History of a Large Test Automation Project Using Selenium

I’ve known Chris McMahon through the Internets for a number of years, but only met him in person at Agile 2009. His talk was immediately after mine and seemed to be one of only a few purely experiential sessions: this is what the situation was, this is what we did and this is what we learned in the process. I like this session a lot more than pure workshop ones, though I’m beginning to see their value too. So even though I know a bit of inside-baseball into the Socialtext automation rig, I still got over two pages of notes. Not to mention the paper that he mentioned exists somewhere that I’m sure he’ll add a link to in the comments. (Won’t ya, Chris…)

  • Manual test cases looked the same-ish as their automated counterparts
  • Tests were named after features
  • Manual tests were note there for regression purposes, but as placeholders for future automation
  • Poverty of Oracle problem – automation reports only one problem
  • Tip – Break out of the frame to increase testability
  • Once the manual test is automated, throw out the manual one
  • There is a need for both canned data and data created through the tests. Canned data is for when you have a large required data set for a test
  • Lewis Carol poems make great (string) seed data (especially for search)
  • If you are creating data, make sure to make it unique through something like Julian timestamps
  • Weave a ‘web’ of tests through your application
  • 90/9/1 Rule – 90% of people read content, 9% comment on it, 1% create new content
  • Smell – All automated tests share the same initial path through the system (a branching strategy)
  • Smell – At a certain number of steps (~200 in Socialtext’s case) the script is too large to (easily) diagnose script failure causes and needs to be refactored
  • Ran scripts end-to-end, continuously
  • If a script fails, run it again immediately and only on second failure mark it as failed. (But don’t lose the fact that you ran it the second time)
  • Scripts can have manual prompts in them for human inspection points. Speeds up screen traversal and environment handling
  • Four points for efficient, long-term automation
    1. Ability to abstract into fixtures / dsl
    2. Strive for feature coverage
    3. Build a web of tests
    4. Have fast, routine reporting of failures
  • The only reason to automate is to give expert testers time to manually test

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