Amazon calculates a product’s star ratings based on a machine learned model instead of a raw data average. The model takes into account factors including the age of a rating, whether the ratings are from verified purchasers, and factors that establish reviewer trustworthiness.
I just completed reading of this book and the description didn't match with my expectations. Just to give some context. I am a QA director with over 25 years experience in the field of software engineering. I have the task to improve an existing team's knowledge around testing outside of the boundaries of the sunny day scenario and going bigger than just functional validation. None have seen or experienced what you can do with test automation, or approaching testing from a system or end to end point of view. They are very talented, they just haven't had a lot of exposure of what is possible outside of the "way its always been done" because of time.
When I read the description, I had my hopes on "Evil" expressing a level deeper of ideas or building blocks that one would approach when testing software outside of the bounds of just validating functional requirements. For example, with a distributed system, I would have liked to seen some real world examples of how folks should think about testing from an architectural perspective(vs. user) with various approaches or styles and why we should do it. I am a firm believer in system testing as it pertains to shaking out race conditions, triggering exceptions and finding memory leaks. I preach this to my team and push for this type of mentality and posture when testing a new project.
I read this book from cover to cover in 2 hours(It normally takes me longer than the average reader to get through a book, given that I am a visual thinker and sometimes have to reread). I was previewing this book in preparation to hand out to my whole team as a good thought exercise and allow the opportunity for folks to think differently and brainstorm fresh approaches. I think this book has some good tips on how to handle the culture around you and what your posture should be in certain situations(including looking at yourself), If you are looking for some high level test approaches and explanation of when and why they should apply and how to think about tackling them, this book won't get you there.
If you are currently a test engineer and you like to hear someone answer common office gripes in a comical way, you may get a few laughs. .
A must-read for software testers at all experience levels, in all contexts. This book has Evil metrics! It has great cartoons! It's hilarious, while making excellent points. Sample: (answer to question about certifications): "...I will not say “do not take it”. It is your money, consequently, your choice. "
And it's pragmatic. For example, on getting involved in projects early, don't start writing up testing strategies and plans, but reflect on what value you can add, think about project risks, avoid wasting your time if you can't add enough value.
Dear Evil Tester is thought-provoking, like the answer to "Why do we have labels?" "Use normal dictionary words", what an interesting idea! The author even channels Dr. Seuss.
My favorite parts are when Evil Tester shares his own experiences. It's good to know other people have fallen into and struggled out of the same pitfalls as I have. If you're still early in your testing career, these stories could help you *avoid* the pitfalls!
I'm sad he doesn't recommend any of the books I co-authored, nevertheless, I recommend Dear Evil Tester to you.