Test Coverage Outlines

This is a presentation I gave at a local test meet up group called VanQ

PDF version of slides: Test Coverage Outlines


Test Coverage Outlines are just elaborate spreadsheets. They were originally inspired by Jonathan Kohl, as part of exploratory testing training at Sophos. A colleague, (Jose Artiga), and I built on the initial inspiration and came up with the first version of the test coverage outline. This was then adopted by the teams at Sophos, and of course refined through use and practice.

(slide 8) Simple spreadsheets to help;

  • Structure & simplify your test planning
  • Inspire & structure your test design
  • Be test professionals and not just test execution machines
  • Collaborate on testing
  • Show clear and concise status at any point in your testing
  • Discuss risk in terms of planned vs actual coverage

(slide 9) An example coverage outline

  • Each white background row is a test idea – a simple sentence or few words to convey an idea you want to cover by testing
  • Try to keep these simple like a heuristic that acts as a guide rather than a step by step procedure

(slide 10) Divide your test ideas up into sections

  • Example shows this as the black lines with white text
  • You can do this by functional area, test focus, heuristic etc (whatever makes sense for you in your context)

(slide 11) Divide your test ideas up into sheets

  • Again divide into functional area per sheet or perhaps copy your sheet to provide same/similar coverage against different builds or versions of your software

(slide 12) Configurations – show your coverage against different configurations

  • Example given is a common one – browsers and OS, but could equally be versions of HW, SW, Mobile device etc

(slide 13) Test types/levels – show your coverage at different test levels or different testing types

  • Matrix your test ideas against different test levels, for example unit tests, integration tests, automated UI tests, manual tests, exploratory tests
  • Even if you are not familiar with the unit tests you can suggest the developers gain some coverage of the test ideas with unit tests and fill out the column with you

(slide 14) Prioritise your test ideas

  • I use simple (high, medium, low) priority levels to organise, sort and filter test ideas by priority
  • Make sure you are executing/covering in priority order

(slide 15) Prioritise your configurations

  • I use a simple left to right prioritisation for configurations, i.e. the highest priority configuration to cover is the left most column

(slides 16 & 17) Use colour and conditional formatting

  • I use simple colours and conditional formatting to make updates easy and to show status and priority clearly
  • Make sure you also use a colour (I use x and grey) to indicate coverage that you are consciously not planning to cover

(slide 18) I use mind maps as a visual test design/planning aid

(slide 19) Start by outlining your test idea areas, use the outline to inspire your test ideas

  • I sometimes use heuristics to structure and inspire my testing, for example using a quality criteria heuristic like usability or performance I can think about test ideas that come under each of those ares
  • Creating templates (see examples) for common types of testing focus can help inspire testers as well as providing some base or consistent tests

(slide 20) Using test ideas rather than detailed test cases

  • enables and encourages variation, exploration and more ‘brain engaged’ testing
  • thus avoiding the pesticide paradox [Boris Bezier]

(slide 21) Collaboration

  • Using google docs or similar enables you to easily collaborate in real time with other testers/colleagues
  • Some of the easiest ways in which you can organise and facilitate collaboration is to allocate a config column, test area or even tabs
  • You can see who is accessing/updating the sheet and can see status of tests others are covering in real time too

(slide 22) Use colour to provide very easy and quick to read status

  • You can just look at a tab and immediately see if you have any fails or blocked tests

(slide 23) Colour coding also makes it easy to see coverage in terms of planned vs actual

Example Coverage Outlines

Feel free to copy and adapt these for you own purposes, hopefully these will inspire you to refine the outlines and share your ideas back with me and others;

Learning from the mistakes our customers care about

5 question marks
5 whys

As mentioned in a previous post I keep a close watch on customer defects. These are the issues that a customer cared about enough (or was sufficiently annoyed by) to contact us and tell us about them.
I am focusing on the issues here, not the feature requests or the how do I’s, though both can be also regarded as defects in ‘failing to understand or predict the customers needs’ or ‘failing to deliver an intuitive product’ respectively.

Being a big fan of prevention is better than cure, I like to investigate the customer issues and perform a root cause analysis or 5 whys on the reasons each issue escaped our attention.
Yes, I refer to customer reported issues as escaped defects, since they escaped our detection. It doesn’t matter how many stages in your pipeline or how may automated tests at different levels, or even how good the teams are, there will be some issues that escape our attention.
Technically, I also regard issues discovered late in our pipeline, after story acceptance and as part of our release process, as escapes too, as well as any issues we happen to find in production (before a customer reports them).

There are lots of quotes around learning from failure, and being doomed to repeat your mistakes if you fail to do so. I believe, along with many others, that true learning only comes from failure and understanding the reasons for it. However, we should take care to not make the same mistake twice as this indicates a failure to learn. So the reason for analysing these escaped defects is not to apportion blame or point fingers, it is instead to learn how we can prevent a similar class of issue in future. The preference here being to prevent the class of issue from ever being coded again. If that proves to be more expensive than the cost of impact of the issues then at least being able to prevent the class of issue escaping our attention again.

I was introduced to Lean software development techniques via Mary and Tom Poppendick  which led me to learn more about The Toyota Way where I learnt the 5 whys technique. Prior to this I had been using other root causing techniques or simply using my QA ability to ask difficult but relevant questions to achieve the learning and expose the actions.
The 5 whys technique is just so simple that it makes it easy for anyone to participate as well as facilitate, meaning that anyone can do this – you don’t need to be a QA or have a background in problem solving or root cause analysis techniques.

So, what does it look like? Well here is an example with some edits to remove any proprietary details (note 5 is simply a guide, you can use more or less whys);

Problem statement: Service proxy was updated in C# provider code but not in consumer code

Why didn’t we catch this?

  • tests run in the consumer pipeline were not sufficient to expose the issue
  • tests were not full contract tests – nothing testing the contract between producer and consumer
  • no communication between the producer and consumer teams on any changes made to the interface

Why didn’t the consumer pipeline tests expose the issue?

  • because the test only exercised the simplest possible scenario which did not get affected by the change (sec call returned minimum possible data)

Why were the contract tests insufficient?

  • contract testing is not very well understood by all teams concerned
  • tests were not reviewed by anyone except developers

Why wasn’t there communication between teams?

  • the producer of the service does not know who is consuming that service
  • tests didn’t relay information of endpoint changes
  • consumer tests were still passing (green)

Why didn’t the tests relay information of endpoint changes?

  • there were no tests asserting or checking the stability of the interface
  • the consumer was coded to de-serialise the entire response when really it only needed to check for ‘success’

Why was the consumer coded to de-serialise the entire response rather than just parse the value of interest?

  • because it was deemed easier to use a standard pattern to de-serialise entire response rather than write code to specifically look for just the value of interest

Some example actions that were taken as a result of this;

  1. Provide training in contract testing patterns
  2. Producer to add tests to notify producer team of interface change (trigger for investigation or communication of change)
  3. Consumer to provide contract tests for producer to run in producer pipeline to alert of breaking changes for consumer
  4. Audit all cross team interfaces/dependencies to negotiate and add any missing contract tests