Have no fear! SmartBear live-streamed the conference. It starts at the 52 minute mark.
Stop Compromising Quality: Setting Automation Up for Success https://youtu.be/WAu1gWmKp5w
Thank you so much Brianne Cordima and Bria Grangard of SmartBear for setting up this event as the Ministry of Testing - Boston's event organizers!
Slides:Which Tests Should We Automate? - Angie Jones
Setup
Let's say you were presented at Twitter with ten features that may need automated tests written. How do you decide what to automate?
Play along at home! Which Twitter feature would you automate? @techgirl1908 @SmartBear pic.twitter.com/pyHm9pxOHt— T.J. Maher (@tjmaher1) June 26, 2018
- Add a Tweet
- View Tweets
- Pin a Tweet
- Follow a User
- Set a Handle / Username
- Set Location
- Update Handle
- Block a User
- View Analytics of a Tweet
- Balloons Appear When It's Someone's Birthday
At the Meetup, Angie had us all pick a partner to analyze these features together.
Step One: What is Your Gut Reaction?
Check off which features, in column "G", before you start analyzing the features, which ones may need automated tests written.
Step Two: Measure the Risk
There are two metrics to consider. On a scale of 1 to 5, what value should each metric be?
- Impact: If broken, what's the impact to customers?
- Probability: Frequency of use by customers.
Multiply the two values you came up with. Write the value in column "R".
On a scale of one to five for Impact and the same for Probability: What is the risk score? pic.twitter.com/m42lra2IT1— T.J. Maher (@tjmaher1) June 26, 2018
Step Three: Measure the Value
On a scale of 1 to 5, what values would each feature have?- Induction to Action: How quickly would this failure be fixed?
- Distinctness: Does this test provide new info?
Multiply the two values you came up with. Write the value in column "V".
What would be the Value: Induction to Action * Distinction? @techgirl1908 @SmartBear pic.twitter.com/lNcujtTZGx— T.J. Maher (@tjmaher1) June 26, 2018
Step Four: Cost Efficiency
On a scale of 1 to 5, what values would each feature have?
- Simplicity: How easy will it be to script this?
- Time: How quickly can this be scripted?
Multiply the two values you came up with. Write the value in column "C".
— T.J. Maher (@tjmaher1) June 26, 2018
Step Five: History
Let's say the following areas have these many bugs:
- Setting location: 51
- Updating handle: 27
- Pinning Tweet: 2
- Viewing Tweets: 10
... Wow! Geolocation has so many bugs associated with it!
On a scale of 1 to 5, what values would each feature have?
- Frequency of Breaks: Volume of historical failures for this test. Geolocation services would definately get a "5" for that. Balloons? It would get a "0" since there are not any bugs associated with it.
- Similarity to Weak Areas: Volume of Historical Failures in related areas.
Multiply the two values you came up with. Write the value in column "H".
What about History: Similar to weak areas * Frequency of Breaks? Here is the list of hypothetical bugs. @techgirl1908 @SmartBear pic.twitter.com/IfcJThbG9J— T.J. Maher (@tjmaher1) June 26, 2018
Step Six: Tally Up The Scores
Add the scores up. What do they look like? What top scores do we need to automate? @techgirl1908 @SmartBear pic.twitter.com/cs3nwiUbtw— T.J. Maher (@tjmaher1) June 26, 2018
Samples from @techgirl1908. What was surprising was that location as a cost effective test, as much as adding a tweet. pic.twitter.com/gv7QYcwngc— T.J. Maher (@tjmaher1) June 26, 2018
Thank you so much, Angie Jones, for running this workshop.
Happy Testing!
-T.J. Maher
Sr. QA Engineer, Software Engineer in Test
Meetup Organizer, Ministry of Testing - Boston
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