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.
I have a task to write tests for future Django Channels+DRF project, don't ask why (we only have swagger documentation for now). So the tests have to test the user use cases (like scenario that may be complex). I have researched about that and found BDD. Here is the question, considering that our project later may have simple unit tests too what should I use, i.e. BDD seems decent but I think it may be excessive for use and may be there is a way of just writing unittests for user use case scenarious and I can get by with that. Does anyone have experience with that? It would be great if you provide articles and code examples.
Scenarios are a bit different to use-cases. A use-case often covers several capabilities. For instance, in the simple laundry use-case shown here, a housekeeper does several things when performing a wash:
washes each load
dries each load.
folds certain items
irons some items
All of these go into the "weekly laundry" use-case.
A scenario in BDD is much more fine-grained. It describes one capability taking place in a particular context or set of contexts. So for instance you might have:
Given the weekly laundry has been washed and dried
And it contains several sheets
And some underpants
When the housekeeper does the folding
Then the sheets should be folded
But the underpants should not.
You can see that we've skipped a couple of the capabilities. This scenario is focused on the capability of folding, and shows how a well-behaved housekeeper would do it. Washing and drying would have to be covered in separate scenarios.
So that's the difference between a use-case and a scenario. Now let's look at a unit test.
When we write code, we don't write it all in one big class or function. We split it up into small pieces. In the same way that a scenario describes an example of the behaviour of the system from the perspective of the users, a unit test describes the behaviour of a class or other small piece of code from the perspective of its users - usually other classes!
So let's imagine that we're on a car purchasing site. We have several capabilities:
Authentication
Searching for cars
Purchasing a car
Listing a car
Removing a car from the list
Each of these will have lots of different classes making it up. Even searching for a car could involve a front-end, a search component, a database of cars, a persistence layer, a webserver, etc.. For each piece of code, we describe the behaviour of that code.
(BDD actually started out at this level; with examples of how classes behave - JBehave was intended to replace JUnit. But JUnit got better and we didn't need this bit any more. I still find it helpful to think of these as examples rather than tests.)
Typically I'll have both scenarios and unit tests in my codebase; one set of them looking from a user / stakeholder perspective at the whole system, and the other set describing my classes in finer detail.
The scenarios help me show how the system behaves and why it's valuable. The unit tests help me drive out good design and separate responsibilities. Both of them provide living documentation which helps to keep the system maintainable and make it easier for newcomers to come on board.
Generally this is how I program:
I have a rough idea of what I want to achieve
I talk to someone about it and write down some scenarios
If we don't quite know what we're looking for, I'll get something working (a spike)
Once we understand better what we're looking for, I automate the scenario first
I take the simplest case and start writing the UI
When the UI needs another class to work, I write some examples of how that code should work (unit tests) first
Then I write the code (or refactor it, because spikes are messy)
When that code needs another class to work, I write some examples of it
If I don't have code that's needed at any point in my unit tests, I use mocks.
Generally we keep the scenarios and the unit tests in different places.
You can see some examples of how I've done this here. It's a tetris game with scenarios which automate the whole game through the UI, and lower-level unit tests which describe the behaviour of particular pieces like the heartbeat which drops the shapes.
Having said that - if your codebase is very simple, you can probably get away with just the scenarios or just the unit tests; you might not need both. But if it starts getting more complex, consider refactoring and adding whatever you need. It's OK to be pragmatic about it, as long as it's easy to change.
I am interested in proving that some robot controller does not reach any faulty state, which I would define by a set of predicates. I know that there are open-source software tools to achieve that. For instance, I heard of BLAST (Berkeley Lazy Abstraction Software Verification Tool), but are you aware of any other that may be simpler to use and/or more targeted to my particular application?
Have you ever used BLAST or another such tool in one of your project, and do you think that the benefits outweigh the effort needed to deploy such tools?
You might find Frama-C useful.
For evaluations by people who are not Frama-C developers, see these two articles. Some engineers developing safety-critical code (e.g. DO-178B level A) have found formal annotations and analysis based on weakest precondition techniques worth the investment, but traditional tests are very expensive for them. This last link is about Caveat, a closed-source analyzer that Frama-C intends to replace in due time.
Your question makes it sound as if you might perhaps appreciate Frama-C's Aoraï plug-in.
Whether this is all time well spent in your case is probably more a matter of whether you consider learning about these techniques a joy or a chore.
Does any one know how to manage Software/Web Applications Testing process ?
The Hexawise test case generator can dramatically reduce your test design time (e.g., figuring out what combinations of browsers, configurations and functions should be tested so as to achieve maximum coverage in a manageable number of test cases).
Free trials are available at: http://hexawise.com/users/new
Disclosure: I created the tool based on the applied statistics-based Design of Experiments principles my dad, William G. Hunter, used to teach about when he was a professor at the University of Wisconsin.
/Slight tangent: it is surprising to me that Design of Experiments methods are widely used in manufacturing today, but rarely used in software testing. The same types of combinatorial explosions exist in both manufacturing (e.g,. thing about how many billions of ways there could be to manufacture a radial tire) and software testing (where billions of potential use cases exist in most non-trivial software applications particularly when browser types and/or configuration options are thrown into the mix). These Design of Experiments methods dramatically improve efficiency in both situations (and are extremely easy to prove in software testing projects by simple "bake-offs"); despite this they remain unused in the vast majority of testing organizations, even at Fortune 100 firms. I'm hoping to raise awareness and help change this. End of tangent/
Justin
There are lots of aspects to it, but one tool that is quickly becoming important in our arsenal is Selenium.
You need to test multiple layers of your software. Unit tests cover the smallest segments of code, like a specific method's output, rather than the way methods interact. Then at the opposite range of the spectrum there is the integrated user experience testing, which mimics a user pressing buttons and doing things with your application (using a tool like Selenium if you're writing web applications).
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.