• Title/Summary/Keyword: Multiplayer online game testing

Search Result 2, Processing Time 0.02 seconds

Blackbox and Scenario-Based Testing of Online Games Using Game Description Language

  • Cho, Chang-Sik;Lee, Dong-Chun;Sohn, Kang-Min;Park, Chang-Joon;Kang, Ji-Hoon
    • ETRI Journal
    • /
    • v.33 no.3
    • /
    • pp.470-473
    • /
    • 2011
  • In this letter, we propose blackbox and scenario-based testing of multiplayer online games as well as simple load testing. Game testing is done from outside the source code, and the access to the source code is not required to testers because the game logic is described with a game description language and virtual game map. Instead of using a subset of the main game client for the test client, only game packet protocols and the sequence of packets are analyzed for new game testing. In addition, complex and various scenarios can be tested through combining defined actions. Scenario-based testing helps testers mimic real testing environments instead of doing simple load testing and improves the productivity of game testing.

Analytical Evaluation Model of the Gameplay in MMO Game - Focused on GOMS Model - (MMO 게임의 게임플레이 분석적 평가 모형 - GOMS 모형을 중심으로 -)

  • Song, Seung-Keun
    • Journal of Korea Multimedia Society
    • /
    • v.12 no.11
    • /
    • pp.1652-1660
    • /
    • 2009
  • The main objective of this research is to build a behavior prediction model of gameplay for MMO (Massively Multiplayer Online) game using the GOMS analysis method. GOMS analysis is an observational approach to HCI(Human Computer Interaction) to model and predict behaviors of a human operator in a highly interactive task. In this research, a pilot experiment was previously conducted with three skilled gamers. The gamers were provided with the goals and operators through the user's guide book, and they found methods and selection rules while being observed. Based on the results obtained from the pilot study, this research was expanded and the model was further tested with 30 subjects (game experts). The new outcomes revealed that the relevance of GOMS analysis for predicting selection rules is 96.25% according to the degree of abstraction and 77.35% based on the degree of complexity. This research will provide game designers with a new testing mechanism in the early development stages, in order to improve the quality of the game product.

  • PDF