The Programmer's Brain

Programming relies on the interplay of long-term memory, short-term memory, and working memory to store, recall, and process information while coding. [1] [2]

The Cognitive Dimensions of Codebases (CDCB) framework evaluates codebases from a cognitive perspective, helping identify how design decisions impact understandability and developer productivity. [1] [2]

Working memory is crucial for processing information in code, and when overloaded, it can make understanding complex code difficult, requiring strategies like state tables and dependency graphs. [1] [2]

Notional machines and mental models provide abstract representations of how code executes, enabling programmers to apply familiar schemata and reason about unfamiliar code. [1] [2]

Programmers often transfer prior knowledge incorrectly, leading to misconceptions such as believing variable assignments create permanent links or misunderstanding loop termination. [1] [2]

Misconceptions can be identified through pair programming, testing, and documentation, and are corrected by replacing faulty mental models with accurate ones. [1]

Clear and consistent naming conventions reduce cognitive load by supporting both short-term and long-term memory, making code easier to understand and maintain. [1] [2]

Linguistic antipatterns, such as misleading or inconsistent names, significantly increase cognitive load and can cause confusion and errors. [1] [2]

Effective onboarding separates domain learning from code exploration and supports memory with documentation and focused tasks. [1] [2]

Aligning code structure and identifiers with business domains enhances closeness of mapping, making code more understandable and maintainable. [1]

Prior knowledge can both help and hinder learning new languages, as positive transfer accelerates learning while negative transfer can cause persistent misconceptions. [1] [2]

Sharing a vocabulary of mental models within a team eases communication and helps members reason about code more effectively. [1]