Skip to main content

Visual Studio 2015 Update 1–Parallel Test Execution

If you are still looking for an excuse to start installing Visual Studio 2015 Update 1, here I got you one: a new feature that existed before but is now finally back in the box is Parallel Test Execution.

What is it?

From the release notes:

The Visual Studio Test Platform introduces support parallel execution of test cases.

Parallel test execution leverages the available cores on the machine, and is realized by launching the test execution engine on each available core as a distinct process, and handing it a container (assembly, DLL, or relevant artifact containing the tests to execute), worth of tests to execute. The unit of scheduling is the test container. Within each container, the tests will be executed as per the semantics of the test framework. If there are many such containers, then as processes finish executing the tests within a container, they are handed the next available container.

Parallel execution is supported through all launch points - CI, command line (CLI) and the IDE (Test Explorer, CodeLens, various “Run” commands, etc.), and the Test Explorer indicators track the progress of tests executing in parallel.

Getting started
  • Open Visual Studio 2015(don’t forget to install Update 1 first Glimlach)
  • Open the solution containing the tests.
    • Note that in order to leverage the Parallel Test Execution features, tests should be split out over multiple ‘containers’(assemblies)
  • Go to Test –> Test Settings –> Select Test Settings File
  • Select the .testsettings file you want to use.
    • If you don’t have a .testsettings file yet, just create an empty xml file and change the extension to .testsettings

clip_image001

  • Open the file in Visual Studio via File –> Open—> File… –> Open With(click on the small arrow next to the Open button) –> XML Editor
  • Paste the following code:
  • Change the MaxCPUCount value according to the following rules:
    • ‘n’ (where 1 <= n <= number of cores) : up to ‘n’ processes will be launched.
    • ‘n’ of any other value : The number of processes launched will be as many as the available cores on the machine.
  • Now run your tests…

Remark: I noticed that it only worked for MSTest. When using NUnit or XUnit no tests were executed.

Popular posts from this blog

Podman– Command execution failed with exit code 125

After updating WSL on one of the developer machines, Podman failed to work. When we took a look through Podman Desktop, we noticed that Podman had stopped running and returned the following error message: Error: Command execution failed with exit code 125 Here are the steps we tried to fix the issue: We started by running podman info to get some extra details on what could be wrong: >podman info OS: windows/amd64 provider: wsl version: 5.3.1 Cannot connect to Podman. Please verify your connection to the Linux system using `podman system connection list`, or try `podman machine init` and `podman machine start` to manage a new Linux VM Error: unable to connect to Podman socket: failed to connect: dial tcp 127.0.0.1:2655: connectex: No connection could be made because the target machine actively refused it. That makes sense as the podman VM was not running. Let’s check the VM: >podman machine list NAME         ...

Azure DevOps/ GitHub emoji

I’m really bad at remembering emoji’s. So here is cheat sheet with all emoji’s that can be used in tools that support the github emoji markdown markup: All credits go to rcaviers who created this list.

Cache stampede: when our cache turned against us

While investigating some performance issues, we ran into an ASP.NET Core API that cached a fairly expensive aggregation query for 60 seconds. Under normal load, that was fine: one request rebuilds the cache, everyone else reads from it. Under peak load, dozens of requests would arrive in that same expiry window, all see a cache miss, and all fire the same expensive query in parallel. The database didn't like that. That was the moment when our caching layer stopped helping and started hurting. A burst of requests comes in at the same time, all miss the cache, and all go hammer the database or the downstream API at once. That's a cache stampede . The cache was supposed to protect our backend, and for a few hundred milliseconds it did the opposite. Why this happens IMemoryCache.GetOrCreate (and its async sibling) looks like it protects you, but it doesn't add any locking on its own. Look at the naive version: public async Task<Report> GetReportAsync(string key) ...