Game Development: Harder Than You Think
Queue - Game Development
Optimal information placement in an interactive 3D environment
Proceedings of the 2007 ACM SIGGRAPH symposium on Video games
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Understanding information observation in interactive 3D environments
Sandbox '08 Proceedings of the 2008 ACM SIGGRAPH symposium on Video games
A data mining approach to strategy prediction
CIG'09 Proceedings of the 5th international conference on Computational Intelligence and Games
Mining game statistics from web services: a World of Warcraft armory case study
Proceedings of the Fifth International Conference on the Foundations of Digital Games
Avatar movement in World of Warcraft battlegrounds
Proceedings of the 8th Annual Workshop on Network and Systems Support for Games
Proceedings of the 1st International Workshop on Games and Software Engineering
International Conference on Software Engineering
Data analytics for game development (NIER track)
Proceedings of the 33rd International Conference on Software Engineering
Mastering the art of war: how patterns of gameplay influence skill in Halo
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
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For several years empirical studies have spanned the spectrum of research from software productivity, quality, reliability, performance to human computer interaction. Analyses have involved software systems ranging from desktop software to telecommunication switching systems. But surprising there has been little work done on the emerging digital game industry, one of the fastest growing domains today. To the best of our knowledge, our work is one of the first empirical analysis of a large commercially successful game system. In this paper, we introduce an analysis of the significant user data generated in the gaming industry by using a successful game: Project Gotham Racing 4. More specifically, due to the increasing ubiquity of constantly connected high-speed internet connections for game consoles, developers are able to collect extensive amounts of data about their games following release. The challenge now is to make sense of that data, and from it be able to make recommendations to developers. This paper presents an empirical case study analyzing the data collected from a released game over a three year period. The results of this analysis include a better understanding of the differences between long-term and short-term players, and the extent to which various options in the game are utilized. This led to recommendations for future development ways to reduce development costs and to keep new players engaged. A secondary goal for this paper is to introduce software game development as a topic of importance to the empirical software engineering community and discuss research results on a key difference area: data analytics on user data to customize user and development experiences.