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exercism / exalysis

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Mentoring tool for the Go track on Exercism. Downloads students code, checks it and provides suggestions.

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Exalysis

Build Status

Exalysis is a tool designed to help mentors of the Exercism Go track. It will automatically run the tests on a student's solution, check gofmt and golint, and make some helpful suggestions for the student based on static analysis of the code for common errors and patterns (see sample Exalysis output).

It's not perfect: you should check Exalysis's suggestions before sending them to the student, and add your own notes if necessary, but it can dramatically speed up the process of mentoring by automating these repetitive tasks.

Status

This is a proof of concept. I use it to mentor, and enhance/extend it as I go.

Exercise implementations:

  • Two Fer
  • Hamming
  • Raindrops
  • Scrabble Score
  • Isogram
  • Difference of Squares
  • Luhn
  • Parallel Letter Frequency

Exalysis will do its format, lint, and test checks on any solution, but specific suggestions have so far been implemented for only the exercises above. If you'd like to add support for a new exercise, please submit a PR! (See 'Contributions' below.)

Installation

Make sure you are in any go module path on your computer. If you have no local modules (or are not sure what that means), choose any empty folder and use go mod init myModule to create a module. This will create a go.mod file in that folder.

Then install exalysis with this command:

go install github.com/exercism/exalysis/cmd/exalysis

This will build and place the executable in your $GOPATH/bin directory which is usually $HOME/go/bin. Add this directory to the $PATH environment variable to be able to use exalysis (and other go tools) from anywhere.

Usage

Watch mode

To start Exalysis in watch mode, run this command:

exalysis -watch

When you copy an Exercism download command to the clipboard, Exalysis will detect this and do the following:

  • Download exercise and run tests, lint checks, and so on
  • Analyse the code and make suggestions for improvement

The output of Exalysis is automatically copied to the clipboard, so all you need to do is paste into the comment box on the Exercism site and review your answer.

Single exercise examination

With no arguments, the exalysis command will analyse the solution in the current directory and write its suggestions to the standard output.

exalysis

Features

  • Auto-detect the exercise from the package name and the student's name from the current path.
  • Run a list of tools to check the code and output the result. See supported tools below.
  • Check supported exercises for special patterns and create todos, suggestions and comments based on that.
  • Sometimes adds an entire block packed with knowledge about a certain topic.
  • Outputs a complete answer ready to be pasted into Exercism. The answer is already in the clipboard when the tool finishes.
  • Provides a suggestion to the mentor whether to approve or not.

Tools

Exalysis runs the following tools on each solution:

  • golint
  • gofmt
  • go test
  • go test -race (for exercises involving concurrency)
  • go vet
  • golangci-lint
  • go test -bench (when run with the -bench flag)

My Typical Workflow

  1. Start exalysis in -watch mode.
  2. Split screen 2/3 Exercism, 1/3 terminal.
  3. Filter Exercism by a certain exercise. For me mentoring the same exercise a few times is much more effective then constantly switching contexts.
  4. Start mentoring a solution and copy the download command.
  5. Wait for Exalysis to run on in the terminal. It will put the answer to be pasted in the clipboard.
  6. Paste the answer to the student on Exercism and validate what it says against the student's solution.
  7. Adjust the answer and submit/approve.

Warning! The tool is not to be used without examining the code and trying to figure out how to best help the student. The output should not be used without checking it! There might be false positives or missing suggestions or simply too much information for the student to handle at once.

Contribution

Any contribution is welcome as long as it complies with the code of conduct of Exercism and the mentoring guidelines.

  • You can open an issue if you find a false positive that you think will happen more than once and should be fixed. The same with suggestions you think are missing.

  • One very simple way to contribute is to add samples for a case that is not covered yet, add the comment that should be shown to the student and add a test for it. That could be done for an already supported exercise or one that is not supported yet. The existing test structure is a good sample.

  • There are still many exercises to be implemented. If you're up for implementing a new exercise, that would be much appreciated.

Discussion

There's a channel on the Exercism Team Slack for discussion, development, and questions about Exalysis: #track-go-exalysis.

If you're not already on this Slack, email [email protected] to request an invite.

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