Why isn’t Software Testing Performed as Efficiently and Effecively as it could be?

Luis Fernández, an Associate professor at Universidad de Alcala is conducting a survey of software testers to gather data relating to, e.g., “Why isn’t software testing conducted as efficiently and effectively as it should be?” and “What factors lead to software testing being ‘under-appreciated’ as a potential career path?”

His survey (as of March, 2010) is listed here: http://www.cc.uah.es/encuestas/index.php?sid=28392&lang=en

Personally, I agree that the following two issues (identified in his survey) are significant causes of inefficiency in software testing:

1) “People tend to execute testing in an uncontrolled manner until the total expenditure of resources in the belief that if we test a lot, in the end, we will cover or control all the system.”

(Or, at least, given the relatively undisciplined test case selection methods prevalent in the industry, my experience in analyzing manually selected test scenarios is that testers generally believe (a) they are covering a higher proportion of an application’s possible combinations than they actually are and (b) they underestimate the amount of time that is spent during test execution unproductively repeating steps that they have previously tested)

2) “Many managers did not receive appropriate training on software testing so they do not appreciate its interest or potential for efficiency and quality.”

It is unfortunate, but true, that many testing managers do not have any background whatsoever in combinatorial testing methods that (a) dramatically reduce the amount of time it takes to select and document test cases, and (b) will simultaneously improve test execution efficiency when applied correctly. See, for example, https://www.hexawise.com/Combinatorial-Softwar-Testing-Case-Studies-IEEE-Computer-Kuhn-Kacker-Lei-Hunter.pdf

See also: http://www.slideshare.net/JustinHunter/efficient-and-effective-test-design

Please consider taking Fernández’s short survey. It takes only 5-10 minutes to complete.

What Software Testers Can Learn from the Game of 20 Questions

Dave Whalen posted a good piece here asserting that software testing, done well, requires a blend of “Science” and “Art”. I recommend it. (He also has a good post about testing databases here).

He includes the statement below which I agree with. If you are a software tester and any doubts about whether all of these methods work (pairwise software testing in particular), I would encourage you to conduct a pilot project on your own and measure the results achieved with and without the technique applied.

From the scientific side, testing can include a number of proven techniques such as equivalency class testing, boundary value analysis, pair-wise testing, etc. These techniques, if used properly, can reduce test times and focus on finding the bugs where they tend to hang out – much like a porch light on a summer night.

My response to Dave’s post, included below, is not especially profound or even well-written, but, hey, I’m in a hurry in the pre-Thanksgiving rush and the topic hit close to home so I couldn’t resist jotting a little something. Enjoy. Please let me know your thoughts / reactions if you have any.

Dave,

Very well said!

I wholeheartedly, enthusiastically agree with your premise. I also wish that more people saw things the same way.

My father co-wrote Statistics for Experimenters which describes the “art and science” within the Design of Experiments (“DoE”) field of applied statistics. Well-run manufacturing companies use DoE techniques in their manufacturing processes. Many companies, such as Toyota see them as an absolutely fundamental part of their processes (yet unfortunately, software testers, who could use DoE techniques such as pairwise and other forms of combinatorial testing, are often ignorant about how to use them properly and the software testing industry as a whole dramatically under-utilizes such techniques…. but I digress).

I brought the book up because it opens up with a good example relevant to the points you made. To win at the game of 20 questions, it is useful to know “the science” of game theory and DoE; choose questions so that there is a 50/50 chance that the answer will be Yes. Someone who knows this technique, all else being equal, will be win more because of their “scientific” approach than someone who doesn’t know the technique. And yet… other stuff (whether the subject matter expertise in this example, or subject matter expertise and “artistic” Exploratory Testing in your example) is indispensable as well.

You can’t truly excel at either 20 Questions or software testing unless you have a good mix of “science” (governed by mathematical principles, proven methods of DoE, etc.) and and “art” (governed by experience, instincts, and subject matter expertise).

– Justin

“I feel honored…”

There are some phrases in English that, as often as not, come off sounding obligatory and/or insincere. The phrase “I’m honored…” comes to mind (particularly if someone is accepting an award in front of a room full of people).

Be that as it may, I genuinely felt really honored last night and again today by a couple comments James Bach has said about me, including these:

Here’s the quick background: (1) James knows much more about software testing than I do and I respect his views a lot. (2) He has a reputation for not suffering fools gladly and pretty bluntly telling people he doesn’t respect them if he doesn’t respect the content of their views. (3) in addition to his extremely broad expertise on “testing in general” James, like Michael Bolton, knows a lot about pairwise and combinatorial testing methods and how to use them. (4) I firmly (and passionately) believe that pairwise and combinatorial testing methods are (a) dramatically under-appreciated, and (b) dramatically under-utilized. (5) James has published a very good and well-reasoned article about some of the limitations of pairwise testing methods that I wanted to talk to him about. (6) I co-wrote an article that IEEE Computer recently published about Combinatorial Testing that I wanted to discuss with him. (7) James and I have been at the STP Conference in Boston over the past few days. (8) I reached out to him and asked to meet at the conference to talk about pairwise and combinatorial testing methods and share with him my findings that – in the dozens of projects I’ve been involved with that have compared testers efficiency and effectiveness – I’ve routinely seen defects found per tester hour more than double. (9) I was interested in getting his insights into where are these methods most applicable? Least applicable? What have his experiences been in teaching combinatorial testing methods to students, etc.

In short, frankly, my goals in meeting with him were to: (a) meet someone new, interesting and knowledgeable and learn as much as could and try to understand from his experiences, his impressive critical thinking and his questioning nature, and (b) avoid tripping up with sloppy reasoning (when unapologetically expressing the reasons I feel combinatorial testing methods are dramatically under-appreciated by the software testing community) in front of someone who (i) can smell BS a mile away, and (ii) doesn’t suffer fools gladly.

I learned a lot, heard some fantastic war stories and heard his excellent counter-examples that disproved a couple of the generalizations I was making (but didn’t dampen my unshaken assertions that combinatorial testing methods are wildly under-utilized by the software testing community). I thoroughly enjoyed the experience. Moving forward, as a result of our meeting, I will go through an exercise which will make me more effective (namely carefully thinking through and enumerating all of the assumptions behind my statements like: “I’ve measured the effectiveness of testers dozens of times – trying to control external variables as much as reasonably possible – and I’m consistently seeing more than twice as many defects per tester hour when testers adopt pairwise/combinatorial testing methods.”

His complement last night was private so I won’t share it but it ranks up there in my all time favorite complements I’ve ever received. I’m honored. Thanks James.

What Else Can Software Development and Testing Learn from Manufacturing? Don’t Forget Design of Experiments (DoE).

Tony Baer from Ovum recently wrote a blog post titled: Software Development is like Manufacturing which included the following quotes:

“More recently, debate has emerged over yet another refinement of agile – Lean Development, which borrows many of the total quality improvement and continuous waste reduction principles of lean manufacturing. Lean is dedicated to elimination of waste, but not at all costs (like Six Sigma). Instead, it is about continuous improvement in quality, which will lead to waste reduction….

In essence, developing software is like making a durable good like a car, appliance, military transport, machine tool, or consumer electronics product…. you are building complex products that are expected to have a long service life, and which may require updates or repairs.”

Here are my views: I see valid points on both sides of the debate.  Rather than weigh general high-level pro’s and cons, though, I would like to zero in on what I see as an important topic that is all-too-often missing from the debate.  Specifically,  Design of Experiments has been central to Six Sigma, Lean Manufacturing, the Toyota Production System, and Deming’s quality improvement approaches, and is equally applicable to software development and testing, yet adoption of Design of Experiments methods in software design and testing remains low.  This is unfortunate because significant benefits consistently result in both software development and software testing when Design of Experiments methods are properly implemented.

What are Design of Experiments Methods and Why are they Relevant?

In short, Design of Experiments methods are a proven approach to creating and managing experiments that alter variables intelligently between each test run in a structured way that allows the experimenter to learn as much as possible in as few experiments as possible.  From wikipedia: “Design of experiments, or experimental design, (DoE) is the design of all information-gathering exercises where variation is present, whether under the full control of the experimenter or not. Often the experimenter is interested in the effect of some process or intervention (the “treatment”) on some objects (the “experimental units”).”

Design of Experiments methods are an important aspect of Lean Manufacturing, Six Sigma, the Toyota Production System, and other manufacturing-related quality improvement approaches/philosophies.  Not only have Design of Experiments methods been very important to all of the above in manufacturing settings, they are also directly relevant to software development. By way of example, W. Edwards Deming, who was extremely influential in quality initiatives in manufacturing in Japan and the U.S. was an applied statistician. He and thousands of other highly respected quality executives in manufacturing, including Box, Juran and Taguchi (and even my dad), have regularly used Design of Experiments methods as a fundamental anchor of quality improvement and QA initiatives and yet relatively few people who write about software development seem to be aware of the existence of Design of Experiments methods.

What Benefits are Delivered in Software Development by Design of Experiments-based Tools?

Application Optimization applications, like Google’s Website Optimizer are a good example of Design of Experiments methods can deliver powerful benefits in the software development process.  It allows users to easily vary multiple aspects of web pages (images, descriptions, colors, fonts, colors, logos, etc.) and capture the results of user actions to identify which combinations work the best. A recent YouTube multi-variate experiment (e.g., and experiment created using Design of Experiment methods) shows how they used the simple tool and increased sign-up rates by 15.7%.  The experiment involved 1,024 variations.

What Benefits are Delivered in Software Testing by Design of Experiments-based Tools?

In addition, software test design tools, like the Hexawise test design tool my company created, enable dramatically more efficient software testing by automatically varying different elements of use cases that are tested in order to achieve an optimal coverage. Users input the things in the application they want to test, push a button and, as in the Google Web Optimizer example, the tool uses DoE algorithms to identify how the tests should be run to maximize efficiency and thoroughness.  A recent IEEE Computer article I contributed to, titled “Combinatorial Testing” shows, on average, over the course of 10 separate real-world projects, tester productivity (measured in defects found per tester hour) more than doubled, as compared to the control groups which continued to use their standard manual methods of test case selection: http://tinyurl.com/nhzgaf

Unfortunately, Design of Experiments methods – one of the most powerful methods in Lean Manufacturing, Six Sigma, and the Toyota Production System – are not yet widely adopted in the software development industry. This is unfortunate for two reasons, namely:

1. Design of Experiments methods will consistently deliver measurable benefits when implemented correctly, and
2. Sophisticated new tools designed with very straightforward user interfaces make it easier than ever for software developers and testers to begin using these helpful methods.

– Justin