Navigating Complexity: How Context Shapes Debugging Strategy Choices among Expert Developers

Debugging is a central yet cognitively demanding part of software development, requiring problem-solving skills, expertise, and appropriate tools. Prior work has documented a variety of debugging strategies—such as hypothesis testing, simplification, and forward or backward reasoning—as well as individual factors that influence their use. However, we still lack an integrated understanding of how expert developers select and adapt these strategies in response to changing contextual factors during real-world challenging debugging. In this paper, we conducted a three-phase study: we first synthesized prior work on challenging debugging contexts, then used a short survey of 35 web developers to surface up-to-date examples of difficult defects, and finally conducted semi-structured interviews with 16 expert web developers to understand how they select and adapt strategies in these contexts. We identified a taxonomy of static and dynamic contextual factors that shape strategy selection. Dynamic factors can evolve during debugging and prompt strategy transitions, whereas static factors provide relatively stable constraints on developers’ choices. We also present a descriptive state-transition model showing how experts adapt strategies as contextual conditions like clarity, reproducibility, and constraints evolve during a debugging scenario. Our findings highlight the need for more contextual design of debugging tools as well as educational decision-making frameworks for choosing effective strategies.