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arXiv · 2009.02445

Learning from the past: A process recommendation system for video game projects using postmortems experiences

Cristiano Politowski·Lisandra M. Fontoura·Fabio Petrillo·Yann-Gaël Guéhéneuc
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Abstract

Context: The video game industry is a billion dollar industry that faces problems in the way games are developed. One method to address these problems is using developer aid tools, such as Recommendation Systems. These tools assist developers by generating recommendations to help them perform their tasks. Objective: This article describes a systematic approach to recommend development processes for video game projects, using postmortem knowledge extraction and a model of the context of the new project, in which "postmortems" are articles written by video game developers at the end of projects, summarizing the experience of their game development team. This approach aims to provide reflections about development processes used in the game industry as well as guidance to developers to choose the most adequate process according to the contexts they're in. Method: Our approach is divided in three separate phases: in the the first phase, we manually extracted the processes from the postmortems analysis; in the second one, we created a video game context and algorithm rules for recommendation; and finally in the third phase, we evaluated the recommended processes by using quantitative and qualitative metrics, game developers feedback, and a case study by interviewing a video game development team. Contributions: This article brings three main contributions. The first describes a database of developers' experiences extracted from postmortems in the form of development processes. The second defines the main attributes that a video game project contain, which it uses to define the contexts of the project. The third describes and evaluates a recommendation system for video game projects, which uses the contexts of the projects to identify similar projects and suggest a set of activities in the form of a process.

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Cristiano Politowski, Lisandra M. Fontoura, Fabio Petrillo, Yann-Gaël Guéhéneuc. 2020-09-05. Learning from the past: A process recommendation system for video game projects using postmortems experiences. https://doi.org/10.1016/j.infsof.2018.04.003

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