponed code refactoring, and more.
There are different types of TD. According to one classification, it can fall into 2 categories — intentional and unintentional. The former appears purposefully to deliver new functionality to market quickly, so it can be tracked and documented for further remediation. The latter occurs due to a lack of software engineering expertise and high software complexity. It can be difficult to identify and document and requires further modification of development processes.
Another categorization suggests that TD has 10+ diverse types, including infrastructure, architecture, requirement, service debts, among others.
Major causes behind TD occurrence
Multiple reasons can contribute to TD accumulation, these include:
- Tight deadlines. The constant pressure to deliver IT products to market quicker often forces development teams to apply quick solutions for writing code. Software engineers must prioritize speed over writing optimal code, which causes risks of additional rework in the future.
- Quick technology evolution. Due to the fast-paced development of the IT industry, components such as tools, frameworks, and libraries can quickly become obsolete. In addition, when software engineering teams lack knowledge of new development solutions, issues related to integrations, code dependencies, or maintenance can arise.
- Inexperienced development teams. A lack of understanding of best practices, industry standards, code writing guidelines, can lead to the low quality of code. In the long run, it can result in poor architecture, challenges with updating code and its further integration with other code parts.
- Ineffective project management. The scarcity of code documentation, shortage of communication between project members, faulty planning activities, issues with project supervising and prioritization lead to overall decreased code quality.
Unfortunately, TD is a common problem faced by many organizations. While meeting time constraints and hoping to postpone some activities until later, it’s easy to skip them completely, as new project tasks appear often, bringing new strict deadlines and complexities.
The most challenging TD consequences
Why is it so important to manage TD and try to prevent it at all costs? I’d say if not addressed swiftly, it can significantly affect software quality, stability and lower project performance.
When striving to speed up development cycles, companies can face serious challenges related to the accumulation of TD that can be costly to eliminate, among them:
- Exceeded budget limits. According to McKinsey research, some companies spend up to 20% of their technology budget on dealing with TD.
- Business continuity issues. Depending on the gravity of problems in software functioning, disruptions to essential operations may appear.
- Poor possibilities for innovation. Instead of advancing current software features or introducing cutting-edge technologies to outperform competitors, companies must spend time on resolving TD.
- Low team morale. Let’s be honest — resolving TD isn’t the most interesting project activity, though important, of course. However, when development teams have to focus a significant part of their efforts on it, chances are high their motivation and interest in the work can decrease.
QA engineers’ assistance in minimizing TD
To ensure overall success, I think that all project members should be responsible for avoiding these unpleasant consequences. Software engineers fulfill activities related to proactive management of risks associated with TD accumulation. However, QA teams can make significant contribution too.
Often the most time-consuming part of QA efforts relates to performing extensive regression testing. Fulfilling it in parallel with mitigating TD requires specific QA experts’ attention to planning, working with test artifacts, and introducing the best quality engineering practices.
Therefore, I’d suggest considering the following priority steps:
- Focus on wise management to optimize QA efforts
It’s rarely the case that the whole sprint is dedicated to mitigating TD. On the contrary, teams strive to balance work on TD with developing or advancing software features. Both these activities are related to code changes and require regression testing afterward.
Therefore, it’s important to carefully plan the QA scope during the sprint.
For instance, when managers know that the current sprint will include TD resolution, regression tests should be performed only after all activities on new functionality and TD are finished. This helps avoid double regression testing within the sprint (after novel features and TD), thus optimizing QA efforts and contributing to building effective release schedule.
2. Give due to attention to controlling test coverage
As QA experts need to constantly analyze the scope of changes to plan optimal test coverage, it’s crucial to manage test model, test documentation and only add necessary test scenarios to the regression testing suite. To quickly filter and find the required test scenarios, the test model must be clear and structured.
For example, when managing tasks on TD, QA managers must understand their complexity for both QA engineers and developers, as this can differ greatly. Consider a scenario: software engineers update a complex algorithm to enhance performance. Here, from both the user’s and QA’s viewpoint, only the result needs verification. Conversely, if developers simply add a new library dependency, QA engineers may need to retest every feature to ensure no problems arise. In these situations, a high-quality test model can streamline the QA process.
3. Introduce continuous testing paired with test automation
Continuous testing allows verification of software quality throughout the entire pipeline without waiting for a full build to be released. It can identify any software issues early in the SDLC, establish round-the-clock QA processes, provide fast and ongoing feedback on software operation, ensure quick mitigation of risks, and accelerate testing activities.
Test automation, being an indispensable component of continuous testing, helps cope with extensive amounts of time-consuming regression as well as unit, integration, performance, and security checks. It cuts testing time significantly, improves overall software quality due to boosted test coverage and minimization of human error, and optimizes operational expenditure in the long run. What’s more, correctly set up automated workflows ease mitigation of TD for QA teams and help software engineers to be confident in the quality and stability of developed features.
To ease test automation adoption, experienced QA vendors can offer proprietary test automation frameworks that, for instance, have an AI-driven module, which recognizes tests failures and reports them on the fly. It helps enhance testing accuracy and reduce the time required for decision-making after obtaining results of test failure analysis.
To cut a long story short
TD is the result of rapid technology evolution and prioritizing speed over software quality that eventually may lead to serious problems on the project — budget overspending, business continuity issues, limited opportunities for introducing innovative technologies, and, unfortunately, unhappy teams.
QA teams can make essential contribution to minimizing TD by relying on proficient QA management, controlling test coverage, and setting up test automation and continuous testing.
These combined efforts help prevent and eliminate defects early in the SDLC, decrease operational expenditure, accelerate releases, and, most importantly, reduce TD.
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