Setup your environment

You will need to set up an appropriate coding environment on whatever computer you expect to use for this assignment. Minimally, you should install:

• git
• Python(version 3.8 or higher)
• Pytest if you want to test locally

rest will be ideally installed by the build.sbt in this project when you do sbt compile or sbt test.

Check out a new branch

Before you start editing any code, you will need to create a new branch in your GitHub repository to hold your work.

1. Go to the repository that GitHub Classroom created for you. You should have received an email/link and you are most probably reading this there. It should look like https://github.com/cs4583spring2019/scala-hw3-<your-username>, where <your-username> is your GitHub username. Create a branch through the GitHub interface.
2. Name your <branch> as lastname_firstname_dev
3. Clone the repository to your local machine and checkout the branch you just created. Your command must be similar to :

   git clone -b <branch> https://github.com/cs4583spring2019/scala-hw3-<your-username>.git
   

Write your code

You will implement one function each for each of the 4 qns, Eg:runQ13a() inside the class QueryEngine. These functions should return the documents in the right order (atleast the top 2) , as asked in the question, as Lucene Documents. A sample return function is also provided for your reference.

Also, you should not edit these files:

• runAllTests.sh
• .travis.yml
• src/test/resources/input.txt
• src/test/scala/edu/arizona/cs/QueryEngineTest.scala

Note: The file src/test/resources/input.txt is the input file you must use (or would have started using) as per hw3 guidelines. Please don't edit it or move it.

Also don’t modify the signature of these functions/classes:

Eg:

class QueryEngineTest extends FunSuite{
  test("QueryEngine.Q1") {

TL;DR: If you have already started coding, your code should have ideally been returning Lucene documents as results. Now all you have to do is return your results via the respective runQ1* functions.

Test your code

Tests have been provided for you in the src/test/scala/edu/arizona/cs/QueryEngineTest.scala file. To run all the provided tests, run the sbt test script from the directory containing build.sbt

If your code passes the test case, you will see output like:

[info] Loading project definition from /Users/mordor/teaching_for_grading/hw3_qn1_stub_scala_version/project
[info] Loading settings for project hw3_qn1_stub_scala_version from build.sbt ...
[info] Set current project to hw3_scala (in build file:/Users/mordor/teaching_for_grading/hw3_qn1_stub_scala_version/)
[info] QueryEngineTest:
[info] - QueryEngine.Q1
[info] - QueryEngine.Q13a
[info] - QueryEngine.Q13b
[info] - QueryEngine.Q13c
[info] Run completed in 804 milliseconds.
[info] Total number of tests run: 4
[info] Suites: completed 1, aborted 0
[info] Tests: succeeded 4, failed 0, canceled 0, ignored 0, pending 0
[info] All tests passed.
[success] Total time: 5 s, completed Mar 13, 2019, 8:38:34 PM

Submitting your code

As you are working on the code, you should regularly git commit to save your current changes locally and git push to push all saved changes to the remote repository on GitHub.

To submit your assignment, create a pull request on GitHub. where the "base" branch is "master", and the "compare" branch is the branch you created at the beginning of this assignment. Then go to the "Files changed" tab, and make sure that all your changes look as you would expect them to. There are test cases that will be run automatically (via., travis) when a pull request is submitted. These are the same as sbt test. So if your code passed sbt test in your machine, it’s highly likely that it will pass in github. Nevertheless you should make sure that you see a green tick mark or a message saying “All Checks Have Passed”. Else close the pull request, fix the errors, and raise another pull request. Do not merge the pull request.

Your instructor will grade the code of this pull request. Pull requests submitted after the deadline won’t be considered.

Grading

Qn1 of this assignment will be graded primarily on their ability to pass the tests that have been provided to you on github after the pull request. Assignments that pass all, and with the corresponding code implementing the correct logic, will receive at least 90% of the possible points.

To get the remaining of the points, the scores you return for all the documents will be checked.