A blank Star Battle puzzle.
You can try this puzzle online.
In a Star Battle puzzle, a n×n grid is divided into n regions. To solve the puzzle, the player must find a placement of 2n stars such that each row, each column, and each region of the puzzle has exactly 2 stars, and no stars are vertically, horizontally, or diagonally adjacent. Other size variations are possible, but we’ll use 10×10 2-star puzzles for this project. We will also assume that valid puzzles have a single unique solution.
This logic puzzle was designed by Hans Eendebak in 2003. You can search the web for many more examples. Here is a site by Jim Bumgardner with tutorials, a web app, and pages and pages of Star Battle puzzle PDFs.
In this project, your group will construct a system that sends puzzles over the network and provides a graphical user interface for players to solve them.
The project will exercise many of the concepts you learned in class. You will implement a client/server architecture; you will use ParserLib to parse puzzles; and you will develop your own abstract data types to represent different aspects of the system. Most importantly, you will also practice working in a small group, using the software engineering techniques we have learned this semester.
On this project, you have significant design freedom to choose the interfaces, classes, and method signatures you use in your code.
Choose them wisely.
You will be expected to use specs, tests, abstraction functions, rep invariants, safety arguments,
checkRep and other assertions.
The specification in this handout constrains what your solution must do, but you will have many design questions that are not answered in this handout. You are free to come up with your own answers to these questions – just be reasonable, consistent, safe from bugs, easy to understand, and ready for change. You can always ask your TA mentor or on Piazza for advice, but there is unlikely to be a single hard-and-fast answer.
One member of your team should ask Didit to create a remote
projects/starbrepository, which will create a single repository shared by all members of your team.
Then all team members will be able to go to Didit, follow the link to your team repo page, and find the
git clonecommand at top. Clone,
npm install, and open in VS Code.
For several pieces of the project, two team members will independently do that piece, resulting in two different designs in iteration #0. The third member of the group will then be responsible for iterating on those designs and taking the next step on that part of the project in iteration #1. These tasks will be described in detail below.
Your team will be assigned a TA mentor who will help you with your design and help you stay on track as you implement it. You are required to check in with your TA during every team work time class. At this check-in, each team member should be prepared to:
- say what they have accomplished since the last check-in
- say what they plan to accomplish by the next check-in
- say what, if anything, is blocking their progress
- show that their own working copy of the project is committed, pushed, and up to date with the remote repo
Other than reflections at the end of the project, all parts of the project should be committed to the repository you share. Each commit to the repository should have a useful commit message that describes what you changed.
Use the code review skills you’ve practiced on Caesar to review one another’s code during the project. Caesar won’t have your project code loaded into it, however, so you can use in-person discussion or email for these reviews. Additionally, you can leave inline comments on individual commits in the github.mit.edu web interface.
You are also strongly encouraged to try pair programming, where two people collaborate on a single computer, with one person watching over the other’s shoulder, or watching by videochat and screenshare. Pair programming is a skill that requires practice. Be patient: expect that pairing will mean you write code more slowly, because it’s like code review in real time, but the results are more correct, more clear, and more changeable. You can find plenty of advice on the Internet for how to structure your pairing.
Note that “pair programming” normally means just one keyboard, with one person driving (typing) and the other person in the backseat (code reviewing). So you are editing only one working copy, and committing the changes just once. When multiple people contribute to a commit, mention them in the commit message. Your TA will be reviewing the Git log to see individual contributions.
What we do in class with Constellation is a closer kind of collaboration than normal pair programming. Using Constellation during the project is possible but not encouraged, because it makes identical changes on two computers that require careful coordination to avoid merge conflicts. But if you really want to use Constellation, then before starting the collaboration, make sure both sides are in a clean state, with no uncommitted changes and fully in sync with the remote repo. After collaborating, both sides should commit the changes to their local repos, then push and pull until the commits are merged and both sides are again in a clean state. Note that you must be extremely disciplined to use Constellation and Git together successfully. Never walk away from a Constellation collaboration without cleaning up and getting merged.
Team contract. Before you begin, write and agree to a team contract. This is due at the end of class on the day the project kicks off.
Understand the problem. Read the project specification on this page carefully.
Your software design is perhaps the most important part of the project: a good design will make it simpler to implement and debug your system. Remember to write clear specifications for classes and methods; define abstraction functions and rep invariants, write
checkRep, and document safety from rep exposure.
Iterate. Because of the short timeframe, the specification for how to iterate on this project is given to you by the staff. Design, test, and implement each piece, always working toward an end-to-end prototype. Then revisit your designs, improve the specifications, and test and implement more. And so on.
Test. You should write Mocha tests for the individual components of your system. Your test cases should be developed in a principled way, partitioning the spaces of inputs and outputs, and your testing strategy should be documented as we’ve been doing all along. Parts of your program may require manual testing, which is described below.
Reflection. Individually, you will write a brief commentary saying what you learned from this project experience, answering the reflection questions. Your reflection may not exceed 300 words, and should be submitted to the reflection form.
The testing page describes how this works, and how to exclude tests from execution if they cannot run on Didit. You are not required to run any of your tests on Didit, but your project must compile and have a green build on Didit in order to be graded. If it doesn’t build on Didit, your TA won’t be able to build it either.
However, if there are specifications you are not sure how to test automatically, you can document manual tests that cover parts of some partitions.
Document these tests in the relevant
mocha test file immediately below the testing strategy.
For each manual test: give it a descriptive name, list the parts covered, and briefly but precisely describe each step a human tester should follow, along with assertions about expected results at each step.
/* * Manual test: navigate to academic calendar * Covers: page=home, type=static, type=redirect, data-source=registrar * 1. browse to http://web.mit.edu => assert that header contains today's date * 2. click "education" * 3. click "academic calendar" => assert that page shows previous June through next June */
It’s fine to use any code provided in this semester’s class. For example:
- Reading 12 example parser
- Reading 15 fetch examples
- Reading 18 Express examples
- Problem Set 3 starting code
- Problem Set 4 starting code
- Each group member has a directory under
iter0for their work on iteration #0, since you may have files with the same names. Commit all iteration #0 work in those directories. After iteration #0, stop committing there and use
- This file should start your server. Running
npm run serverwill compile and run this file.
- These files are your client user interface. Running
npm run watchify-clientwill compile this TypeScript file and its dependencies, and automatically recompile whenever you edit the TypeScript. Opening
starb-client.htmlin your web browser will run the code.
- Contains example Star Battle puzzle files that your system must be able to use.
kd-1-1-1.starbis the puzzle shown at the top of this handout.
- A starting point for your user interface.
npm run watchify-examplewill compile this TypeScript file, and opening
example-page.htmlin your web browser will run the code and show you what it does.
- Placeholder for project documentation. If you’re not sure your TA mentor will be able to find an iteration #0, iteration #1, or final project deliverable; or if there are instructions to run and use your project, document them here.
Since this assignment asks you to implement all the parsing, rendering, and game logic of our Star Battle puzzle system, remember that it is not appropriate to reuse any such components from an external source.
Until you have a complete working end-to-end implementation, your design freedom is limited. Items marked [for now] are requirements during iteration #0, iteration #1, and integration. Only once you have a complete working end-to-end system may you break these restrictions if it will improve your design, enable new features, etc.
You must use ParserLib.
Your client web page must use another client ADT to manage its state (for example, what puzzle is being played, using the puzzle ADT) and operations (for example, in reaction to user input). Its design is entirely up to you.
Note that clients and servers do not have shared memory, so they do not share instances of the puzzle ADT (or instances of the parser in the previous section). But you must use the same ADT type (and same parser class) in both parts of the system.
Unlike Problem Set 3, it is not required that every puzzle ADT instance (which includes partially-solved puzzles) have a parseable string representation (the parser is only required to handle “blank” and “solved”).
The client web page must: request a blank puzzle, display the puzzle on screen, allow the user to add stars anywhere on the grid, display those stars, allow the user to remove stars they have added, and inform the user if and when they have solved the puzzle.
Contributions include writing specifications, writing testing strategy, writing tests, prototyping, writing internal docs, writing implementation code, fixing bugs, and giving code review feedback. Contributions you work on as a pair or a whole team are great, as long as everyone is involved.
Because of the short timeframe for the project, the staff has specified a breakdown of tasks you must follow. The description in this section is in reverse chronological order because the assignment of tasks for iteration #1 determines who does what for iteration #0.
As team members complete their iteration #1 tasks assigned below, everyone should work together to integrate them. When you have a complete working system, revise and refactor to make it as safe from bugs, easy to understand, and ready for change as you can.
If you find that more substantial redesign is needed, plan and execute another iteration on the project. Only if you have time, consider implementing some of the extensions suggested above or ideas of your own.
Fill in names in the boxes below to plan the division of work on different modules of your system as described in the spec. Record your decisions in your team contract.
You are required to divide the work such that every team member makes several different kinds of contributions. Assign iteration #1 of these components, with two tasks per group member, such that no person is mentioned more than once in each row or column:
- Puzzle ADT
- the ADT(s) for representing puzzles on both the client and server
- parser for puzzles read from a file and sent from server to client
- HTTP server for sending puzzles to clients
- Client ADT
- the ADT(s) for representing client state
- function(s) or type(s) for drawing puzzles
- function(s) or type(s) to drive client interaction with server and user, handling user input
(That is: both group members who are not the person assigned to puzzle ADT iteration #1 above must be assigned to puzzle ADT specs + t.s. iteration #0 below; and so on. Here “t.s.” means a testing strategy that partitions inputs/outputs.)
|Puzzle ADT |
specs + t.s.:
|Web API |
|Client ADT |
specs + t.s.:
t.s. + tests:
- Puzzle ADT specs + t.s.
- specs and testing strategy for puzzle ADT (no choosing tests or implementing)
- single grammar for “blank” and “solved” puzzles (no testing or implementation)
- Web API + t.s.:
- specs for client/server communication and testing strategy (no puzzle grammar, choosing tests, or implementation)
- Client ADT specs + t.s.
- specs and testing strategy for client ADT (no choosing tests or implementing)
- Drawing prototype
- hard-coded drawing of different puzzle components (not using puzzle or client ADTs)
- Integration t.s. + tests
- plan for manual testing of entire client/server system (partitions and outline of manual test cases)
And they should be done quickly: after reading this handout and understanding the spec, spend no more than one hour on each iteration #0 task. The group member assigned to work on iteration #1 will… iterate!
Each group member should commit their iteration #0 work in the directory under
iter0 with their username: e.g.
alyssap works in
After iteration #0, leave those files where they are, and use
test/ for iteration #1 and beyond.
- For the drawing prototype: you can write the iter0 code by editing
npm run watchify-example, and viewing in
example-page.html. But don’t commit there: copy and commit your work under your username directory in
iter0, so you don’t create conflicts. Ask your TA mentor if you need advice.
At the iteration #0 check-in, everyone should have completed at least two out of four of their iteration #0 tasks, with plans to finish any remaining tasks by the end of the day. Both iteration #0 tasks for a component must be done and committed to the project repo before the team member assigned to iteration #1 of that component starts their work.
At the iteration #1 check-ins, everyone should have substantial progress on at least one (on Thu May 4) and then both (on Tue May 9) of their iteration #1 tasks, with plans to finish any remaining work by the end of the day. You should demonstrate as many individual or connected-together parts of the system as you have working.
You should have a first (or for items covered by iteration #0, second) draft of grammars, specs, automated & manual tests, data type definitions, rep invariants, abstraction functions,
toString, etc. defined where appropriate.
Remember once again that none of these things are final yet!
If you are having trouble, seek help early.
- Thu Apr 27, 9:30-11am
- Initial check-in meeting with your TA mentor. Use this opportunity to ask questions about the project specification, tasks, or schedule.
- Thu Apr 27, 11am
- (end of class)
- Your team contract must be committed to your group repository in a PDF file called
team-contract.pdfin the top level of your repo. It should clearly describe the assignment of tasks as outlined above, according to the requirements.
- Tue May 2, 9:30-11am
- Iteration #0 completion check-in meeting. You should discuss progress, plans, and blockers on iteration #0 tasks. You should aim to be done with iteration #0 by 10pm.
- Thu May 4, 9:30-11am
- Iteration #1 progress check-in meeting. You should discuss progress, plans, and blockers on iteration #1 tasks.
- Tue May 9, 9:30-11am
- Iteration #1 completion check-in meeting. You should discuss progress, plans, and blockers on iteration #1 tasks. You should aim to be done with iteration #1 by 10pm.
- Thu May 11, 9:30-11am
- Last check-in meeting with your TA mentor. You should aim to demonstrate your project working end-to-end, and discuss specific plans for any remaining work.
- Fri May 12, 10pm
- Project deadline. Your specifications, tests, and implementation should be complete and committed to your group’s repository by this deadline.
- Fri May 12, 10pm
- Reflection deadline. Individually, you should write a brief reflection and submit it using the reflection form. Your reflection should be at most 300 words of plain text.
Check-ins with your TA mentor are also graded as binary checkoffs, either passed or missed, based on whether all team members are prepared and participate in the meeting. Missing a check-in costs up to 5 points on the overall project grade. You will check in with your mentor in all five class times during the project.