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How should I unit test threaded code?
The classical unit testing is basically just putting x in and expecting y out, and automating that process. So it's good for testing anything that doesn't involve time. But then, most of the nontrivial bugs I've come across have had something to do with timing. Threads corrupt each others' data, or cause deadlocks. Nondeterministic behavior happens – in one run out of million. Hard stuff.
Is there anything useful out there for "unit testing" parts of multithreaded, concurrent systems? How do such tests work? Isn't it necessary to run the subject of such test for a long time and vary the environment in some clever manner, to become reasonably confident that it works correctly?
An example of a real-world scenario that could be covered by a unit test is a checking that your car door can be unlocked, where you test that the door is unlocked using your car key, but it is not unlocked using your house key, garage door remote, or your neighbour's (who happen to have the same car as you) key.
There are 2 types of Unit Testing: Manual, and Automated.
unittest-parallel is a parallel unit test runner for Python with coverage support. By default, unittest-parallel runs unit tests on all CPU cores available. To run your unit tests with coverage, add either the "--coverage" option (for line coverage) or the "--coverage-branch" for line and branch coverage.
Most of the work I do these days involves multi-threaded and/or distributed systems. The majority of bugs involve "happens-before" type errors, where the developer assumes (wrongly) that event A will always happen before event B. But every 1000000th time the program is run, event B happens first, and this causes unpredictable behavior.
Additionally, there aren't really any good tools to detect timing issues, or even data corruption caused by race conditions. Tools like Helgrind and drd from the Valgrind toolkit work great for trivial programs, but they are not very useful in diagnosing large, complex systems. For one thing, they report false positives quite frequently (Helgrind especially). For another thing, it's difficult to actually detect certain errors while running under Helgrind/drd simply because programs running under Helgrind run almost 1000x slower, and you often need to run a program for quite a long time to even reproduce the race condition. Additionally, since running under Helgrind totally changes the timing of the program, it may become impossible to reproduce a certain timing issue. That's the problem with subtle timing issues; they're almost Heisenbergian in the sense that altering a program to detect timing issues may obscure the original issue.
The sad fact is, the human race still isn't adequately prepared to deal with complex, concurrent software. So unfortunately, there's no easy way to unit-test it. For distributed systems especially, you should plan your program carefully using Lamport's happens-before diagrams to help you identify the necessary order of events in your program. But ultimately, you can't really get away from brute-force unit testing with randomly varying inputs. It also helps to vary the frequency of thread context-switching during your unit-test by, e.g. running another background process which just takes up CPU cycles. Also, if you have access to a cluster, you can run multiple unit-tests in parallel, which can detect bugs much quicker and save you a lot of time.
If you can run your tests under Linux, valgrind includes a tool called helgrind which purports to detect race conditions and potential deadlocks in programs that use pthreads; you might get some benefit from running your multithreaded code under that, since it will report potential errors even if they didn't actually occur in that particular test run.
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