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Evaluating programming proficiency has become more relevant as the demand for coding skills has increased. Current methods, such as questionnaires or interviews, are methods that lack intuition, flexibility, and real-time capabilities. In our work, we investigate eye gaze behavior as an estimate for skill assessment. Specifically, we conducted a study (N=14) using an eye tracker to analyze the participants' abilities to understand source code by presenting them with a series of programs. Wedoi:10.1145/3205873.3210702 dblp:conf/perdis/LiangKK018 fatcat:jyfq5oobvzhb3dpznxae2w63pi