Вот собрал тут что важно по хардскилам, вместо ваших алгоритмов, литкода, высоконагруженных кабанчиков и карго-культа микрооптимизации:
- Data structures (just how to use)
- Type systems: nominal, structural, variance...
- Modularity system (in your language)
- Polymorphism (Ad-hoc, Subtype, Parametric, etc...)
- Structural composition, aggregation, delegation
- Functional composition, pure functions
- Abstraction layers separation
- Dispatch and Dynamic dispatch
- Referential transparency
- Law of Demeter
- Referential transparency
- Abstract data types (ADT)
- Hidden and explicit state
- Lazy evaluation
- Declarative vs imperative style
- Recursion versus loops
- Generics (generic programming)
- Separation of concerns
- Isolation, interfaces, architectural boundaries
- Dependency injection and Inversion of control
- Coupling and cohesion
- Mutable vs immutable data
- Idempotent operations
- Naming conventions
- Error handling
- Refactoring, code review process
- Tests (unittesting, coverage, end-to-end...)
- Multiparadigm programming
- Metaprogramming (codegeneration and dynamic)
- Platform-agnostic, framework-agnostic approach
- Domain-Specific Language (DSL), Interpreter, AST
- Contract programming
- Concurrency and Asynchronous programming
- Separation of system and applied code
- Language and semantics
- AI-assisted engineering
Но все это тоже должно занимать в голове не более 30% от развития инженера, as of 2026. Про 70% напишу еще чуть позже
Repo: https://github.com/tshemsedinov/Programming-Knowledge