State-Transition Testing

One of our goals at Expert Testers is to discuss practical topics that can help every tester do their job better. To this end, my last two articles have been about Decision Table Testing and Being an Effective Spec Reviewer. Admittedly, neither of these topics break new ground. That doesn’t mean, however, most testers have mastered these techniques. In fact, almost 50% of the respondents to our Decision Table poll said they’ve never used one.

Continuing the theme of discussing practical topics, let’s talk about State Transition Diagrams. State Transition Diagrams, or STDs as they’re affectionately called, are effective for documenting functionality and designing test cases. They should be in every testers bag of tricks, along with Decision Tables, Pair-Wise analysis, and acting annoyed at work to appear busy.

STDs show the state a system will move to, based on its current state and other inputs. These words, I understand, mean little until you’ve seen one in action, so let’s get to an example. Since I’m particularly busy (i.e., lazy) today, I’ll use a simple example I found on the web.

Below is a Hotel Reservation STD. Each rectangle, or node, represents the state of the reservation. Each arrow is a transition from one state to the next. The text above the line is the input–the event that caused the state to change. The text below the line is the output–the action the system performs in response to the event.


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One benefit of State Transition Diagrams is that they describe the behavior of the system in a complete, yet easy-to-read and compact, way. Imagine describing this functionality in sentence format; it would take pages of text to describe it fully. STDs are much simpler to read and understand. For this reason, they can show paths that were missed by PM or Developer, or paths the Tester forgot to test.

I learned this when I was testing Microsoft Forefront Protection for Exchange Server, a product that protects email customers from malware and spam. The product logic for determining when a message would be scanned was complicated; it depended on the server role, several Forefront settings, and whether the message was previously scanned.

The feature spec described this logic in sentence format, and was nearly impossible to follow. I took it upon myself to create a State Transition Diagram to model the logic. I printed it out and stuck it on my office (i.e., cubicle) wall. Not a week went by without a Dev, Tester, or PM stopping by to figure out why their mail wasn’t being scanned as they expected.

If you read my article on Decision Tables (DTs), and I’m sure you didn’t, you may be wondering when to use an STD and when to use a DT. If you’re working on a system where the order of events matter, then use an STD; Decision Tables only work if the order of events doesn’t matter.

Another benefit of STDs is that we can use them to design our test cases. To test a system completely, you’d need to cover all possible paths in the STD. This is often either impractical or impossible.

In our simple example, there are only four paths from start of the STD to the end, but in larger systems there can be too many to cover in a reasonable amount of time. For these systems, you can use multiple STDs for sub-systems rather than trying to create a single STD for the entire system. This will make the STDs easier to read, but will not lower the total number of paths. It’s also common to find loops in an STD, resulting in an infinite number of possible paths.

When covering all paths is impractical, one alternative is to ensure each state (node) is covered by at least one test. This, however, would result in weak coverage. For our hotel booking system, we could test all seven states while leaving some transitions and events completely untested.

Often, the best strategy is to create tests that cover all transitions (the arrows) at least once. This guarantees you will test every state, event, action, and transition. It gives you good coverage in a reasonable amount of tests.

If you’re interested in learning more about STDs (it’s impossible to cover them fully in a short blog article) I highly recommend reading A Practitioner’s Guide to Software Test Design. It’s where I first learned about them.

The next time you’re having trouble describing a feature or designing your tests, give a State Transition Diagram or Decision Table a try. The DTs and STDs never felt so good!


Exploratory Testing == Fun Productivity

You are probably familiar with the testing approaches of black box, white box, and gray box testing.  Each “tool” in the tester’s tool belt can be used in the right circumstances, or misused in the wrong circumstances.  Exploratory Testing (ET) can be used in almost all circumstances, and whether done formally or informally, it is a tool we shouldn’t be afraid to use.

Exploratory testing (ET) is something you probably already do. It is more than just “clicking around” the product.  ET is defined as a test-execution approach where the tester uses information gained while performing tests to intuitively derive additional tests. You can think of it as that little voice in the back of your head telling you “Did I just see something that looked wrong? I better check that out more deeply.” This is subtly different from black-box (BB) testing where you apply tools like Boundary Value Analysis (BVA) and Equivalence Class (EQ) to first develop a list of tests, and second run those tests. It also differs from gray-box (GB) testing where you first use internal knowledge of the structure of the feature and code to develop a list of tests, and second run those tests. You can think of ET as BB and GB testing with a feedback loop—you do test design and test execution at the same time. You are free to explore other avenues of the product in order to track down bugs and issues.

Exploratory testing provides value to the testing effort. It is generally good at evaluating the “look and feel” of a project, but several studies raise important questions about the overall effectiveness and efficiency of behavioral testing and popular exploratory testing approaches to software testing. The details of the studies can be found in chapter six of How We Test Software at Microsoft.

ET can be explained with an analogy (from James Bach’s “Exploratory Testing Explained“):

Have you ever solved a jigsaw puzzle? If so, you have practiced exploratory testing. Consider what happens in the process. You pick up a piece and scan the jumble of unconnected pieces for one that goes with it. Each glance at a new piece is a test case (“Does this piece connect to that piece? No? How about if I turn it around? Well, it almost fits but now the picture doesn’t match…”). You may choose to perform your jigsaw testing process more rigorously, perhaps by concentrating on border pieces first, or on certain shapes, or on some attribute of the picture on the cover of the box. Still, can you imagine what it would be like to design and document all your jigsaw “test cases” before you began to assemble the puzzle, or before you knew anything about the kind of picture formed by the puzzle?

When I solve a jigsaw puzzle, I change how I work as I learn about the puzzle and see the picture form. If I notice a big blotch of color, I might decide to collect all the pieces of that approximate color into one pile. If I notice some pieces with a particularly distinctive shape, I might collect those together. If I work on one kind of testing for a while, I might switch to another kind just to keep my mind fresh. If I find I’ve got a big enough block of pieces assembled, I might move it into the frame of the puzzle to find where it connects with everything else. Sometimes I feel like I’m too disorganized, and when that happens, I can step back, analyze the situation, and adopt a more specific plan of attack. Notice how the process flows, and how it remains continuously, each moment, under the control of the practitioner. Isn’t this very much like the way you would assemble a jigsaw, too? If so, then perhaps you would agree that it would be absurd for us to carefully document these thought processes in advance. Reducing this activity to one of following explicit instructions would only slow down our work.

This is a general lesson about puzzles: the puzzle changes the puzzling. The specifics of the puzzle, as they emerge through the process of solving that puzzle, affect our tactics for solving it. This truth is at the heart of any exploratory investigation, be it for testing, development, or even scientific research or detective work.

Key advantages of ET:

  • Exploratory testing is heavily influenced by the tester’s in-depth system and domain knowledge and experience. The more you know, the better you are at following the paths that are most likely to find bugs or issues.
  • Less preparation is needed.
  • Important bugs are quickly found.
  • ET tends to be more intellectually stimulating than execution of scripted tests.
  • Even if you come back and test the same area again, you are likely to perform your tests in a slightly different way (you aren’t following a script), so you are more likely find more bugs.
  • ET is particularly suitable if requirements and specifications are incomplete, or if there is a lack of time.
  • ET can also be used to  validate that previous testing has found the most important defects.
  • ET is better than just testing.

Key drawbacks of ET:

  • You must manage your time wisely. You need to know when to stop pursuing one avenue and move on to another.
  • You can’t review cases in advance (and by that prevent errors in code and test cases).
  • It can be hard to reproduce tests later unless you are documenting everything you do.  One idea is to use a screen recorder whenever you are doing ET.
  • It can be difficult to know exactly which tests have been run. This can be partially alleviated if you are recording your test steps and creating automation, or if you tracking code coverage.
  • You may end up testing paths that the user would never do. You can use customer data as an addition to your ET so that you don’t spend time testing areas that don’t need be tested.

Use ET when:

  • You need to provide feedback on a new product or feature.
  • You need to quickly learn a new product.
  • You have already been using scripts and seek to diversify the testing.
  • You want to find the single most important bug in the shortest time.
  • You want to check the work of another tester by doing a brief independent investigation.
  • You want to find and isolate a particular defect.
  • You want to determine the status of a particular risk, in order to evaluate the need of scripted tests in that area.
  • You are on a team practicing agile or Extreme Programming.

The last bullet deserves some context. Why would an agile team be interested in ET? Agile teams can suffer from groupthink. The team members spend all day working together, talking, coding, attending meetings, and so on. They tend to start thinking alike. While this helps the agile process, it can hinder testing. Why? Everyone starts to think about the product in the same way and use the product in the same way. Your scripted tests start following the same sequence as the developer’s code. ET can help break that groupthink, randomize the testing, and find issues that the customer would.

Are you a master or an amateur ET tester?

  • Test design: Exploratory tester is first and foremost a test designer. Anyone can design a test accidentally. The excellent exploratory tester is able to craft tests that systematically explore the product. This requires skill such as the ability to analyze a product, evaluate risk, use tools, and think critically, among others.
  • Careful observation: Excellent exploratory testers are more careful observers than novices, and for that matter, experienced scripted testers. The scripted tester will only observe what the script tells them to observe. The exploratory tester must watch for anything unusual or mysterious. Exploratory testers also must be careful to distinguish observation from inference, even under pressure, lest they allow preconceived assumptions to blind them to important tests or product behavior.
  • Critical thinking: Excellent exploratory testers are able to review and explain their logic, looking for errors in their own thinking. This is especially true when reporting the status of a session of exploratory tests investigating a defect.
  • Diverse ideas: Excellent exploratory testers produce more and better ideas than novices.  They may make use of heuristics to accomplish this. Heuristics are devices such as guidelines, generic checklists, mnemonics, or rules of thumb. The diversity of tester temperaments and backgrounds on a team can also be harnessed by savvy exploratory testers through the process of group brainstorming to produce better test ideas.
  • Rich resources: Excellent exploratory testers build a deep inventory of tools, information sources, test data, and friends to draw upon. While testing, they stay alert for opportunities to apply those resources to the testing at hand.

Exploratory testing can be valuable in specific situations and reveal certain categories of defects more readily than other approaches. The overall effectiveness of behavioral testing approaches is heavily influenced by the tester’s in-depth system and domain knowledge and experience. Of course, the effectiveness of any test method eventually plateaus or becomes less valuable and testers must employ different approaches to further investigate and evaluate the software under test (The Pesticide Paradox).

TestApi… A Forgotten Soldier in the Fight Against Bugs.

Bug Fighters ala Starship Troopers

I was talking to my team today about doing globalization testing as a part of normal tests in our UI. In this conversation we were discussing ways of generating random strings using different unicode chars. I mentioned that there was a Microsoft created library for use in many different areas of testing, one of which is for string generation. However not many testers, even in Microsoft, know about or use this handy library. I’d previously used the string generation portion to do some fuzz testing in a different project, because it was much easier to use than most fuzz tools normally suggested for this purpose.

I decided it might be a good idea to disseminate this information so that it gets more use amongst our test warriors. The following is the basic information to get you started.

Here is the info on the TestApi library that Microsoft made and has many different uses:

§ Overview of TestApi

§ Part 1: Input Injection APIs

§ Part 2: Command-Line Parsing APIs

§ Part 3: Visual Verification APIs

§ Part 4: Combinatorial Variation Generation APIs

§ Part 5: Managed Code Fault Injection APIs

§ Part 6: Text String Generation APIs

§ Part 7: Memory Leak Detection APIs

§ Part 8: Object Comparison APIs

Here is an example from the String generation section that allows you to generate random strings for testing.

  // Generate a Cyrillic string with a length between 10 and 30 characters.

  StringProperties properties = new StringProperties();
  properties.MinNumberOfCodePoints = 10;
  properties.MaxNumberOfCodePoints = 30;
  properties.UnicodeRanges.Add(new UnicodeRange(UnicodeChart.Cyrillic));

  string s = StringFactory.GenerateRandomString(properties, 1234);

  The generated string may look as follows:
  s: Ӥёӱіӱӎ҄ҤяѪӝӱѶҾүҕГ


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