Two Level Empirical Study of Logging Statements in Open Source Java Projects

Log statements present in source code provide important information to the software developers because they are useful in various software development activities. Most of the previous studies on logging analysis and prediction provide insights and results after analyzing only a few code constructs. In this paper, the authors perform an in-depth and large-scale analysis of logging code constructs at two levels. They answer nine research questions related to statistical and content analysis. Statistical analysis at file level reveals that fewer files consist of log statements but logged files have a greater complexity than that of non-logged files. Results show that a positive correlation exists between size and logging count of the logged files. Statistical analysis on catch-blocks show that try-blocks associated with logged catch-blocks have greater complexity than non-logged catch-blocks and the logging ratio of an exception type is project specific. Content-based analysis of catch-blocks reveals the presence of different topics in try-blocks associated with logged and non-logged catch-blocks.