SOLID Principles · Coding problem

Add Campaigns Without Touching Checkout

A free coding problem from the Open/Closed Principle skill. Read it here, then solve it in the app in Java or Python.

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  • Easy
  • Coding problem
  • Free
  • Java and Python

The problem

Marketing launches new discount campaigns all the time. The old checkout had a switch over campaign names that had to be edited - and re-tested - for every one. It has been redesigned around an extension point: each campaign is a DiscountRule, and Checkout simply looks the rule up. SummerSale (10% off) already exists.

Add three campaigns without changing Checkout:

  • BLACK_FRIDAY - 30% off orders of 2000 or more; nothing off smaller orders
  • LOYALTY - 5% off, but never more than 200 off
  • FIRST_ORDER - a flat 100 off (Checkout already makes sure a price never goes below 0)

Percentages are rounded down (amount * 30 / 100). Register each new rule in Campaigns.all() - the only existing code you should need to edit. An unknown campaign gives no discount.

In Python: DiscountRule is an abstract base class, the registration list is the all_campaigns() function (Java's Campaigns.all()), and percentages round down with //.

Input: each command is <CAMPAIGN> <amount>, printed as <CAMPAIGN> <amount> -> <final price>.

Example

Input:
5
SUMMER 1000
BLACK_FRIDAY 2500
BLACK_FRIDAY 1999
LOYALTY 1000
FIRST_ORDER 60

Output:
SUMMER 1000 -> 900
BLACK_FRIDAY 2500 -> 1750
BLACK_FRIDAY 1999 -> 1999
LOYALTY 1000 -> 950
FIRST_ORDER 60 -> 0

Constraints

  • At most 1000 commands; 0 <= amount <= 10^9; campaign names are case-sensitive.

How it's graded

  • Run checks your code against the examples. Submit also runs hidden tests, and you see pass or fail for them, never their inputs.
  • Stuck? Hints come in four steps, from a nudge to a code skeleton, each costing part of the points.
  • Once you pass, you see the approaches from brute force to optimal, and where your solution lands among them.

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