A Study on the Comprehensibility of Behavioral Programming Variants

Adiel Ashrov, Arnon Sturm, Achiya Elyasaf, Guy Katz

Abstract: Behavioral Programming (BP) is a software engineering paradigm for modeling and implementing complex reactive systems. BP’s goal is to enable developers to incrementally model systems in a manner naturally aligned with their perception of the system’s requirements. This study compares two BP variants: classical, context-free BP, and the more recently proposed Context-Oriented BP (COBP). While BP advocates simplicity and modularity, COBP introduces context-aware constructs for handling context-dependent behaviors. A practical question arises: which variant leads to reactive systems that are more comprehensible for developers? Through a controlled experiment with 109 participants, we evaluated both variants across two dimensions: comprehension of execution semantics and identification of requirements from implementations. The results indicate that BP generally leads to better comprehension and higher confidence; while COBP demonstrates advantages in complex, context-dependent behaviors