TY - GEN
T1 - Model-based Player Experience Testing with Emotion Pattern Verification
AU - Ansari, Saba Gholizadeh
AU - Prasetya, I.S.W.B.
AU - Prandi, Davide
AU - Kifetew, Fitsum Meshesha
AU - Dastani, Mehdi
AU - Dignum, Frank
AU - Keller, Gabriele
PY - 2023
Y1 - 2023
N2 - Player eXperience (PX) testing has attracted attention in the game industry as video games become more complex and widespread. Understanding players’ desires and their experience are key elements to guarantee the success of a game in the highly competitive market. Although a number of techniques have been introduced to measure the emotional aspect of the experience, automated testing of player experience still needs to be explored. This paper presents a framework for automated player experience testing by formulating emotion patterns’ requirements and utilizing a computational model of players’ emotions developed based on a psychological theory of emotions along with a model-based testing approach for test suite generation. We evaluate the strength of our framework by performing mutation test. The paper also evaluates the performance of a search-based generated test suite and LTL model checking-based test suite in revealing various variations of temporal and spatial emotion patterns. Results show the contribution of both algorithms in generating complementary test cases for revealing various emotions in different locations of a game level.
AB - Player eXperience (PX) testing has attracted attention in the game industry as video games become more complex and widespread. Understanding players’ desires and their experience are key elements to guarantee the success of a game in the highly competitive market. Although a number of techniques have been introduced to measure the emotional aspect of the experience, automated testing of player experience still needs to be explored. This paper presents a framework for automated player experience testing by formulating emotion patterns’ requirements and utilizing a computational model of players’ emotions developed based on a psychological theory of emotions along with a model-based testing approach for test suite generation. We evaluate the strength of our framework by performing mutation test. The paper also evaluates the performance of a search-based generated test suite and LTL model checking-based test suite in revealing various variations of temporal and spatial emotion patterns. Results show the contribution of both algorithms in generating complementary test cases for revealing various emotions in different locations of a game level.
UR - http://www.scopus.com/inward/record.url?scp=85161368617&partnerID=8YFLogxK
U2 - 10.1007/978-3-031-30826-0_9
DO - 10.1007/978-3-031-30826-0_9
M3 - Conference contribution
SN - 9783031308253
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 151
EP - 172
BT - Fundamental Approaches to Software Engineering - 26th International Conference, FASE 2023, Held as Part of the European Joint Conferences on Theory and Practice of Software, ETAPS 2023, Proceedings
A2 - Lambers, L.
A2 - Uchitel, S.
PB - Springer Science and Business Media Deutschland GmbH
T2 - 26th International Conference on Fundamental Approaches to Software Engineering, FASE 2023, held as part of the 26th European Joint Conferences on Theory and Practice of Software, ETAPS 2023
Y2 - 22 April 2023 through 27 April 2023
ER -