Hiccupps

There was once a young man, a handsome, moral, and brave young man, dexterous beyond compare, sharp of eye, voracious in the consumption of information and with sagacity and recall to rival that of the wisest of elephants. Oh yes, and he was also a software tester. This preternaturally blessed young man, over the course of time, had occasion to visit many conveniences, both public and private. As was his way, he declined to waste those periods of forced repose and so took the opportunity to exercise and practice the skills that served him so well elsewhere in his life while sequestered in those littlest of rooms. To this end, over repeated visits to a particular water closet he began to observe that, while the cleanliness in general could not be faulted, there was one area which was reliably hygienic to a significantly lower standard than the rest. This region, populated by dust, tiny fragments of tissue, hair, and other detritus, he noted, was along the base of the wall directl

Cohen and Medley, in Stop Working & Start Thinking , say: Simple tests are not experiments ... A chef will bake a cake at different temperatures and find the one that gives the best results ... [but] we should only include [this test] in classical "science" if the "normal" situation is included as a control ... Every careful observation of a puzzling or new phenomenon should be matched to similar observations of well-understood or classical material. They go on to introduce some useful terminology: variables are the things that you will aim to alter in the experiment; all other factors that could vary, but which you will aim not to vary, are parameters . And they then describe three types of experiment concerned with investigating the possibility of a causal relationship between a variable, A, and an outcome, X. Deficit : run one experiment with A and one without A. Monitor the presence of X in both cases. If X is seen with A but not without A then pe

In Stop Working & Start Thinking (which I also mentioned the other day )  Jack Cohen and Graham Medley want scientists to consider what science is and how they do it, as well as just getting on with it. To help explain this, they partition scientific answer-seeking like so: observation measurement investigation experiment And that's interesting in and of itself.  But the authors have been round the block and so recognise that this categorisation is not absolute, and that sometimes it might not be clear where a particular activity sits, and that some activities probably sit in multiple categories at different times and even at the same time. In science — and thinking, so this applies to you too, testers — generalisations are useful because they help us to frame hypotheses at relevant granularities. We’re all made up of atoms but a description of social deprivation in inner cities at an atomic level would unhelpfully obscure, for example, that higher-level concepts

Perhaps it's true that there's nothing new under the sun , but that doesn't mean that what's already known is necessarily uninteresting. Here's a quick example: I was recently reflecting on how talking to multiple people about their perspectives, finding data from several independent sources, or asking the same question in different ways felt analogous to a technique from surveying, triangulation . Triangulation is an ancient but still widespread method of mapping a landscape in which a network of points are plotted in relationship to one another, with each point always connected to two others, making triangles. Building one triangle against the next, and the next, and the next allows the whole space under consideration to be covered. I'm nowhere near the first here, though, as a quick search established : In the social sciences , triangle is often used to indicate that two (or more) methods are used in a study in order to check the results of one an

The Test team book club at Linguamatics read On Testing Non-testable Programs  by Elaine Weyuker this week. As usual, the discussion was interesting and, as usual, the reading material was only the starting point and, as usual, we found ourselves exploring our own context and sharing our own experiences and ideas. I find this kind of interaction invigorating and energising. It remains fascinating to me that we each bring common and unique perspectives to these meetings and I thrive on hearing others on my team talk about how they see the topic, I covet the time I spend thinking about how I do, and then I enjoy immensely contrasting the two. I had wondered, while reading the paper, whether I could extract some kind of ontology of oracles from it. Informally, it seemed that Weyuker had structured her analysis in this way: programs are testable or not; these are characteristics of non-testable programs; non-testable programs are of three types; these approaches to oracles can