How are you generating tests from specifications? - testing

I came across a printed article by Bertrand Meyer where he states that tests can be generated from specifications. My development team does nothing like this, but it sounds like a good technique to consider. How are you generating tests from specifications? How would you describe the success your having in discovering program faults via this method?

This might be a reference to RSpec, which is a really clever way of developing tests as a series of requirements. I'm still getting used to it, but it's been very handy in both defining what I need to do and then ensuring I do it.

#Tim Sullivan from Bertrand Meyer it can only be related to Eiffel :)
I think he's talking about ESpec. Given the name RSpec from the Ruby Folk, I think we can give them the label "heavily inspired".

I would say it depends on your specs. I have yet to work anywhere where the specs were good enough to create full unit tests from specifications - the level of detail just wasn't there. My managers always told us that if we specified to that level they could just ship the specs off to India and get it coded on the cheap ;)

There are all sorts of ways to do it, ranging from what I'd consider an 'art form' (and not necessarily good art) all the way to mathematically derived tests from formal specifications. At the end of the day, your development team needs to decided on what they can do based on the schedule they are working with. That being said, being able to test software against specs is a Good Thing.
Only your team can gauge the 'depth' of your tests, and that will probably be a function of how good your specs are. If they say something like, 'the login UI needs to provide a cancel button and a login button, and they need to work', your tests are going to be pretty general. But keep in mind - even very general tests are a Good Thing. Testing is a Good Thing. Too many developers have a bad attitude when it comes to testing, but at the end of the day, you're shipping software which should work, and to me, that means a lot.
The effectiveness your tests will having in finding program faults will depend on the detail you put into them. What is especially nice about having test procedures written to specs is that you can test each build to the same level of detail as the previous build (typically referred to as a regression test).

Related

Starting Testing department

I am joining a company, they dont have any formal testing setup. They expect me to start a testing department. I have good understanding of manual and automated testing. Not sure about how to start or which tools to use for document sharing, bugs tracking.
please guide as much info you can provide.
thanks
This is a very broad question and almost impossible to answer without significantly more knowledge of your companies products, quality goals and existing tooling... But I've got some Opinions :tm: that might help, starting with some philosophy (sorry).
What You're For
The function of a testing department isn't to test; the goal is to help the company be confident in its delivery of products. Your customers want to know that your software is accurate and stable. Your Operations team wants to avoid Production going down. Your Developers want to feel confident that their changes work and don't have any negative side effects.
I personally feel that the best way for a testing team to provide that confidence is not by writing tests; It's by editing them. The testing team provides the tooling, guidelines and expertise to help the rest of the Engineering departments make testing an integral part of the process.
It's like cooking. You don't make a well seasoned meal by chopping and sautéing and stirring and then giving it to a head chef to taste. You taste continually while you go because you're the one who knows what the food should be like. The head chef trains you and provides feedback on the final dish so that you learn how to season correctly.
Choosing Tools
Irrelevant. Mostly.
Your tools need to give you what you're after and then get out of your way. At the moment, the company barely knows what it's after, so you could even use a Google Doc to track defects.
You don't want to get in anyone's way to begin with, or they'll start to resent you. Your team needs to provide value and start to earn the social capital to change the Engineering processes to help deliver your goals.
So, use whatever document sharing tools are already in use; Whether that's a Wiki, Google, Dropbox etc. If you're choosing a new one because there's no collaboration, I'm partial to Notion.
If your team already has a collaborative build tool (eg Jenkins, Travis) it's probably best to stick with that, adding in testing steps. Again, the less friction you introduce, the better your initial outcomes.
I wouldn't bother building and maintaining a test grid; Instead, lean on a vendor like Sauce Labs for infrastructure and expertise. That way you've got easy parallelisation, wide platform coverage, test asset collection, insights, as well as their experience in supporting Testing teams. Disclaimer: I'm the Manager of Developer Relations at Sauce Labs, so I'm probably biased ;)
As for testing tools; If you want your engineering teams to collaborate on test production, you need to stick with an ecosystem they can use. This likely means whatever they're already using.
How To Start Testing
Selecting What To Test
Your organisation wants testing so bad they're hiring you. That implies there's a traumatic event that they want to avoid happening again. So, start there. Find out what it is, and create a test for it.
If Black Friday overwhelmed their site, do Load testing. If their build is always breaking, concentrate on unit testing. If functionality doesn't work in Prod, add an integration test.
Test Coverage
There's a trap for new players, and you're likely to hear this from your devs:
We're so far behind on test coverage we'll never catch up
That is absolutely true.... if you never start! Add the tests that prevent the trauma that bought you on board and you're already adding value; You'll catch that problem next time.
Another trap is setting test coverage goals. Test coverage is a great way to monitor your process but a terrible way to improve it. Force your teams to increase test coverage (or not let it slip) and they'll start to resent the process... And write crap tests just to boost the percentage.
Instead, use coverage for feedback. If coverage goes down during a commit, discuss why and talk about how to improve it. if it drops way down you might want to do something, but a little dip while you're getting started is A-OK.
Assuming you've covered the trauma that got you hired, increasing test coverage is best done on an as-worked basis. If a developer is writing new code, it gets tests. If a developer is modifying old code, it gets tests to (at least) prove that the modifications work, and ideally to prove that they don't break the old functionality either.
You may come across old code that literally can't be tested. That's a good time to refactor that code. If people are scared of refactoring because it might break, point out that that's exactly what tests are for. Try to pull out to a level where you can test. If you can't test a unit, test the class. If you can't test the class, test the package. Then, go back in and start re-working. You have to do it some day.
Oh, no, we'll be replacing the Fizzwangle with a new Buzzshooper implementation soon; There's no need to take the risk of refactoring for testability.
This is a lie. Even if they mean it truthfully, it's a lie. Buzzshooper isn't coming any time soon. Refactor that shit.
Tests Are Code, Code Is Tests
Your tests need to be treated like high quality code. Use all the abstractions you use when writing code, like inheritance, polymorphism, modularisation, composability.
Look at techniques like the Page Object Model for front end testing. Your test code should restrict implementation detail knowledge (eg, element locators) to the least number of places, so that changes are easy to implement.
Oh, and also, your Code is Code. Learn about then help your teams write code for testability, and tests for code-ability. Structure your tests and app so you can test in parallel, reliably, as fast as possible:
Give HTML elements unique, simple IDs
Write tests that test a single thing
Bypass complicated test setup by doing things like pre-populating databases
Log in once, then use session management to avoid doing it again
Use data generators to create unique test data (including logins)
Other Resources
Check out past conference talks like SauceCon Online.
Testing Talks Online has some great discussions and is the closest thing I've found to a real-life meetup during Covid.
There's also a lot of great content over at Ministry of Testing.

TDD and BDD Differences

I honestly don't see the difference between BDD and TDD. I mean, both are just tests if what is expected happens. I've seen BDD Tests that are so fleshed out they practically count as TDD tests, and I've seen TDD tests that are so vague that they black box a lot of code. Let's just say I'm pretty convinced that having both is better.
Here's a fun question though. Where do I start? Do I start out with high level BDD tests? Do I start out with low level TDD tests?
I honestly don't see the difference between BDD and TDD.
That's because there isn't any.
I mean, both are just tests if what is expected happens.
That's wrong. BDD and TDD have absolutely nothing whatsoever to do with testing. None. Nada. Zilch. Zip. Nix. Not in the slightest.
Unfortunately, TDD has the word "test" in pretty much everything (not only in its name, but also in test framework, unit test, TestCase (the class you tpyically inherit from), FooTest (the class which typically holds your tests), testBar (the typical naming pattern for a test method), plus a lot test-related terminology such as "assertion" and "verification") which leads some people to believe that it actually does have something to do with tests. So, some smart people said: "Hey, let's just change the name" to remove any potential for confusion.
And that's what BDD is. It's just TDD with any test-related terminology replaced by examples-of-behavior-related terminology:
Test → Example
Assertion → Expectation
assert → should
Unit → Behavior
Verification → Specification
… and so on
BDD is just TDD with different words. If you do TDD right, you are doing BDD. The difference is that – provided you believe at least in the weak form of the Sapir-Whorf Hypothesis – the different words make it easier to do it right.
BDD is from customers point of view and focuses on excpected behavior of the whole system.
TDD is from developpers point of view and focuses on the implementation of one unit/class/feature. It benefits among others from better architecture (Design for testability, less coupling between modules).
From technical point of view (how to write the "test") they are similar.
I would (from an agile point of view) start with one bdd-userstory and implement it using TDD.
From what I've gathered on Wikipedia, BDD includes acceptance and QA test that can't be done without stakeholders/user input. Also BDD uses a natural language to specify its test while TDD usually uses programming language. There might be some overlap between the two but I think it's not the vagueness but BDD's language that is the main difference.
As for where you are to start, well that really depends on your development process, doesn't it? I assume if you are doing bottom-up that you're going to write TDD first and once you reach higher level you'll use BDD to test if those features work as expected.
As k3b noted: main difference would be that BDD is problem-domain oriented while TDD is more oriented solution-domain.
Just copying the answer from Matthew Flynn which I agree more than "TDD and BDD have nothing to do with tests":
Behavior Driven Development is an extension/revision of Test Driven Development. Its purpose is to help the folks devising the system (i.e., the developers) identify appropriate tests to write -- that is, tests that reflect the behavior desired by the stakeholders. The effect ends up being the same -- develop the test and then develop the code/system that passes the test. The hope in BDD is that the tests are actually useful in showing that the system meets the requirements.
UPDATE
Units of code (individual methods) may be too granular to represent the behavior represented by the behavioral tests, but you should still test them with unit tests to guarantee they function appropriately. If this is what you mean by "TDD" tests, then yes, you still need them.
BDD is about getting your TDD right. It provides "structure and diciplene" to your TDD. It guides you in testing the right thing and doing the right amount of test. Here is a fantastic small post on BDD and TDD,
http://codingcraft.wordpress.com/2011/11/12/bdd-get-your-tdd-right/
I think the biggest contribution of BDD over TDD or any other approaches, is making non-technical people(product owners/customers) part of the software development process at all levels.
Writing executable scenarios in natural languages have almost bridged the gap between the requirement and the delivery.
Product owners can himself run the scenarios he had written and test with different data sets if he wants to play around the behavior of the code written by the development team.
That's amazing! Customer is sitting right at the center and precisely not just asking what he really wants but verifying and experiencing the deliverables as well.
A fantastic article on the differences between TDD and BDD:
http://www.lostechies.com/blogs/sean_chambers/archive/2008/12/07/starting-with-bdd-vs-starting-with-tdd.aspx
Should give you everything you need to know, including problems with both, and examples.
Terminology are different, but in my work, i use TDD to dev detail, mainly for unit test, and the BDD is more high level, for customer, QA or no-tech man .
Overall
BDD is really Design-by-Contract using different terms. Generally speaking, BDD is in the form of Given-When-Then, which is roughly analogous to Preconditions (Given), Check-conditions/Loop-invariants (When), and Post-conditions/Invariants (Then).
Notice
Note that BDD is very much Hoare-logic (i.e. {P}C{Q} or {P}recondition-[C]ommand-{Q}Post-condition). Therefore:
Preconditions (Given) must hold true for the command (method/function) to compute correctly. Any violation of the Given (precondition) signals a fault in the calling Client code.
Command(s) (When) are what happens after the precondition(s) are met. In Eiffel, they can be punctuated within the method or function code with other contracts. Think about these as though they are QA/QC checks along a process assembly line.
Post-conditions (Then) must hold true once the Command (When) is finished.
Moral of the Story
Because BDD is just DbC (Hoare-logic) repackaged in different words, this means it is not TDD. Why? Because TDD is not about preconditions/checks/post-condition contracts tied directly to methods, functions, properties, and class-state. TDD is the next step up the ladder in testing methods, functions, properties, and classes with their discrete states. Once you see this and fully appreciate that TDD is not BDD and BDD is not TDD, but that they are separate and complementary technologies for software correctness proofs—THEN—you will finally understand these topics correctly. You will also use and apply them correctly.
Conclusion
Eiffel is the only language I am aware of where BDD (Design-by-Contract) is baked raw into both the language specification and compiler. It is not a Frankenstein bolt-on monster with limitations. In Eiffel, BDD (aka DbC) is an elegant, helpful, useful, and direct participant in the software correctness toolbox.
See Also
Wikipedia helps defined Hoare-logic. See: https://en.wikipedia.org/wiki/Hoare_logic
I have created an example in Eiffel that you can look at. See:
Primary class: https://github.com/ljr1981/stack_overflow_answers/blob/main/src/so_73347395/so_73347395.e
Test class: https://github.com/ljr1981/stack_overflow_answers/blob/main/testing/so_73347395/so_73347395_test_set.e
The main difference is just the wording. BDD uses a more verbose style so that it can be read almost like a sentence.

In agile like development, who should write test cases? [closed]

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Our team has a task system where we post small incremental tasks assigned to each developer.
Each task is developed in its own branch, and then each branch is tested before being merged to the trunk.
My question is: Once the task is done, who should define the test cases that should be done on this task?
Ideally I think the developer of the task himself is best suited for the job, but I have had a lot of resistance from developers who think it's a waste of their time, or that they simply don't like doing it.
The reason I don't like having my QA people do it, is because I don't like the idea of them creating their own work. For example they might leave out things that are simply too much work to test, and they may not know the technical detail that is needed.
But likewise, the down part of developers doing the test cases, is that they may leave out things that they think will break. (even subconsciously maybe)
As the project manager, I ended up writing the test cases for each task myself, but my time is taxed and I want to change this.
Suggestions?
EDIT: By test cases I mean the description of the individual QA tasks that should be done to the branch before it should be merged to the trunk. (Black Box)
The Team.
If a defect gets to a customer, it is the team's fault, therefore the team should be writing test cases to assure that defects don't reach the customer.
The Project Manager (PM) should understand the domain better than anyone on the team. Their domain knowledge is vital to having test cases that make sense with regard to the domain. They will need to provide example inputs and answer questions about expectations on invalid inputs. They need to provide at least the 'happy path' test case.
The Developer(s) will know the code. You suggest the developer may be best for the task, but that you are looking for black box test cases. Any tests that a developer comes up with are white box tests. That is the advantage of having developers create test cases – they know where the seams in the code are.
Good developers will also be coming to the PM with questions "What should happen when...?" – each of these is a test case. If the answer is complex "If a then x, but if b then y, except on Thursdays" – there are multiple test cases.
The Testers (QA) know how to test software. Testers are likely to come up with test cases that the PM and the developers would not think of – that is why you have testers.
I think the Project Manager, or Business Analyst should write those test cases.
They should then hand them over to the QA person to flesh out and test.
That way you ensure no missing gaps between the spec, and what's actually tested and delivered.
The developer's should definately not do it, as they'll be testing their unit tests.
So it's a waste of time.
In addition these tests will find errors which the developer will never find as they are probably due to a misunderstanding in the spec, or a feature or route through the code not having been thought through and implemented correctly.
If you find you don't have enough time for this, hire someone else, or promote someone to this role, as it's key to delivering an excellent product.
From past experience, we had pretty good luck defining tests at different levels to test slightly different things:
1st tier: At the code/class level, developers should be writing atomic unit tests. The purpose is to test individual classes and methods as much as possible. These tests should be run by developers as they code, presumably before archiving code into source control, and by a continuous-integration server (automated) if one is being used.
2nd tier: At the component integration level, again have developers creating unit tests, but that test the integration between components. The purpose is not to test individual classes and components, but to test how they interact with each other. These tests should be run manually by an integration engineer, or automated by a continuous-integration seerver, if one is in use.
3rd tier: At the application level, have the QA team running their system tests. These test cases should be based off the business assumptions or requirements documents provided by a product manager. Basically, test as if you were an end user, doing the things end users should be able to do, as documented int eh requirements. These test cases should be written by the QA team and the product managers who (presumably) know what the customer wants and how they are expected to use the application.
I feel this provides a pretty good level of coverage. Of course, tiers 1 and 2 above should ideally be run before sending a built application to the QA team.
Of course, you can adapt this to whatever fits your business model, but this worked pretty well at my last job. Our continous-integration server would kick out an email to the development team if one of the unit tests failed during the build/integration process too, incase someone forgot to run their tests and committed broken code into the source archive.
We experimented with a pairing of the developer with a QA person with pretty good results. They generally 'kept each other honest' and since the developer had unit tests to handle the code, s/he was quite intimate with the changes already. The QA person wasn't but came at it from the black box side. Both were held accountable for completeness. Part of the ongoing review process helped to catch unit test shortcomings and so there weren't too many incidents that I was aware of where anyone was purposely avoiding writing X test because it would likely prove there was a problem.
I like the pairing idea in some instances and think it worked pretty well. Might not always work, but having those players from different areas interact helped to avoid the 'throw it over the wall' mentality that often happens.
Anyhow, hope that is somehow helpful to you.
The reason I don't like having my QA people do it, is because I don't like the idea of them creating their own work. For example they might leave out things that are simply too much work to test, and they may not know the technical detail that is needed.
Yikes, you need to have more trust in your QA department, or a better one. I mean, imagine of you had said "I don't like having my developers develop software. I don't like the idea of them creating their own work."
As a developer, I Know that there are risks involved in writing my own tests. That's not to say I don't do that (I do, especially if I am doing TDD) but I have no illusions about test coverage. Developers are going to write tests that show that their code does what they think it does. Not too many are going to write tests that apply to the actual business case at hand.
Testing is a skill, and hopefully your QA department, or at least, the leaders in that department, are well versed in that skill.
"developers who think it's a waste of their time, or that they simply don't like doing it" Then reward them for it. What social engineering is necessary to get them to create test cases?
Can QA look over the code and test cases and pronounce "Not Enough Coverage -- Need More Cases". If so, then the programmer that has "enough" coverage right away will be the Big Kahuna.
So, my question is: Once the task is done, who should define the goal of "enough" test cases for this task? Once you know "enough", you can make the programmers responsible for filling in "enough" and QA responsible for assuring that "enough" testing is done.
Too hard to define "enough"? Interesting. Probably this is the root cause of the conflict with the programmers in the first place. They might feel it's a waste of their time because they already did "enough" and now someone is saying it isn't "enough".
the QA people, in conjunction with the "customer", should define the test cases for each task [we're really mixing terminology here], and the developer should write them. first!
Select (not just pick randomly) one or two testers, and let them write the test cases. Review. It could also be useful if a developer working with a task looks at the test cases for the task. Encourage testers to suggest improvements and additions to test sets - sometimes people are afraid to fix what the boss did. This way you might find someone who is good at test design.
Let the testers know about the technical details - I think everyone in an agile team should have read access to code, and whatever documentation is available. Most testers I know can read (and write) code, so they might find unit tests useful, possibly even extend them. Make sure the test designers get useful answers from the developers, if they need to know something.
My suggestion would be to having someone else look over the test cases before the code is merged to ensure quality. Granted this may mean that a developer is overlooking another developer's work but that second set of eyes may catch something that wasn't initially caught. The initial test cases can be done by any developer, analyst or manager, not a tester.
QA shouldn't write the test cases as they may be situations where the expected result hasn't been defined and by this point, it may be hard to have someone referee between QA and development if each side thinks their interpretation is the right one. It is something I have seen many many times and wish it didn't happen as often as it does.
I loosely break my tests down into "developer" tests and "customer" tests, the latter of which would be "acceptance tests". The former are the tests that developers write to verify that their code is performing correctly. The later are tests that someone other than developers write to ensure that behavior matches the spec. The developers must never write the accepatance tests because their creation of the software they're testing assumes that they did the right thing. Thus, their acceptance tests are probably going to assert what the developer already knew to be true.
The acceptance tests should be driven by the spec and if they're written by the developer, they'll get driven by the code and thus by the current behavior, not the desired behavior.
The Agile canon is that you should have (at least) two layers of tests: developer tests and customer tests.
Developer tests are written by the same people who write the production code, preferably using test driven development. They help coming up with a well decoupled design, and ensure that the code is doing what the developers think it is doing - even after a refactoring.
Customer tests are specified by the customer or customer proxy. They are, in fact, the specification of the system, and should be written in a way that they are both executable (fully automated) and understandable by the business people. Often enough, teams find ways for the customer to even write them, with the help of QA people. This should happen while - or even before - the functionality gets developed.
Ideally, the only tasks for QA to do just before the merge, is pressing a button to run all automated tests, and do some additional exploratory (=unscripted) testing. You'll want to run those tests again after the merge, too, to make sure that integrating the changes didn't break something.
A test case begins first in the story card.
The purpose of testing is to drive defects to the left (earlier in the software development process when they are cheaper and faster to fix).
Each story card should include acceptance criteria. The Product Owner pairs with the Solution Analyst to define the acceptance criteria for each story. This criteria is used to determine if a story card's purpose has been meet.
The story card acceptance criteria will determine what automated unit tests need to be coded by the developers as they do Test Driven Development. It will also drive the automated functional test implemented by the autoamted testers (and perhaps with developer support if using tools like FIT).
Just as importantly, the acceptance criteria will drive the automated performance tests and can be used when analyzing the profiling of the application by the developers.
Finally, the user acceptance test will be determined by the acceptance criteria in the story cards and should be designed by the business partner and or users. Follow this process and you will likely release with zero defects.
I've rarely have heard of or seen Project Managers write test cases except for in the smaller teams. In any large,complex software application have to have an analyst that really knows the application. I worked at a mortgage company as a PM - was I to understand sub-prime lending, interest rates, and the such? Maybe at a superficial level, but real experts needed to make sure those things worked. My job was to keep the team healthy, protect the agile principles, and look for new opportunities for work for my team.
The system analyst should review over all test-cases and its correct relation with the use-cases.
Plus the Analyst should perform the final UAT, which could be based on test-cases also.
So the analyst and the quality guy are making sort of peer-review.
The quality is reviewing the use-cases while he is building test-cases, and the analyst is reviewing the test-cases after they are written and while he is performing UAT.
Of course BA is the domain expert, not from technical point of view. BA understands the requirements and the test cases should be mapped to the requirements. Developers should not be the persons writing the test cases to test against their code. QA can write detail test steps per requirement. But the person who writes the requirement should dictate what needs to be tested. Who actually writes the test cases, I dont care too much as long as the test cases can be traced back to requirements. I would think it makes sense that BA guides the testing direction or scope, and QA writes the granular testing plans.
We need to evolve from the "this is how it has been done or should be done mentality" it is failing and failing continuously. The best way to resolve the test plan/cases writing issue is that test cases should be written on the requirements doc in waterfall or the user story in agile as those reqs/user stories are being written. This way there is no question what needs to be tested and QA and UAT teams can execute the test case(s) and focus time on actual testing and defect resolution.

How much a tester should know about internal details of code?

How useful, if at all, is for the testers on a product team to know about the internal code details of a product. This does not mean they need to know every line of code but a good idea of how the code is structured, what is the object model, how the various modules are inter-linked, what are the inter-dependencies between various features etc.? This can argubaly help them in finding related issues or defects once they hit one. On the other side, this can potentially 'bias' their "user-centric" approach towards evaluating and certifying the product and can effect the testing results in the end.
I have not heard of any specific model for such interaction. (Lets assume a product that users, potentially non-technical consume, and not a framework or API that the testers are testing - in the latter case the testers may need to understand the code to test that because the user is another programmer).
That entirely depends upon the type of testing being done.
For functional system testing, the testers can and probably should be oblivious to the details of the implementation -- if they know the details they may inadvertently account for that in their test strategy and not properly test the product.
For performance and scalability testing it's often helpful for the testers to have some high-level knowledge of the structure of the codebase, as it's beneficial in identifying potential performance hotspots, and therefore writing targetted test cases. The reason this is important is that generally performance testing is a broad open-ended process, so anything that can be done to focus the testing to get results is beneficial to everybody.
This sounds similiar to this previous question: Should QA test from a strictly black-box perspective?
I've never seen a circumstance where a tester who knew a lot about the internals of system was disadvantaged.
I would assert that there are self justifying myths that an informed tester is as adequate or even better than a deeply technical one because:
It allows project managers to use 'random or low quality resources' for testing. The 'as uninformed as the user myth'. If you want this type of testing - get some 'real' users to test your stuff.
Testers are still often seen as cheaper and less valuable than developers. The 'anybody can do blackbox testing myth'.
Development can defer proper testing to the test team. Two myths in one 'we don't need to train testers' and 'only the test team does testing' myths.
What you are looking at here is the difference between black box (no knowledge of the internals), white box (all knowledge) and grey box (some select knowledge).
The answer really depends on the purpose of the code. For integration heavy projects then where and how they communicate, even if it is entirely behind the scenes, allows testers to produce appropriate non-functional test cases.
These test cases are determining whether or not a component will gracefully handle the lack of availability of a dependency. It can also be used to identify performance related issues.
For example: As a tester if I know that the Web UI component defers a request to a orchestration service that does the real work then I can construct a scenario where the orchestration takes a long time (high load). If the user then performs another request (simulating user impatience) and the web service will receive a second request while the first is still going. If we continually repeat this the web service will eventually die from stress. Without knowing the underlying model it would not be easy to find the problem
In most cases for functionality testing then black box is preferred, as soon as you move towards non-functional or system integration then understanding the interactions can assist in ensuring appropriate test coverage.
Not all testers are skilled or comfortable working/understanding the component interactions or internals so it is on a per tester/per system basis on whether it is appropriate.
In almost all cases we start with black box and head towards white as the need sees.
A tester does not need to know internal details.
The application should be tested without any knowledge of interal structure, development problems, externals depenedncies.
If you encumber the tester with those additional info you push him into a certain testing scheme and the tester should never be pushed in a direction he should just test from a non coder view.
There are multiple testing methodologies that require code reviewing, and also those that don't.
The advantages to white-box testing (i.e. reading the code) is that you can tailor your testing to only test areas that you know (from reading the code) will fail.
Disadvantages include time wasted from actual testing to understand the code.
Black-box testing (i.e. not reading the code) can be just as good (or better?) at finding bugs than white-box.
Normally both types of testing can happen on one project, developers white-box unit testing, and testers black-box integration testing.
I prefer Black Box testing for final test regimes
In an ideal world...
Testers should know nothing about the internals of the code
They should know everything the customer will - i.e. have the documents/help required to use the system/application.(this definetly includes the API description/documents if it's some sort of code deliverable)
If the testers can't manage to find the defects with these limitations, you haven't documented your API/application enough.
If they are dedicated testers (Only thing they do) then I think they should know as little about the code as possible that they are attempting to test.
Too often they try to determine why its failing, that is the responsibility of the developer not the tester.
That said I think developers make great testers, because we tend to know the edge cases for certain types of functionality.
Here's an example of a bug which you can't find if you don't know the code internals, because you simply can't test all inputs:
long long int increment(long long int l) {
if (l == 475636294934LL) return 3;
return l + 1;
}
However, in this case it would be found if the tester had 100% code coverage as a target, and looked at only enough of the internals to write tests to achieve that.
Here's an example of a bug which you quite likely won't find if you do know the code internals, because false confidence is contagious. In particular, it is usually not possible for the author of the code to write a test which catches this bug:
int MyConnect(socket *sock) {
/* socket must have been bound already, but that's OK */
return RealConnect(sock);
}
If the documentation of MyConnect fails to mention that the socket must be bound, then something unexpected will happen some day (someone will call it unbound, and presumably the socket implementation will select an arbitrary local address). But a tester who can see the code often doesn't have the mindset of "testing" the documentation. Unless they're really on form, they won't notice that there's an assumption in the code not mentioned in the docs, and will just accept the assumption. In contrast, a tester writing from the docs could easily spot the bug, because they'll think "what possible states can a socket be in? I'll do a test for each". Since no constraints are mentioned, there's no reason they won't try the case that fails.
Answer: do both. One way to do this is to write a test suite before you see/write the code, and then add more tests to cover any special cases you introduce in your implementation. This applies whether or not the tester is the same person as the programmer, although obviously if the programmer writes the second kind of test, then only one person in the organisation has to understand the code. It's arguable whether it's a good long-term strategy to have code only one person has ever understood, but it's widespread, because it certainly saves time getting something out the door.
[Edit: I decline to say how these bugs came about. Maybe the programmer of the first one was clinically insane, and for the second one there are some restrictions on the port used, in order to workaround some weird network setup known to occur, and the socket is supposed to have been created via some de-weirdifying API whose existence is mentioned in the general sockets docs, but they neglect to require its use. Clearly in both these cases the programmer has been very careless. But that doesn't affect the point: the examples don't need to be realistic, since if you don't catch bugs that only a very careless programmer would make, then you won't catch all the actual bugs in your code unless you never have a bad day, make a crazy typo, etc.]
I guess it depends how good of testing you want. If you just want to sanity check the common scenarios, then by all means, just give the testers / pizza-eaters the application and tell them to go crazy.
However, if you'd like to have a chance at finding edge cases, performance or load issues, or a whole lot of other issues that hide in the depths of your code, you'd probably be better off hiring testers who know how and when to use white box techniques.
Your call.
IMHO, I think the industry view of testers is completely wrong.
Think about it ... you have two plumbers, one is extremely experienced, knows all the rules, the building codes, and can quickly look at something and know if the work is done right or not. The other plumber is good, and get the job done reliably.
Which one would you want to do the final inspection to make sure you don't come home to a flooded house? In fact, in what other industry do they allow someone who knows hardly anything about the system they are inspecting to actually do the inspection?
I have seen the bar for QA go up over the years, and that makes me happy. In time, QA may become something that devs aspire to be.
In short, not only should they be familiar with the code being tested, but they should have an understanding that rivals the architects of the product, as well as be able to effectively interface with the product owner(s) / customers to ensure that what is being created is actually what they want. But now I am going into a whole seperate conversation ...
Will it happen? Probably sooner than you think. I have been able to reduce the number of people needed to do QA, increase the overall effectiveness of the team, and increase the quality of the product simply by hiring very skilled people with dev / architect backgrounds with a strong aptitude for QA. I have lower operating costs, and since the software going out is higher quality, I end up with lower support costs. FWIW ... I have found that while I can backfill the QA guys effectively into a dev role when needed, the opposite is almost always not true.
If there is time, a tester should definitely go through a developers code. This way, you can improve your tests to get better coverage.
So, maybe if you write your black box tests looking at the spec and think you have the time to execute all of those and will still be left with time, going through code cannot be a bad idea.
Basically it all depends on how much time you have.. Another thing you can do to improve coverage is look at the developers design documents. Those should give you a good idea of what the code is going to look like...
Testers have the advantage of being familiar with both the dev code and the test code!
I would say they don't need to know the internal code details at all. However they do need to know the required functionality and system rules in full detail - like an analyst. Otherwise they won't test all the functionality, or won't realise when the system misbehaves.
For user acceptance testing the tester does not need to know the internal code details of the app. They only need to know the expected functionality, the business rules. When a bug is reported
Whoever is fixing the bug should know the inter-dependencies between various features.

Model Based Testing Strategies

What strategies have you used with Model Based Testing?
Do you use it exclusively for
integration testing, or branch it
out to other areas
(unit/functional/system/spec verification)?
Do you build focused "sealed" models or do you evolve complex onibus models over time?
When in the product cycle do you invest in creating MBTs?
What sort of base test libraries do you exclusively create for MBTs?
What difference do you make in your functional base test libraries to better support MBTs?
­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­
[There are several essays worth reading on this. Stack Overflow won't let me post more than one, so I've aggregated them in a blog post, linked at the end of this answer.]
First, a quick note on terms. I tend to use James Bach’s definition of Testing as “Questioning a product in order to evaluate it”. All test rely on /mental/ models of the application under test. The term Model-Based Testing though is typically used to describe programming a model which can be explored via automation. For example, one might specify a number of states that an application can be in, various paths between those states, and certain assertions about what should occur in on the transition between those states. Then one can have scripts execute semi-random permutations of transitions within the state model, logging potentially interesting results.
There are real costs here: building a useful model, creating algorithms for exploring it, logging systems that allow one to weed through for interesting failures, etc. Whether or not the costs are reasonable has a lot to do with what are the questions you want to answer? In general, start with “What do I want to know? And how can I best learn about it?” rather than looking for a use for an interesting technique.
All that said, some excellent testers have gotten a lot of mileage out of automated model-based tests. Sometimes we have important questions about the application under test that are best explored by automated, high-volume semi-randomized tests. Harry Robinson (one of the leading theorists and proponents of model-based testing) describes one very colorful example where he discovered many interesting bugs in Google driving directions using a model-based test (written with ruby’s Watir library). 1
Robinson has used MBT successfully at companies including Bell Labs, Microsoft, and Google, and has a number of helpful essays.[2]
Ben Simo (another great testing thinker and writer) has also written quite a bit worth reading on model-based testing.[3]
Finally, a few cautions: To make good use of a strategy, one needs to explore both its strengths and its weaknesses. Toward that end, James Bach has an excellent talk on the limits and challenges of Model-Based Testing. This blog post of Bach’s links to his hour long talk (and associated slides).[4]
I’ll end with a note about what Boris Beizer calls the Pesticide Paradox: “Every method you use to prevent or find bugs leaves a residue of subtler bugs against which those methods are ineffective.” Scripted tests (whether executed by a computer or a person) are particularly vulnerable to the pesticide paradox, tending to find less and less useful information each time the same script is executed. Folks sometimes turn to model-based testing thinking that it gets around the pesticide problem. In some contexts model-based testing may well find a much larger set of bugs than a given set of scripted tests…but one should remember that it is still fundamentally limited by the Pesticide Paradox. Remembering its limits — and starting with questions MBT addresses well — it has the potential to be a very powerful testing strategy.
Links to all essays mentioned above can be found here: http://testingjeff.wordpress.com/2009/06/03/question-about-model-based-testing/
We haven't done any/much I&T and use unit testing almost exclusively, seasoned with a bit of system testing. But our focus is clearly on unit testing. I'm pretty strict on the APIs we build/provide, so the assumption is, if it works by itself, it will work in conjunction and there hasn't been much wrong in it yet.
Our models are focused on a single purpose/module with as little dependencies as possible.
The focus is always to start as early as possible (TDD-kinda), but unfortunately we don't always get to it. The problem is, you always have to sell it to management and then it's hard because while testing improves stability (overall QA), the people from the outside (outside of tech) can't really relate to what that means until something bad happened.
Since we use PHP, we employ PHPUnit for the unit tests. All in all, we do CI with various different tools. :)
Harry Robinson, an author of MBT-books and worked a lot with it for example at Google and Microsoft have this site with some great info and whitepapers.
http://www.geocities.com/model_based_testing/
The best way is to try by yourself a Model based testing tool. It's the best way for know if the model based testing is adapted in your context. And what sort of strategies is the good one.
I advise you the "MaTeLo" tool of All4Tec (www.all4tec.net)
"MaTeLo is a test cases generator for black box functional and system testing. Conformed to the Model Based Testing approach, MaTeLo uses Markov chains for modeling the test. This statistic addin allows products validation in a Systematic way. The efficiency is achieved by a reduction of the human resources needed, an increase of the model reuse and by the enhancement of the test strategy relevance (due to the reliability target). MaTeLo is independent and user-friendly, offers to the validation activities to pass from test scripting to real test engineering and to focus on the real added value of testing: the test plans"
You can ask an evaluation licence and try by yourself.
You can find some exemples here : http://www.all4tec.net/wiki/index.php?title=Tutorials