TY - GEN
T1 - Regression Testing of Massively Multiplayer Online Role-Playing Games
AU - Wu, Yuechen
AU - Chen, Yingfeng
AU - Xie, Xiaofei
AU - Yu, Bing
AU - Fan, Changjie
AU - Ma, Lei
N1 - Funding Information:
ACKNOWLEDGMENTS This work was supported in part by JSPS KAKENHI Grant No. 20H04168, 19K24348, 19H04086, and JST-Mirai Program Grant No. JPMJMI18BB of Japan.
PY - 2020/9
Y1 - 2020/9
N2 - Regression testing aims to check the functionality consistency during software evolution. Although general regression testing has been extensively studied, regression testing in the context of video games, especially Massively Multiplayer Online Role-Playing Games (MMORPGs), is largely untouched so far. One big challenge is that game testing requires a certain level of intelligence in generating suitable action sequences among the huge search space, to accomplish complex tasks in the MMORPG. Existing game testing mainly relies on either the manual playing or manual scripting, which are labor-intensive and time-consuming. Even worse, it is often unable to satisfy the frequent industrial game evolution. The recent process in machine learning brings new opportunities for automatic game playing and testing. In this paper, we propose a reinforcement learning-based regression testing technique that explores differential behaviors between multiple versions of an MMORPGs such that the potential regression bugs could be detected. The preliminary evaluation on real industrial MMORPGs demonstrates the promising of our technique.
AB - Regression testing aims to check the functionality consistency during software evolution. Although general regression testing has been extensively studied, regression testing in the context of video games, especially Massively Multiplayer Online Role-Playing Games (MMORPGs), is largely untouched so far. One big challenge is that game testing requires a certain level of intelligence in generating suitable action sequences among the huge search space, to accomplish complex tasks in the MMORPG. Existing game testing mainly relies on either the manual playing or manual scripting, which are labor-intensive and time-consuming. Even worse, it is often unable to satisfy the frequent industrial game evolution. The recent process in machine learning brings new opportunities for automatic game playing and testing. In this paper, we propose a reinforcement learning-based regression testing technique that explores differential behaviors between multiple versions of an MMORPGs such that the potential regression bugs could be detected. The preliminary evaluation on real industrial MMORPGs demonstrates the promising of our technique.
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U2 - 10.1109/ICSME46990.2020.00074
DO - 10.1109/ICSME46990.2020.00074
M3 - Conference contribution
AN - SCOPUS:85096637365
T3 - Proceedings - 2020 IEEE International Conference on Software Maintenance and Evolution, ICSME 2020
SP - 692
EP - 696
BT - Proceedings - 2020 IEEE International Conference on Software Maintenance and Evolution, ICSME 2020
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 36th IEEE International Conference on Software Maintenance and Evolution, ICSME 2020
Y2 - 27 September 2020 through 3 October 2020
ER -