#GitHub Burndown Chart ##Rework in Progress

##Next ->

[ ] Write tests to fetch open/closed issues (and save ourselves the trouble when milestone has 0 issues count)

##Project Charter

The app is to display a burndown chart from a set of GitHub issues in a milestone.

If we can, do all processing and storage on the client which makes the app run for "free" on gh-pages etc.

Show:

• Upcoming issues by size.
• Issues closed today.
• For each issue show other tags and assignee (avatar).
• Number of working days left.
• To whom open issues still belong.
• Projected ship date (project running late/not).
• For each user/avatar what is their % progress and number of open/closed issues.
• Heat: if we are struck/very productive for a period of time, colorize the chart line.
• For milestones with no due date, show an estimate as to when it will probably be finished.

Allow:

• Toggle non working days.
• Have a print view.
• Customization of the theme (own logo/colors etc.).

Configure:

• Repos for users/orgs.
• Private api keys.
• Non working days.
• Label pattern to determine size (?).
• How often to poll for updates (limited by GH API).

Be:

• Responsive.
• As lightweight as possible (do we need Backbone/jQuery?).
• Well documented and modularized.
• Handling upstream API downtimes.
• Testing the algo by way of using the proxy service to fake responses.
• Handling daylight savings et al.

Usage envisaged in these three scenarios:

1. Use the gh-pages branch of this repo to connect and visualize a public repo.
   • App requesting a static JSON config file, merging with LocalStorage.
2. Deploy the app on a static server elsewhere with custom config.
   • App requesting a static JSON config file, merging with LocalStorage.
3. Proxy requests through a service to not disclose private api keys publicly.
   • Proxy app wrapping a request with API credentials. When requesting the config file we get the file dynamically stating which URL to use to make requests. API keys are scrubbed from the JSON file. When someone makes a request to us, wrap their request (only GET requests to specific endpoints!) and pipe the response back.
   • All this works as a Connect Middleware.
   • Also, make this cache responses for a given amount of time (poll time). This way people concerned with a big amount of requests can share the same resource.

##Design

###Initialization

1. Get milestones and determine which one is ending the soonest.
2. For this milestone get both open & closed issues (can span multiple pages).
3. Filter out issues not matching our pattern. For those that do keep tally and insert them to a map of days. Keep track of issue ids of open and closed issues.
4. Determine what the average velocity per day needs to be.
5. Go from the front (milestone creation date) to the back (milestone due date) day by day.
   1. For each day that has an entry in the map, add them to the end array (for actual).
   2. For expected just keep reducing the total by velocity every day.
6. Profit.

###Poll

An issue can be re-opened so we need to keep track of changes to individual tickets. Assume that polls happen quite frequently in the day and not say once a week or something.

1. Get both open & closed tickets sorted by their created and updated in a descending order. Do not need to get all pages back to UNIX time...
2. If we have a mismatch between our previous arrays of open/closed issue ids then determine if we need to move an issue (change of state) from one group to another.