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Uma das principais dificuldades no processo de design de um jogo está em realizar o balanceamento de seus elementos de modo a deixar os jogadores imersos durante o gameplay. Essa dificuldade está diretamente associada em equilibrar a habilidade do jogador aos elementos de gameplay, o que não é uma tarefa simples considerando a enorme variedade de gêneros de jogos e suas características distintas. Visto isso, este artigo tem por objetivo realizar uma revisão rápida da literatura (RRL) com o intuito de investigar estudos sobre o balanceamento de elementos estéticos e dinâmicos em jogos do gênero ação, estratégia, RPG e simulação. A execução do RRL retornou 150 estudos, porém, após serem submetidos a critérios de inclusão e exclusão, apenas 14 foram aceitos. Como resultado, observou-se contextos, técnicas e métodos de balanceamento, sobretudo muito relacionados a mecânicas de jogo. Isso, foi interpretado como oportunidades de investigação futuras sobre o balanceamento de elementos estéticos e mecânicos, contribuindo assim, com avanços no estudo em game design.
The HTML5 is used to display high quality graphics in web applications such as web games (i.e., games). However, automatically testing games is not possible with existing web testing techniques and tools, and manual testing is laborious. Many widely used web testing tools rely on the Document Object Model (DOM) to drive web test automation, but the contents of the are not represented in the DOM. The main alternative approach, snapshot testing, involves comparing oracle snapshot images with test-time snapshot images using an image similarity metric to catch visual bugs, i.e., bugs in the graphics of the web application. However, creating and maintaining oracle snapshot images for games is onerous, defeating the purpose of test automation. In this paper, we present a novel approach to automatically detect visual bugs in games. By leveraging an internal representation of objects on the , we decompose snapshot images into a set of object images, each of which is compared with a respective oracle asset (e.g., a sprite) using four similarity metrics: percentage overlap, mean squared error, structural similarity, and embedding similarity. We evaluate our approach by injecting 24 visual bugs into a custom game, and find that our approach achieves an accuracy of 100%, compared to an accuracy of 44.6% with traditional snapshot testing. CCS CONCEPTS• Software and its engineering → Software testing and debugging.
Gameplay videos contain rich information about how players interact with the game and how the game responds. Sharing gameplay videos on social media platforms, such as Reddit, has become a common practice for many players. Often, players will share gameplay videos that showcase video game bugs. Such gameplay videos are software artifacts that can be utilized for game testing, as they provide insight for bug analysis. Although large repositories of gameplay videos exist, parsing and mining them in an effective and structured fashion has still remained a big challenge. In this paper, we propose a search method that accepts any English text query as input to retrieve relevant videos from large repositories of gameplay videos. Our approach does not rely on any external information (such as video metadata); it works solely based on the content of the video. By leveraging the zero-shot transfer capabilities of the Contrastive Language-Image Pre-Training (CLIP) model, our approach does not require any data labeling or training. To evaluate our approach, we present the GamePhysics dataset consisting of 26,954 videos from 1,873 games, that were collected from the GamePhysics section on the Reddit website. Our approach shows promising results in our extensive analysis of simple queries, compound queries, and bug queries, indicating that our approach is useful for object and event detection in gameplay videos. An example application of our approach is as a gameplay video search engine to aid in reproducing video game bugs. Please visit the following link for the code and the data: https://asgaardlab.github.io/CLIPxGamePhysics/ CCS CONCEPTS• Software and its engineering → Software testing and debugging.
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