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    Area of Science:

    • Software Engineering
    • Human-Computer Interaction
    • Cognitive Science

    Background:

    • Developers spend significant time navigating codebases, hindering productivity.
    • Existing tools lack theoretical grounding for effective code navigation and exploration.

    Purpose of the Study:

    • To establish a unified theoretical framework for code navigation inspired by foraging theory.
    • To develop and validate a novel computational framework for assessing code foraging mechanisms.
    • To investigate the impact of software entity clustering on code foraging efficiency.

    Main Methods:

    • Applied optimal food-foraging principles to develop a code navigation theory.
    • Created a computational framework to automatically assess foraging mechanisms in program comprehension.
    • Conducted quantitative analysis on open-source projects and qualitative inquiry into developer behavior.

    Main Results:

    • Clustering of software entities was found to enrich the development environment.
    • Improved code foraging efficiency was observed due to enhanced software environments.
    • Qualitative data provided insights into actual developer navigation strategies and behaviors.

    Conclusions:

    • The proposed foraging-based theory offers a foundation for designing ecologically valid code navigation tools.
    • Computational assessment of foraging mechanisms can quantitatively evaluate navigation tool effectiveness.
    • Understanding developer foraging behavior can lead to more intuitive and efficient software development tools.