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

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.

Multimedia Recommendation System for Video Game Based on High-Level Visual Semantic Features

“…e existing studies can be categorized as game product recommendation [16], game development process recommendation [17], and video game recommendation to users [18]. e features used for game recommendation systems are varied; the existing work shows that the main features used for recommendations are metadata, profile expansion, textual and visual features, and ratings.…”

“…Despite this, the reported studies work on contentbased recommendations [18] or collaborative recommendations [23,24]. A systematic study was performed for a recommendation system for video game developers using the developer process and recommended a new project using previous game development experience [17]. In line with the survey reported in 2018, [25] described the importance of using multimedia features for multimedia recommendations.…”

Using Linguistic VIKOR and Fuzzy Cognitive Maps to Select Virtual Reality Games Development Project

“…Moradi et al (2018) collected relative information and applied the analytic hierarchy process (AHP) and balanced scorecard (BSC) to execute performance evaluation of the digital game industry [6]. Politowski et al (2018) designed a systematic framework to evaluate video game projects. In this framework, an algorithm rule was developed to evaluate the game based on quantitative and qualitative information [7].…”

“…Politowski et al (2018) designed a systematic framework to evaluate video game projects. In this framework, an algorithm rule was developed to evaluate the game based on quantitative and qualitative information [7]. Rumeser and Emsley (2018) built the systematic review to improve serious games application in project management [8].…”

Dataset of Video Game Development Problems

“…They concluded that the majority of the game industry uses agile instead of the waterfall method. In their next work, Politowski et al [9] used 55 postmortems to create a recommendation system for new video-game projects using previous mistakes and good practices.…”