class: center, middle # TDD, CI, Pairing, and Web Servers __CS291A__ Dr. Bryce Boe October 10, 2017 --- # Today's Agenda * TODO * [Finish Agile Lecture](/slides/2017/03_html_css_agile/#26) * Agile Review * Test Driven Development * Continuous Integration * Github Workflow * Pair Programming --- # TO-DO ## Should be done: * Chapters 1, 2, 9-11 in [HPBN](https://hpbn.co/primer-on-latency-and-bandwidth/) / Chapter 1 in the [Ruby on Rails Tutorial](https://www.railstutorial.org/book/beginning) ## Before Thursday's Lab: * Complete Chapters 2 through 6 in the [Ruby on Rails Tutorial](https://www.railstutorial.org/book/toy_app) * Learn [git](http://rogerdudler.github.io/git-guide/) * Your team's github should have a single-controller app and a README with project description, and team member photos. --- # Agile Review > ## Sprint 2: Starts October 12 > * Conduct a __retrospective__ on how the last sprint went and how your group > can improve. > * Decide on a sprint commitment. > * Implement stories from the current sprint. --- # Test Driven Development Assume we have a large group of software engineers working on the same project. Every day, each engineer makes many changes to the project. Human error is common and information is not global. Errors will happen. -- > How do we discover when errors occur? --- # Discovering Errors * Humans can be used to check for defects, but this is expensive. * Type systems and compilers work well to statically check for defects, but can only discover certain classes of errors. * Formal verification tools exist, but are not widely used in industry. * Automated testing --- # Automated testing... * ... is writing testing code to execute your production code and make assertions about how it should behave. * ... can be measured by code coverage tools that determine which code paths are executed by your tests. * ... allows you to build large and complex systems with very permissive languages. * For a dynamically typed language like Ruby, automated testing can make up for the lack of static checks normally done by a compiler. --- # Automated Testing: How? __If automated testing is important and we want significant code coverage (not necessarily 100%), how do we get there?__ * Don't write any production code, until there is test code that tests the desired functionality. * Write the minimal amount of production code to make the test(s) pass. -- ## Steps 1. Write the test and observe a failure (__red__) 2. Write the production code and observe a pass (__green__) 3. Clean up your design of both the code and tests (__refactor__) --- # TDD Example: FizzBuzz * If the argument is divisible by three, return "Fizz" * If the argument is divisible by five, return "Buzz" * If the argument is divisible by both return "FizzBuzz" * Otherwise return the argument --- # Test Fizz (red) ## Test ```ruby def test_divisible_by_3 assert_equal 'Fizz', fizzbuzz(3) end ``` -- ## Program ```ruby def fizzbuzz(n) # test_divisible_by_3 fails end ``` --- # Test Fizz (green) ## Test ```ruby def test_divisible_by_3 assert_equal 'Fizz', fizzbuzz(3) end ``` ## Program ```ruby def fizzbuzz(n) 'Fizz' # test_divisible_by_3 passes end ``` --- # Test Buzz (red) ## Test ```ruby def test_divisible_by_5 assert_equal 'Buzz', fizzbuzz(5) end ``` -- ## Program ```ruby def fizzbuzz(n) 'Fizz' # test_divisible_by_3 passes # test_divisible_by_5 fails end ``` --- # Test Buzz (green) ## Test ```ruby def test_divisible_by_5 assert_equal 'Buzz', fizzbuzz(5) end ``` ## Program ```ruby def fizzbuzz(n) if n % 3 == 0 'Fizz' else 'Buzz' end # test_divisible_by_3 passes # test_divisible_by_5 passes end ``` --- # Test FizzBuzz (red) ## Test ```ruby def test_divisible_by_both assert_equal 'FizzBuzz', fizzbuzz(15) end ``` -- ## Program ```ruby def fizzbuzz(n) if n % 3 == 0 'Fizz' else 'Buzz' end # test_divisible_by_3 passes # test_divisible_by_5 passes # test_divisible_by_both fails end ``` --- # Test FizzBuzz (green) ## Test ```ruby def test_divisible_by_both assert_equal 'FizzBuzz', fizzbuzz(15) end ``` ## Program ```ruby def fizzbuzz(n) if n % 3 == 0 if n % 5 == 0 'FizzBuzz' else 'Fizz' end else 'Buzz' end # test_divisible_by_3 passes # test_divisible_by_5 passes # test_divisible_by_both passes end ``` --- # Test Other (red) ## Test ```ruby def test_divisible_by_neither assert_equal 17, fizzbuzz(17) end ``` -- ## Program ```ruby def fizzbuzz(n) if n % 3 == 0 if n % 5 == 0 'FizzBuzz' else 'Fizz' end else 'Buzz' end # test_divisible_by_3 passes # test_divisible_by_5 passes # test_divisible_by_both passes # test_divisible_by_neither fails end ``` --- # Test Other (green) ## Program ```ruby def fizzbuzz(n) if n % 3 == 0 if n % 5 == 0 'FizzBuzz' else 'Fizz' end elsif n % 5 == 0 'Buzz' else n end # test_divisible_by_3 passes # test_divisible_by_5 passes # test_divisible_by_both passes # test_divisible_by_neither passes end ``` --- # FizzBuzz Refactor ## Program ```ruby def fizzbuzz(n) if n % 15 == 0 'FizzBuzz' elsif n % 3 == 0 'Fizz' elsif n % 5 == 0 'Buzz' else n end # test_divisible_by_3 passes # test_divisible_by_5 passes # test_divisible_by_both passes # test_divisible_by_neither passes end ``` --- # Types of Tests The previous FizzBuzz example demonstrated __unit__ tests. Other types of tests are: * Functional * Integration * System * Acceptance Whenever you discover a bug, the first thing you _should_ do is write a test that demonstrates the failure caused by the bug. Then fix the code and observe it passing. Building this set of tests helps prevent the introduction of a _regression_. --- # Testing Pyramid .center[![Test Pyramid](test-pyramid.png)] There should be signficantly more unit tests than higher-level tests. Source: https://martinfowler.com/bliki/TestPyramid.html --- # TDD Encouragement When working on your projects I strongly recommend that you begin by trying out test driven development. High test coverage can help you avoid getting stuck on bugs, which is even more important as more people are working on the same code. Your grade does not depend on your code coverage, however, significant code coverage will help to ensure a bug is not introduced prior to your team's presentation (that would impact your grade). It should also help reduce the time to __integrate__ feature branch changes. --- # Integration Taking independently developed changes and reconciling their conflicts. Integration can be very difficult and painful. > Should we perform integration as rarely as possible or as frequently as > possible? --- # Martin Fowler .left-column40[ .center[ ![Martin Fowler](martin_fowler.jpg) Chief Scientist, ThoughtWorks ] ] .right-column60[ > The effort of integration is exponentially proportional to the amount of time between integrations.] --- # Reconcile Early and Often If we never let our changes diverge too much from the rest of the group, reconciling our changes will never be too hard. __Conclusion__: commit early and often, and merge others' changes early and often > How do we ensure we have successfully reconciled? --- # Continuous Integration __Automated Tests!__ Utilize a __Continuous Integration__ server (CI) that will monitor changes to your source code. Whenever anyone checks in new code, run all the tests. * The sooner you find and fix integration problems, the better. * This also prevents defects unrelated to integration. The CI server can also test code quality and security, among other things. --- # CI via TeamCity .center[![APM Bundle Trunk Team City CI](apm_bundle_ci.png)] --- # CI via Travis CI .center[![Rails Travis CI](rails_ci.png)] --- # Travis CI You will configure your projects to use Travis CI: [https://travis-ci.org/](https://travis-ci.org/) Travis CI is free for open-source projects. If you are doing TDD and creating automated tests, Travis CI will provide you with immediate feedback on your changes through GitHub: .center[![Github Pull Request "All is well"](github_pr_all_is_well.png)] --- # Other Related Tools ## Coveralls Web service that provides view into code coverage that occurs during the testing phase. Integrates with github and Travis ci and can be configured to _fail_ pull requests that decrease code coverage. https://coveralls.io/ Free for open source projects. ## Rubocop A static analysis tool for ruby that suggests source code improvements encompassing code style, unused variables, visually ambiguous statements, and more. https://github.com/bbatsov/rubocop --- # Workflow We know that we do not want our changes to diverge too far from the rest of the group. > What's the right way to use our source control system to accomplish this > goal? There are two popular git-based workflow systems: * [Git-flow](http://nvie.com/posts/a-successful-git-branching-model/) * [GitHub Flow](https://guides.github.com/introduction/flow/) GitHub Flow is simpler and recommended for this class. --- # GitHub Flow 1. Ensure your master branch is up-to-date with the remote (often called `origin`) 2. Create a new branch for your feature (often called a `feature branch`) 3. Make regular [atomic commits](https://www.freshconsulting.com/atomic-commits/) to the feature branch 4. Regularly push your local changes to the remote branch on github 5. Open a github pull request when the work on the feature branch is complete 6. Have a group member perform a _code review_ of your changes 7. If there are issues to address from _code review_, complete them 8. If there are test failures (you've set up a CI system, right?) fix them 9. Merge the branch to master when everything is good-to-go __Note__: We neglected the _deploy_ phase just prior to merging. --- # GitHub Flow Commands ## Ensure your master branch is up-to-date with the remote ```bash git pull ``` ## Create a new branch for your feature ```bash git checkout -b feature_name ``` ## Commit to the feature branch regularly ```bash git add [files...] git commit -m "Add a brief useful description of changes" ``` ## Push local changes to the remote ``` bash git push -u origin HEAD ``` --- # Integration with Git Recall what we want to reconcile our changes regularly. Feature branches should be no more than a day or two out-of-sync with their parent branch. If you want to reconcile your changes without merging to master, a __git rebase__ is very useful: ```bash git rebase master feature_branch ``` .center[![git rebase](git_rebase.png)] --- # Git Interactive Rebase .left-column40[ If you have been committing frequently and want to squash some commits, consider an interactive rebase: ```bash git rebase -i master ``` ] .right-column60[ .center[![git interactive rebase](git_interactive_rebase.png)] ] --- # Pair Programming .left-column[ .center[![Pair programming](pair_programming.png)] Two developers share one computer and discuss all code that is being written. ] .right-column[ ### Driver-Navigator One person does most of the implementation while the other watches, discusses, thinks of consequences, and looks forward. ### Ping-pong pairing One person writes the test, the other makes it pass. This approach is frequently used while learning TDD and pair programming. In both approaches, pairs should regularly switch roles (e.g., every twenty minutes). ] --- # Pairing: Problem Complexity .center[![pairing usefulness as a function of problem complexity](pairing_and_problem_complexity.png)] Source: Dr. Andrew Mutz --- # Pairing: Expertise Disparity .center[![pairing usefulness as a function of expertise_disparity](pairing_and_expertise_disparity.png)] Source: Dr. Andrew Mutz --- # Pairing: Code Reading .center[![pairing usefulness as a function of amount of time spent reading code](pairing_and_code_reading.png)] Source: Dr. Andrew Mutz --- # Pairing in this class Pair programming is __strongly__ encouraged, but not required. When you pair you will inevitably experience more of your project. This means you can claim you worked on that component in an interview, and as a result should be able to sufficiently explain what was done. On the other hand, it is possible for there to be bad pairings among your group. If you don't feel it is working out, then simply don't do it.