GSoC sachith500 Proposal

This page is related to Summer of Code 2014

See the list of Summer of Code 2014 Ideas

This is a Summer of Code 2014 student page

Description

Sachith Seneviratne - Multiplayer Data Analysis Proposal

Although Multiplayer games are being archived currently, no data is saved regarding the winner(s). Recording and presenting this information would allow for easier balancing and feedback for content creators. Specifically, this project will add a means by which players can indicate who won, as well as parse the saved data and store in a database as much useful information regarding the games as possible.

Deliverables

Priorities are divided among
Optional - may not get implemented, but can be a future use of having this project implemented.
High Priority - will most probably be implemented.
Critical - Will definitely be implemented.

[Critical] Provide winner of game whenever possible

• A button for players to resign with. On click, it will print "GG" in chat, and auto-quit the game.

[Critical] Provide a database with easy extensibility to support different future types that may need to be entered.

• A MySQL / SQLite database with a connector which can store generated stats.

High Priority Stats and a way for players/content creators to gain access to them.

• Set it up on a webpage.

Timeline

The timeline has been devised to get working components as soon as possible, and then to iteratively improve them to the desired level. This ensures that the deliverable are guaranteed, and the iterations allow for easier management of the work required on each individual component.

Implementation Details

This section will describe the major components as well as the design decisions and implementations which are a part of this project. The components will also be developed with maximum extensibility in mind (So that changes to WML, such as new tags etc, can be easily supported in the future). The implementation will feature a top-down approach to

Winner Detection

This deliverable shall deliver a means of identifying winners in multiplayer games.

• Step 1 : Identify winners by having players declare a winner at the end of the game.
• Step 2 : Implement advanced winner detection, specially with respect to custom games. (this will be implemented on the parser, most probably)

Data Analysis

Core Components

• WML Parser
• Database to store results of analysis

This mainly involves implementing a parser (Currently decided language is C++) as well as a database (MySQL) that stores parsed information.

Parser

The parser will target WML and attempt to derive useful information. This will involve mostly standard string processing within the tags. Certain tags like the end-level tag will be of particular interest with regards to winner detection especially for custom scenarios. The parser will be designed so as to support future tags as well as easy changes to the nature of tagging. Certain data may not need to be parsed due to already being available in-game (such as unit recruit/advancement/death information). Modules that currently do such processing could send that information to the parser.

Database

Since the database is going to be used for a lot of lookup, the current plan is to keep it sufficiently denormalised to optimize performance, while at the same time allow for enough normalisation to reduce needless redundancy.
Important: Note that columns with a "!" at the end may require further decisions as it relates to certain things like collecting player stats.

Schema

The schema is a work in progress and is subject to change over the course of the project. Below is a list of the main tables and a short description listing the expected structure and logic behind it.

• Game Table
  • Stores overall information about games (game_id,num_turns,num_players,winning_team,duration, ...)

• Player Entry table
  • Stores information regarding the performance of each individual side in a game. Note that a single player may control 2 sides of the same race,leader combination, so (Game, player, race, leader) need not necessarily form a candidate key.
  • Will include data such as game_num,player_num(!),faction,leader,gold_gathered,gold_spent,damage_dealt,damage_taken,healing_done, ...)

• Unit Table
  • This table will contain details such as, unit_name,num_recruited,num_died,num_advanced,xp,damage_dealt,healing_done, ...
  • It might also be interesting to store details on an individual unit basis (could allow for unit trait analysis), but this would probably be too much data.

Note- if the Leader Table is implemented as below, leader details would not be included in the unit table.

• Leader Table
  • Stores data about the performance by leaders in various games. This will give valuable stats about how different leaders perform on different maps,against different other factions and even other leaders.
  • This table will provide interesting insights into how leaders affect the game as a whole.

Week	Major Tasks	Subtasks
Week 1 (19-26 May)	Implement Resign Button	Implement Button for players to Press Include the player resign data in the stream to the server
Week 2 (26 May-02 June)	Basic Replay Parser	Implement support for checking for resigned players Collect some of the data that will be added to persistent storage later. Test basic functionality
Week 3 (June 2 – 9)	Set-up basic database controller, and add data generated so far into database.	Implement Database (SQL) Implement extensible design to allow for future data
Week 4 (June 9 – 16)	Set-up connectivity between all new components, test implemented functionality.	Test extensibility of the database/dbcontroller design by adding new datatypes to the parser Write a few unit tests.
Week 5 (June 16 – 23)	Implement Additional parser functionality	Add several more fields to the database and implement corresponding query mining on the server stream.
Week 6 (June 23 – 30)	Implement advanced victory detection	Implement better victory detection in addition to the resign button. Scrub code and complete documentation in expectation of mid evaluations.
Week 7 (June 30 – July 7)	Optimize Communication between server and parser.	Provide parser with only relevant data from the server data stream Implement basic aggregation views etc in preparation of providing presentable data.
Week 8 (July 7 – 14)	Scrub Code and improve parser functionality.	Implement some additional data gathering functionality in parser. Get up-to-date on documentation and tests.
Week 9 (July 14 – 21)	Start work on presenting generated results/analysis	Provide complete set of aggregation methods/ statistical analysis Provide access to stats a few stats on a webpage (basic victory stats)
Week 10 (July 21 – 28)	Provide more details on webpage	Add era-wise,race-wise analysis of results Add capabilities for custom queries
Week 11 (July 28 – August 4)	Add additional features to parser/database to check extensibility	Add a few more fields to check how extensible system is Improve extensibility further
Week 12 (August 4 – 11)	Scrub all code and complete testing/documentation	Add a few more fields to check how extensible system is Improve extensibility further

About Me

Hello everyone! I'm a 22 year old guy studying Computer Science and Engineering at the University of Moratuwa, Sri Lanka. This is my first year taking part in GSoC and I definitely intend to take part in it next year as well. If you wish to contact me I hope the following details will be sufficient. Please feel free to leave me any feedback regarding this proposal, or anything else! :D

IRC

sachith500

Email

sachith500@gmail.com

Github

https://github.com/sachith500

Experience

I've worked on a number of projects in various languages. I've compiled a small collection of them that is relevant to this project here.

Programming Contests

Language used: C++
I have about 5 years of experience with programming contests. I've listed links to my profiles below.

Topcoder

Language : C++

Codeforces

Language : C++

Project Euler

Language : C++

Robotgame AI game

Language : Python

Google AI Challenge 2010

Language : Java

Decision Support System for SoilTech

• PHP
• MySQL

Customer Managing DBMS

Database Management System that uses MySQL for storing as well as controlling access to customer information.

• PHP
• MySQL
• Symfony2
• Doctrine

DiscoverLanka -Maching Learning, Query Mining Android App

A Location based, context aware app that employs query mining using an ontology database in order to learn about users as well as the places they are interested in visiting.

Technologies used:

• Android

Contribution to Wesnoth

Patches

I started work on Wesnoth even before it got officially selected for GSoC :D Description is colour coded by acceptance status.
GREEN indicates the patch was accepted.
RED indicates the patch is pending approval.

Bug#	Description	Submission Date
#21358	Help link for special ability plague was not linking back to the units	2014.02.15
#21486	Team labels were clearing non-team labels on the map	2014.02.14

Brainstorm

THIS SECTION WILL BE REMOVED FOR THE FINAL PROPOSAL. This section is just used for brainstorming various half formed ideas, so they can be iterated upon.

1. Add this information to archive.

• Possible Cases to consider
  1. Everyone disconnects : no clear winner.
  2. All leaders on all sides except one are dead : Side with leaders remaining win.
  3. All players except 1 disconnect : TODO- Decide if game is still multiplayer

• At the end of the game, attempt to identify the winner using available information.
• Current work plan :
  1. Implement very basic winner detection.
  2. Implement some basic database features.
  3. Repeat until satisfactory.

A suitable database connector would be incorporated into the wml parser to allow for saving of collected data into a database (MySQL perhaps?). A separate class could then be used in conjunction with the connector to provide an extensible design for the database. [High Priority] Provide stats regarding game, (units used, advancements made etc)
[Optional] Provide stats on the pages of units.wesnoth.org. eg:- http://units.wesnoth.org/1.10/mainline/en_US/Vampire%20Bat.html could have stats on vampire bats, % appearing in games, of those offer a breakdown of how many (1,2,3 bats etc). How many advancements etc.