Talk About Quality

As good as the misconceptions surrounding Toyota make it sound, the truth is even better.

– Stewart Anderson in Quality Digest’s Quality Insider 20-Oct-2009

Thanks to Stewart Anderson, both for bringing us the real story about how Toyota, famed for focus on quality, actually goes about doing it. Put aside for a moment what you know about ISO, QMS, metrics etc and read the carefully crafted wisdom of experience. How quality really works at Toyota. And yes, you really can apply these ideas elsewhere, even in software development.

All quotes are from the linked article by Stewart Anderson.

Toyota’s basic pattern for improving a process is based on a simple three-part model:

1. Understanding the current condition.
2. Developing and defining a target condition.
3. Understanding and tackling problems which need to be overcome to move from the current condition to the target condition.

This model has learning at its heart [to identify] actions to solve problems in the current condition.

The primary responsibility [of the team leader] is to monitor the process, ensure that standard work is being followed, and coach and mentor the work team in improving the process. Team leaders receive special training in process improvement and problem solving ….

To read the full article click here.

Related reading: Gemba Kaizen: A Commonsense, Low-Cost Approach to Management (my review here).

Full disclosure: My Toyota is over 15 years old and still running fine. My last car was also a Toyota.

Consider a function in software code, and how to write it properly so that it meets its requirements and doesn’t fail. The standard way of looking at it is that a function has an API — a signature — of input and output variables and types. The code for the function has a pretty standard form. There are checks for invalid input, and a function body which implements a mini-flowchart of conditional checks, and maybe a state machine if needed. All this to take every given input vector to the correct output.

Unit tests, whether they’re written before coding (test-driven development), or after, apply test input vectors to the function and check if the expected output is produced. The same story applies to a module: a collection of functions or classes that implements a feature. There are still valid inputs to check if they give correct output, and invalid inputs that must be rejected. Best-practice test design methods, such as boundary-value checking and equivalence classes, help the developer choose the best test vectors from the sea of possibilities. The ones that will produce good tests that cause failures early, while the code is still in the hands of the developer.

So why do we still have so many “surprise” failures? Unit-tested code that nevertheless comes back from system testing with failures? And the Steps to Reproduce — so simple — like, “I left the system running overnight and when I came back in the morning it had crashed.”

The answer may be in the flow of data. Functions and modules in embedded software don’t just deal with single inputs one by one. Generally they are expected to process streams of data in real time. For example, a modern television set-top box, with a built-in disk, has to process multiplexed video data and metadata, the same from the hard disk, as well as a much slower stream of user input via the TV remote control. If the code slips up, or leaks memory, sooner or later, you get a wrong, stuck, or crash situation that QC proudly reports.

Where have we seen this before? How about those robot car competitions that university engineering departments often hold? Contests which have expanded outward to worldwide challenges to design, for example, an auto-piloted car. (See “The DARPA Urban Challenge“). These contests demand software that will keep a driverless car on track for long periods of time, avoiding stationary and moving obstacles (other cars).

Could it help, then, to see a lowly function in embedded software not as a flowchart of if-then-else statements, but as a little car — or perhaps delivery truck– that must be kept on track, avoiding obstacles in the data stream while delivering packages to the right place? How would that view affect code layout, code review, and unit test design? See you at the track!