Early this year, I recently completed, what I felt was the best software book I've read in a really long time: How Google Tests Software by Whittaker, James A., Arbon, Jason, Carollo, Jeff ( 2012 ) (HGTS).
Although a couple of years old now, and even though the main driver James Whittaker, has left Google and gone back to Microsoft, this book is really a jewel that belongs in the annals of great Software Testing books, really.
The book is not filled with theory and academic nonsense - it speaks directly at practitioners of all types and levels involved in Software Engineering. Straight-forward, realistic breakdown of how things go down in software product teams, the challenges with fitting in Test/QA streams (actually there's no such thing as fitting in QA/Test, it should always be there, but the reality is that developers don't always get it), balancing the needs of business in terms of delivering on time against meeting the needs of the customer (will real customers use the product, is it valuable), etc, etc.
Please get your hands on this book, it will open your eyes to real-world, massively scaling software systems & teams. Honestly, it felt quite refreshing to learn Google's mindset is similar to mine, as I'd been promoting similar testing styles for much of my management career, being a firm advocate that developers should do as much testing upfront as possible, with Test/QA supplementing development by providing test tools & frameworks, as well as employing a QA Program Manager (known as Test Engineer in Google) to oversee and co-ordinate the overall test strategy for a product. I have written about QA/Testing topics in the past, the ideas there don't stray too far from the core message contained in HGTS.
The book shares a wealth of insider information on the challenges that Google faced with its product development & management as the company scaled in growth in both its use of its products as well as the number of people employed, working across continents, explosive growth and large development centres across the world. It is filled with interviews with influential Googlers that give some insight into the challenges and solutions adopted. You will also find information on the internal organisational structures that Google implements in its product development teams, along with some useful references on Open Source Tools that have been borne out of Google's own internal Testing Renaissance, now shared with the rest of the world for free, thanks Google for sharing!
One such tool is Google Test Analytics ACC (Attribute, Component, Capability) analysis model - which is the topic I want to focus on. In the Set-Top-Box projects that I run, I look to the QA Manager/Tech Leads to know the product inside-out, to develop an overall Test Strategy that outlines the ways and methods of testing that will achieve our Go-To-Market in a realistic & efficient manner (and not adopt process-for-process-sake). I generally look toward usability and risk-based test coverage, seeking out a heat map that shows me in broad strokes, the high level breakdown of the products feature set (i.e. what is it about the product that makes it so compelling to sell), what the product is made of (i.e. the building blocks of the product), and what the product does (i.e. the capabilities or core feature properties). We do this generally in Microsoft Excel spreadsheet, manually importing test data from clunky test repositories. What I look out for, as a classic Program Manager, the RAG (Red, Amber, Green) status that tells me the fifty thousand foot view, what the overall quality of this product is, and how far away we're from having a healthy launch-candidate system.
It turns out the Google do pretty much the same thing, but are way more analytical about it - they call it ACC, according to the book written in 2011/12 "ACC has passed its early adopter's phase and is being exported to other companies and enjoying the attentoin to tool developers who automate it under the "Google Test Analytics" label".
So I've created my own generic Set-Top-Box project based on Google's ACC model, aiming to share this with like minded people working on STB projects. It is not complete, but offers the basic building blocks to fully apply ACC in a real project. I think this will be a useful learning for anyone involved in QA/Testing role.
My generic-STB-Project is currently hosted on the Google Test Analytics site, along with a complete ACC profile. It took me about four hours to do the full detail (spread over a few days of 10 minute tea breaks, between meetings), and about one hour to get the first draft of the High Level Test Plan with at least one ACC triple filled in. The book challenges you to get to a High Level Test plan in just 10 minutes, which I actually I think that is quite doable for STB projects as well!!
In about four hours, which is about half-one working day, I was able to create a Test Matrix of 254 core high level test scenarios (note I'm really not a QA/Test expert so imagine what a full time QA/Test Engineer could knock up in one day?) that looks like this:
Google currently use this model in their high level test plans for various products, like ChromiumOS, Chrome Browser & Google+. It was developed by pulling the best processes from the various Google test teams and product owners, implementation pioneered by the author's Whittaker, Arbon & Carollo. Taken from the book. Test planning really stops at the point you know what tests you need to write (it is about the high level cases, not the detailed test scripting). Knowing what to test kicks off the detailed test case writing, and this is wherer ACC comes in (quoting snippet from Chapter 3, The Test Engineer):
Although a couple of years old now, and even though the main driver James Whittaker, has left Google and gone back to Microsoft, this book is really a jewel that belongs in the annals of great Software Testing books, really.
The book is not filled with theory and academic nonsense - it speaks directly at practitioners of all types and levels involved in Software Engineering. Straight-forward, realistic breakdown of how things go down in software product teams, the challenges with fitting in Test/QA streams (actually there's no such thing as fitting in QA/Test, it should always be there, but the reality is that developers don't always get it), balancing the needs of business in terms of delivering on time against meeting the needs of the customer (will real customers use the product, is it valuable), etc, etc.
Please get your hands on this book, it will open your eyes to real-world, massively scaling software systems & teams. Honestly, it felt quite refreshing to learn Google's mindset is similar to mine, as I'd been promoting similar testing styles for much of my management career, being a firm advocate that developers should do as much testing upfront as possible, with Test/QA supplementing development by providing test tools & frameworks, as well as employing a QA Program Manager (known as Test Engineer in Google) to oversee and co-ordinate the overall test strategy for a product. I have written about QA/Testing topics in the past, the ideas there don't stray too far from the core message contained in HGTS.
The book shares a wealth of insider information on the challenges that Google faced with its product development & management as the company scaled in growth in both its use of its products as well as the number of people employed, working across continents, explosive growth and large development centres across the world. It is filled with interviews with influential Googlers that give some insight into the challenges and solutions adopted. You will also find information on the internal organisational structures that Google implements in its product development teams, along with some useful references on Open Source Tools that have been borne out of Google's own internal Testing Renaissance, now shared with the rest of the world for free, thanks Google for sharing!
One such tool is Google Test Analytics ACC (Attribute, Component, Capability) analysis model - which is the topic I want to focus on. In the Set-Top-Box projects that I run, I look to the QA Manager/Tech Leads to know the product inside-out, to develop an overall Test Strategy that outlines the ways and methods of testing that will achieve our Go-To-Market in a realistic & efficient manner (and not adopt process-for-process-sake). I generally look toward usability and risk-based test coverage, seeking out a heat map that shows me in broad strokes, the high level breakdown of the products feature set (i.e. what is it about the product that makes it so compelling to sell), what the product is made of (i.e. the building blocks of the product), and what the product does (i.e. the capabilities or core feature properties). We do this generally in Microsoft Excel spreadsheet, manually importing test data from clunky test repositories. What I look out for, as a classic Program Manager, the RAG (Red, Amber, Green) status that tells me the fifty thousand foot view, what the overall quality of this product is, and how far away we're from having a healthy launch-candidate system.
It turns out the Google do pretty much the same thing, but are way more analytical about it - they call it ACC, according to the book written in 2011/12 "ACC has passed its early adopter's phase and is being exported to other companies and enjoying the attentoin to tool developers who automate it under the "Google Test Analytics" label".
So I've created my own generic Set-Top-Box project based on Google's ACC model, aiming to share this with like minded people working on STB projects. It is not complete, but offers the basic building blocks to fully apply ACC in a real project. I think this will be a useful learning for anyone involved in QA/Testing role.
My generic-STB-Project is currently hosted on the Google Test Analytics site, along with a complete ACC profile. It took me about four hours to do the full detail (spread over a few days of 10 minute tea breaks, between meetings), and about one hour to get the first draft of the High Level Test Plan with at least one ACC triple filled in. The book challenges you to get to a High Level Test plan in just 10 minutes, which I actually I think that is quite doable for STB projects as well!!
In about four hours, which is about half-one working day, I was able to create a Test Matrix of 254 core high level test scenarios (note I'm really not a QA/Test expert so imagine what a full time QA/Test Engineer could knock up in one day?) that looks like this:
Capabilities & Risk Overview of a Generic Set Top Box |
Google currently use this model in their high level test plans for various products, like ChromiumOS, Chrome Browser & Google+. It was developed by pulling the best processes from the various Google test teams and product owners, implementation pioneered by the author's Whittaker, Arbon & Carollo. Taken from the book. Test planning really stops at the point you know what tests you need to write (it is about the high level cases, not the detailed test scripting). Knowing what to test kicks off the detailed test case writing, and this is wherer ACC comes in (quoting snippet from Chapter 3, The Test Engineer):
ACC accomplishes this by guiding the planner through three views of a product, corresponding to 1) adjectives and adverbs that describe the product's purpose and goals, 2) nouns that identifiy the various parts and features of the product, and 3) verbs that indicate what the product actually does.
- A is for "Attribute"
- Attributes are the adjectives of the system. They are the qualities and characteristics that promote the product and distinguish it from the competition. Attributes are the reasons people would choose to use the product over a competitor.
- C is for "Component"
- Components are the building blocks that together constitute the system in question. They are the core components and chunks of code that make the software what it is.
- C is for "Capability"
- Capabilities are the actions the system performs at the command of the user. They are the responses to input, answers to queries, and activities accomplished on behalf of the user.