Synthesizing Program Execution Time Discrepancies in Julia Used for Scientific Software

Scientific software is defined as software that is used to analyze data to investigate unanswered research questions in the scientific community. Developers use programming languages such as Julia to build scientific software. When programming with Julia, developers experience program execution time discrepancy i.e. not obtaining desired program execution time, which hinders them to efficiently complete their tasks. The goal of this paper is to help developers in achieving desired program execution time for Julia by identifying the causes of why program execution time discrepancies happen with an empirical study of Stack Overflow posts. We conduct an empirical study with 263 Julia-related posts collected from Stack Overflow, and apply qualitative analysis on the collected 263 posts. We identify 9 categories of program execution time discrepancies for Julia, which include discrepancies related to data structures usage such as, arrays and dictionaries. We also identify 10 causes that explain why the program execution time discrepancies happen. For example, we identify program execution time discrepancy to happen when developers unnecessarily allocate memory by using array comprehension.