This paper describes a case study of using developer activity logs as indicators of a program comprehension effort by analyzing temporal sequences of developer actions (e.g., navigation and edit actions). We analyze developer activity data spanning 109,065 events and 69 hours of work on a medium-sized industrial application. We examine potential correlations between different measures of developer activity, code change metrics and code smells to gain insight into questions that could direct future technical debt interest estimation. To gain more insights into the data, we follow our analysis with commit message analysis and a developer interview. Our results indicate that developer activity as an estimate of program comprehension effort is correlated with both change proneness and static metrics for code smells.