Quality control in a zero cost of replication business

When a new manufacturing material becomes available, its use is often integrated with existing techniques, e.g., using scientific management techniques for software production.

Customers want reliable products, and companies that sell unreliable products don’t make money (and may even lose lots of money).

Quality assurance of manufactured products is a huge subject, and lots of techniques have been developed.

Needless to say, quality assurance techniques applied to the production of hardware are often touted (and sometimes applied) as the solution for improving the quality of software products (whatever quality is currently being defined as).

There is a fundamental difference between the production of hardware and software:

  • Hardware is designed, a prototype made and this prototype refined until it is ready to go into production. Hardware production involves duplicating an existing product. The purpose of quality control for hardware production is ensuring that the created copies are close enough to identical to the original that they can be profitably sold. Industrial design has to take into account the practicalities of mass production, e.g., can this device be made at a low enough cost.
  • Software involves the same design, prototype, refinement steps, in some form or another. However, the final product can be perfectly replicated at almost zero cost, e.g., downloadable file(s), burn a DVD, etc.

Software production is a once-off process, and applying techniques designed to ensure the consistency of a repetitive process don’t sound like a good idea. Software production is not at all like mass production (the build process comes closest to this form of production).

Sometimes people claim that software development does involve repetition, in that a tiny percentage of the possible source code constructs are used most of the time. The same is also true of human communications, in that a few words are used most of the time. Does the frequent use of a small number of words make speaking/writing a repetitive process in the way that manufacturing identical widgets is repetitive?

The virtually zero cost of replication (and distribution, via the internet, for many companies) does more than remove a major phase of the traditional manufacturing process. Zero cost of replication has a huge impact on the economics of quality control (assuming high quality is considered to be equivalent to high reliability, as measured by number of faults experienced by customers). In many markets it is commercially viable to ship software products that are believed to contain many mistakes, because the cost of fixing them is so very low; unlike the cost of hardware, which is non-trivial and involves shipping costs (if only for a replacement).

Zero defects is not an economically viable mantra for many software companies. When companies employ people to build the same set of items, day in day out, there is economic sense in having them meet together (e.g., quality circles) to discuss saving the company money, by reducing production defects.

Many software products have a short lifespan, source code has a brief and lonely existence, and many development projects are never shipped to paying customers.

In software development companies it makes economic sense for quality circles to discuss the minimum number of known problems they need to fix, before shipping a product.

Moving to the 12th circle in fault prediction modeling

Most software fault prediction papers are based on a false assumption, i.e., a list of dates when a fault was first experienced, by a program, contains enough information to build a model that has a connection to reality. A count of faults that have been experienced twice is required to fit a basic model that has some mathematical connection to reality.

I had thought that people had moved on from writing papers that fitted yet more complicated equations to one of the regularly used data sets. No, it seems they have just switched to publishing someplace they have not been seen before.

Table 1 lists the every increasing number of circles within circles; the new model is proposed as the 12th refinement (the table is a summary, lots of forks have been proposed over the years). I have this sinking feeling there is another paper in the works, one that ‘benchmarks’ the new equation using a collection of the other regular characters data sets that appear in papers of this kind.

Fitting an equation to data of first experience of a fault is little better than fitting noise.

As Planck famously said, science advances one funeral at a time.