Computer Science

Conceptual & Structural Systems

(How software is *organized* at a high level)

• Architecture – The fundamental structure of a system: components, responsibilities, and relationships.
• Design Pattern – Reusable solutions to recurring structural or behavioral problems.
• System Design – End-to-end planning of components, data flow, scaling, and failure modes.
• Platform – A base system upon which other software or services are built.
• Ecosystem – Interacting tools, libraries, services, and users around a platform.
• Stack – A layered collection of technologies used together (e.g., LAMP, MERN).
• Subsystem – A self-contained functional unit within a larger system.
• Module – A discrete, replaceable unit of functionality.
• Component – A deployable or reusable unit with a defined interface.

Code Reuse & Capability Systems

(Things you *build with*)

• Framework – Opinionated structure that controls application flow.
• Library – Reusable code invoked by the developer.
• SDK (Software Development Kit) – Tools, libraries, docs, and examples for a platform.
• API – A formal interface for interacting with a system or service.
• Middleware – Software that connects or mediates between systems.
• Runtime – The environment in which code executes.
• Plugin System – Mechanism for extending a host application.
• Extension – Add-on module that enhances functionality.
• Package – A distributable unit of code.
• Dependency – External code required by a system.

Execution & Environment Systems

(Where software *runs*)

• Environment – A configured context (variables, paths, services).
• Runtime Environment – OS + libraries + execution context.
• Virtual Environment – Isolated dependency space (e.g., Python venv).
• Container – Lightweight, isolated execution unit (e.g., Docker).
• Virtual Machine (VM) – Fully virtualized OS instance.
• Sandbox – Restricted execution environment for safety.
• Host System – The machine or OS running workloads.
• Target Environment – Intended deployment context.
• Emulator – Software that mimics another system.
• Interpreter – Executes code directly.
• Compiler Toolchain – System that translates source to binaries.

Development & Tooling Systems

(How developers *work*)

• IDE – (Integrated Development Environment) Unified coding, debugging, and tooling system.
• Editor – Code authoring environment.
• Build System – Automates compilation, linking, and packaging.
• Toolchain – Collection of compilers, linkers, debuggers, etc.
• Package Manager – Manages dependencies and versions.
• Task Runner – Automates development workflows.
• Debugger – Inspection and control of execution.
• Profiler – Performance measurement system.
• Linter – Static analysis and style enforcement.
• Formatter – Code layout normalization system.

Data & State Systems

(How information is *stored and managed*)

• Database – Persistent data storage system.
• DBMS – Software managing databases.
• Data Store – Generalized storage system.
• Cache – Fast, transient data system.
• Message Queue – Asynchronous communication system.
• Event Bus – Event-driven messaging system.
• State Management System – Controls application state.
• Filesystem – Persistent hierarchical storage system.
• Indexing System – Accelerated lookup structures.

Distributed & Service Systems

(How software *communicates*)

• Client–Server System - A model where a client (user interface or device) sends requests and a server processes those requests and returns responses.
• Distributed System - A collection of multiple computers that work together over a network to function as a single system.
• Microservices Architecture - An approach where an application is built as a set of small, independent services that communicate over APIs.
• Monolith - A single, tightly coupled application where all functionality is contained in one codebase and deployed as one unit.
• Service Mesh - An infrastructure layer that manages communication between services, handling routing, security, and observability.
• Backend System - The server-side components that handle business logic, data processing, and storage.
• Frontend System - The user-facing interface that interacts with the backend, such as web apps or desktop interfaces.
• Control Plane / Data Plane - The control plane makes decisions and manages the system, while the data plane executes those decisions and handles real work.
• Load Balancer - A system that distributes incoming requests across multiple servers to improve performance and reliability.
• Gateway - A centralized entry point that routes, filters, and enforces policies on incoming requests to a system.
• Reverse Proxy - A server that sits in front of backend services and forwards client requests while hiding internal system details.

Deployment & Operations Systems

(How software *lives in the world*)

• Operating System - Software that manages hardware resources and provides a runtime environment for applications.
• Infrastructure - The underlying physical or virtual resources such as servers, storage, and networking that support systems.
• Cloud Platform - A system that provides on-demand access to computing resources and services through abstraction and automation.
• Orchestration System - Software that automates deployment, scaling, scheduling, and management of applications (e.g., Kubernetes).
• CI/CD Pipeline - An automated workflow that builds, tests, secures, and deploys software from source code to running systems.
• Monitoring System - A system that tracks performance and health metrics of infrastructure and applications.
• Logging System - A system that collects and stores event records and system messages for debugging and auditing.
• Telemetry System - A system that gathers and analyzes metrics, logs, and traces to understand system behavior.
• Configuration Management System - A system that defines, manages, and enforces configuration settings across environments.
• Secrets Management System - A system that securely stores and controls access to sensitive data like passwords, keys, and tokens.

Security & Governance Systems

(How systems *protect themselves*)

• Authentication System - A system that verifies the identity of a user or service.
• Authorization System - A system that determines what actions an authenticated user or service is allowed to perform.
• Identity Management System - A system that manages user identities, credentials, and access lifecycle.
• Access Control System - A system that enforces rules governing access to resources.
• Key Management System - A system that creates, stores, and manages cryptographic keys.
• Policy Engine - A system that evaluates rules and policies to make access or operational decisions.
• Permission Model - A framework that defines how permissions are structured and assigned (e.g., roles or attributes).
• Trust Boundary - A point in a system where trust assumptions change and additional security controls are required.
• Security Sandbox - An isolated environment used to safely execute untrusted or restricted code.

AI-Specific System Terms

(Modern AI “systems” framing)

• Model Architecture - The structure and design of a machine learning model, such as a transformer or neural network.
• Inference Engine - The system that runs a trained model to generate predictions or outputs.
• Training Pipeline - The process and infrastructure used to train machine learning models from data.
• Evaluation Framework - A system for measuring and validating model performance and reliability.
• RAG Pipeline - A system that retrieves relevant data and feeds it into a model to improve generated outputs.
• Vector Database - A database optimized for storing and searching embeddings for semantic similarity.
• Agent System - A system where an AI model can take actions, use tools, and execute tasks autonomously.
• Orchestration Graph - A structured representation of workflows and dependencies between components or steps.
• Prompting Framework - A system for managing and structuring prompts, templates, and context for AI models.
• Multi-Agent System - A system where multiple AI agents collaborate or coordinate to complete tasks.