Does Severity Matter for Software Regression Defects? Let's Explore.
Thank you all for the acknowledgements and feedback on the previous article: "Software Regression - Why it Matters More Than You Think" https://www.dhirubhai.net/feed/update/urn:li:activity:7288668079134232577/?
?? Let’s set the stage for this topic: Your team has been working tirelessly on the latest update. The features are polished, the bugs have been fixed, and the release is ready to ship. But then, during the GA build testing, a regression is uncovered. It’s minor—perhaps low severity—but it’s there. What happens next? Does the severity of the regression really matter?
The Regression Dilemma: To Fix or Not to Fix?
Development teams often weigh the impact of defects against their severity. But when it comes to regressions, is severity even a factor?
Consider this:
From a customer’s perspective, none of this matters. To them, it’s simple: "Something that used to work no longer works." This perceived failure undermines trust, regardless of how trivial it might seem internally.
A Case for Fixing All Regressions
??? Every regression—no matter the severity—deserves attention and resolution before a release or update reaches production. Why? Because once it’s out in the wild, even a minor issue can grow into a significant trust gap.?
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For the engineering teams, triaging and addressing even minor regressions can reveal significant underlying issues in the implementation.
As a well-known adage goes: "Trust takes years to build, seconds to break, and forever to repair." A regression, no matter how small, is a crack in the foundation of that trust.
Quality Over Expediency
?? While timelines and deadlines are important, they should never come at the expense of quality. Engineering sign-off should be contingent upon addressing all regression defects, regardless of their perceived severity. Doing so sends a clear message: We prioritize our customers and their experience above all else.
Looking Ahead: Tackling Escapes ??
This brings us to an important question: What happens when regressions slip through the cracks and make it to production? These are known as escapes, and they represent a unique challenge. In a future article, we’ll dive into strategies for identifying and addressing escapes, particularly those that are regressions.
?? What’s your take? Should severity play a role in addressing regression defects? Have you faced situations where fixing a minor regression had a major impact? Share your thoughts and join the discussion in the comments below! ??
I agree, in principle. However, things can get blurry when, very close to a release date, a regression is found in a rarely-used feature but there is a fairly simple workaround. Even so, the fix for the regression may be risky and could cause a more critical regression or even break the new important feature that customers are waiting for. Now, there are the following 3 options: 1. Allow the release to proceed, with a fairly simple workaround for a regression in a rarely-used feature. 2. Try to fix the regression in a short time, keeping the delay to a minimum but risking a bigger regression or breakage in the new highly-anticipated feature in the release. 3. Hold the release for as long as it takes to fix the regression, and do thorough testing, fixing any other problems found - causing a significant delay to the release, when the customer base was expecting to have the new much-needed feature available already, and not having it available could be affecting their business negatively. Not an easy decision. To me, #1 seems to be the best option here - but there can be different opinions on this.
I agree. Even a trivial regression can have a significant impact if left unresolved, regression issue regardless of size, should be fixed promptly.