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Defect Tracker, Heal Thyself


By Edward J. Correia
December 17, 2007 — 
Many people reading this are doing so while taking time away from one defect tracking system or another. If you’re one of those people, you might never have realized that the data you look at when you’re not reading e-mail can be used—if analyzed correctly—to improve your processes and practices.

In other words, information within the defect tracker can be used to improve the defect tracking process. QA professional Colleen Voelschow has figured out how, and last week shared some of her wisdom with me. Today I share it with you.

“I found myself recommending this to a lot of clients,” says Voelschow, a senior staff consultant with Denver-area test automation and QA services consultancy ProtoTest . “It’s insight they don’t normally turn to.” Instead, organizations usually use the data to tell them what’s wrong with product,” she says. “But information collected on a product’s quality can also be used to evaluate the process quality.”

Defect management, often a responsibility of the QA team, is used as a tool to evaluate and measure the quality of products during both test and production. “This information is typically detailed, up-to-date and publicly available, making it an easy candidate for collecting and evaluating data about the entire software development process.”

By looking at the root cause of the defects—such as ambiguous requirements or complex code—organizations can identify where the process may be breaking down. Voelschow has developed a framework for identifying such process gaps, allowing teams to find these defects sooner in the process, when they are the cheapest to fix.

Key concepts in the framework include an evaluation of the defect tracking processes in place within the organization to identify any changes required to make this evaluation process possible. “Conduct formal defect reviews, including who needs to be involved and what needs to be covered,” Voelschow advises. “Offer advice on how to make this process an objective one, eliminating what may seem like personally directed attacks.”

Because defect information in most cases is already being collected and tracked, this process doesn’t require additional data collection; only a different approach to analysis. “I recommend this as an easy starting point they can troubleshoot on their own,” she says. “It’s easy because I’m not asking them to start a new process or collection of data. They can mine information they already have or go back and look at projects they’re already completed.” This can benefit not just the QA department, but the entire company in its potential to save time and money by finding and addressing the cause of defects sooner.

And based on her nine years of QA experience, the area most often responsible for code defects is the requirements phase. “Defects usually point to requirements that are ambiguous or missing, or that are misinterpreted by the developer,” Voelschow explains. Such issues are often entered as defects or worse, come in as enhancements once they’ve made it to production. “They can be fixed earlier in the process versus being a defect found in production.”

If you’ve found this article helpful, keep an eye out for an upcoming feature in Software Test & Performance magazine that will lay out techniques for finding defects earlier in the development process, using defect data you already have. Voelschow also will detail steps you can take to close the gap between requirements and development, identify the warning signs of other gaps in your processes, and include examples of defects that demonstrate this.


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