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Automated Testing of Massively Multiplayer Games: Lessons Learned from The Sims Online
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Weight	7 lb, 11 oz
SKU	GDC-03-124
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Description

Automated Testing of Massively Multiplayer Games: Lessons Learned from The Sims Online,
839

Programming, Lecture

Larry Mellon
, EA/maxis
The development and operation of massively multiplayer Persistent State Worlds has proven to be difficult. The distributed nature and scale of the target system increases the complexity of debugging the implementation, while the size, scope and constantly evolving nature of the feature set incurs a high regression cost. The Sims Online encountered stability and scalability issues early in the development cycle. To address these major cost drivers, TSO shifted to a development approach revolving around a set of automated testing tools. Portions of the TSO game client are used to assemble a test client that interacts with servers in the normal manner. A scripting system is attached to this test client at the same entry points as the GUI, using a Presentation Layer to provide a semantic abstraction of the UI’s functionality. Scripts may thus mimic a series of user actions. Remote process control and synchronization primitives add single-script control for multiple clients. A single, data-driven test client thus supports developer pre-checkin testing, QA feature regression and load testing. This paper addresses the design, implementation and fielding of such tools. The effects of introducing automated tests in the day to day development and debugging of a massively-multiplayer game are discussed, while lessons learned illustrate the issues in fielding such a tool for a large, constantly evolving distributed system.

The audience should leave with the ability to rapidly convert any Internet game client, or any single player game, into a test client with strong regression and debugging capabilities. Strategies for increasing the testability of a system via simple abstractions are presented, resulting in increased stability during fielding and lower development costs. Through both the above, the audience encounters specific examples of problems encountered and lessons learned while implementing and fielding TSO’s distributed system toolkit.

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