Assessing Programming Difficulty and Effort: Statistical Correlations with the Index of Internal Effort
Alisson Antônio de Oliveira · 2024
Code metrics are essential variables for evaluating complexity and effort in different development contexts. However, there is a gap in comprehensive measurement of complexity and team effort. This study uses a dataset of 46 codes from the Brazilian Informatics Olympiad to investigate correlations between metrics such as difficulty, number of lines of code, cyclomatic complexity, and the Index of Internal Effort (IIE), a generic framework for measuring Explicit Intellectual Activities (EIA). Statistical results revealed positive and significant correlations among the studied metrics, including the IIE, validating its applicability as a complexity indicator. This study contributes to the understanding of perceived complexity in programming competitions, suggesting practical applications in creating more balanced challenges and managing software projects, based on a new framework as a complexity metric.