Student Marks Manager

A marks manager collects assessments, calculates totals and averages, and assigns grades. Separate calculation from display so the grading policy can change without affecting record storage. Explicitly handle students with no marks.

The average of 88, 92, and 90 is 90, so the first student receives A. An empty marks array is reported explicitly instead of dividing by zero.

A score may be a number but still be out of the allowed 0–100 range; validate before saving it.

This source was compiled using TypeScript 5.8.3 with strict checking, then executed with Node.js 22.16.0. Its stdout below is the actual captured output. The core logic is runnable without a framework or a remote API; integration-specific examples appear in a separate lab when needed.

TypeScript source

type Student = { name: string; marks: number[] };
function report(student: Student): string {
  if (!student.marks.length) return `${student.name}: no marks`;
  const avg = student.marks.reduce((a, b) => a + b, 0) / student.marks.length;
  const grade = avg >= 90 ? "A" : avg >= 75 ? "B" : avg >= 50 ? "C" : "D";
  return `${student.name}: ${avg.toFixed(1)} (${grade})`;
}
console.log(report({ name: "Maya", marks: [88, 92, 90] }));
console.log(report({ name: "Sam", marks: [] }));

Verified output

Maya: 90.0 (A)
Sam: no marks

Compile: npx tsc --strict --target es2022 --module commonjs student-marks-manager.ts; run: node student-marks-manager.js. For examples importing node: modules, install @types/node as a development dependency; for browser or React projects use the separate lab setup.

The average of 88, 92, and 90 is 90, so the first student receives A. An empty marks array is reported explicitly instead of dividing by zero.

Before editing the code, predict what the output will be for one changed input. Run it and compare your prediction with the actual result.

A score may be a number but still be out of the allowed 0–100 range; validate before saving it.

Determine whether the issue belongs to the type system, a trust boundary, or actual runtime behavior before choosing a correction.

Add multiple subjects, rank students by average, and handle tied scores consistently.

Record expected success and failure outcomes, run the code, and compare the observed behavior. Keep the exercise compatible with strict type checking.

The average of 88, 92, and 90 is 90, so the first student receives A. An empty marks array is reported explicitly instead of dividing by zero.

Apply the same reasoning to the practice task, then integrate it into a real app only when the runtime and dependency setup are ready.