Measuring Software Testing When The Labels Don’t Fit

This episode is about the struggle to explain, measure, and name the work testers and quality advocates actually do — especially when traditional labels and metrics fall short.

Links to stuff we mentioned during the pod:

• 05:05 - Defect Detection Rate (DDR)
  • The rate at which bugs are detected per test case (automated or manual)
  • No. of defects found by test team / No. of Test Cases executed) *100
• 15:06 - David Evans' LinkedIn
• 24:57 - Janet Gregory
  • Janet's website
  • Janet's LinkedIn
• 26:01 - Defect Prevention Rate
  • Perplexity search results here
• 28:28 - Jerry Weinberg
  • Jerry's Wikipedia page (his books are highly recommended)
• 49:33 - Shift-Left: The concept of moving testing activities earlier in the software development lifecycyle.

Some resources explaining the Shift-Left concept (Perplexity link)

00:00 - Intro
01:11 - Welcome & "woke" testing 😳
03:15 - QA, QE, Testing… whatever we call it, how do we measure if we're doing a good job?
03:44 - Vernon’s first experience with testing metrics: more = better?
05:00 - Defect Detection Rate enters the chat
06:41 - Rich reverse engineers quality skills needed in the AI era
10:54 - How do we know if we’re doing any of this well?
12:40 - Trigger warning: the topic of coverage is incoming 😅
16:54 - Bugs in production
21:09 - Automation metrics: flakiness, pass rates, and execution time
24:29 - Can you measure something that didn’t happen? (Prevention metrics)
27:43 - Do DORA metrics actually measure prevention?
32:03 - Here comes Jerry!
33:50 - The one metric the business cares about...
36:23 - QA vs QE: whose “quality” are we "assuring"?
39:25 - What's the story behind the numbers?
48:29 - Rich brings in Shift Left Testing
50:14 - Metrics that reach beyond engineering
53:14 - Rich gets a new perspective on QE and the business
56:50 - Who does this work? Testers? QEs? Or someone else?