Functional requirements describe behavior users need; non-functional requirements define qualities and constraints such as latency, accessibility, security, capacity, and recovery.
Functional requirements describe behavior users need; non-functional requirements define qualities and constraints such as latency, accessibility, security, capacity, and recovery.
| Question | Practical answer |
|---|---|
| When is it useful? | In a small real-world scenario, draw the parts involved, follow one request or decision from start to finish, and mark the evidence produced at each step. |
| What should you do? | Rewrite a vague login request into three behavior examples and four measurable quality constraints, each with an owner and verification method. |
| How do you know it worked? | The result can be repeated from your notes, and each important claim is supported by an output, measurement, query result, or reviewable artifact. |
| Common failure | A common mistake is choosing a tool or pattern before stating the problem, constraints, and success measure. |
flowchart LR
A[Question] --> B[Functional vs non-functional requirements]
B --> C[Small example]
C --> D[Evidence]
The important idea is not to stop at a definition: connect the concept to a small example and observable evidence.
In a small real-world scenario, draw the parts involved, follow one request or decision from start to finish, and mark the evidence produced at each step.
Before acting, write the success signal. Change one condition at a time, observe the result, and record assumptions. For Functional vs non-functional requirements, this separates what you know from what you are merely guessing.
Goal: Rewrite a vague login request into three behavior examples and four measurable quality constraints, each with an owner and verification method.
Expected result: The result can be repeated from your notes, and each important claim is supported by an output, measurement, query result, or reviewable artifact.
A common mistake is choosing a tool or pattern before stating the problem, constraints, and success measure.
When the result differs from your prediction, do not change many things at once. Check inputs, versions, environment, permissions, and logs, then repeat from the smallest example.
Use the linked resource or repository at the end of the page when you need a full implementation. Check current versions before applying commands to a real project.
Learn system design as a sequence of decisions, using a small learning platform as the running example.
High-level design explains system boundaries, data flow, dependencies, and major tradeoffs; low-level design specifies components, interfaces, data models, algorithms, and failure handling.
A capacity estimate converts product assumptions into requests per second, concurrency, stored bytes, and network throughput. Ranges and peak factors are more honest than false precision.