Count Tested Devices After Test Operations

Count Tested Devices After Test Operations

What is this problem about?

The Count Tested Devices After Test Operations coding problem presents a simulation where you have an array of integers representing the battery percentage of several devices. You process them in order. If a device has a battery percentage $> 0$, it is considered "tested," and the battery of all subsequent devices decreases by 1. If a device has 0 battery, you move to the next without any penalty to others.

The goal is to find the total number of tested devices.

Why is this asked in interviews?

Accenture and similar firms ask this to verify basic simulation interview pattern skills. It tests if you can follow a set of procedural rules and update state across an array. While the problem allows for a naive $O(N^2)$ update, a clever candidate will realize that you don't need to actually subtract from the array, but rather track a "global decrease" value, which demonstrates optimization skills.

Algorithmic pattern used

This problem can be solved using Simulation and Greedy/Lazy Updates.

• Naive: For every tested device, run a loop to decrement all future devices.
• Optimized ($O(N)$): Maintain a tested_count. For each device $i$, its actual battery is initial_battery[i] - tested_count. If this value is $> 0$, then this device will be tested, and you increment tested_count.

Example explanation

batteries = [1, 1, 2, 1, 3]

1. Device 0: Battery 1. $1 > 0$. Tested! tested_count = 1.
2. Device 1: Battery 1. Actual: $1 - 1 = 0$. Skip.
3. Device 2: Battery 2. Actual: $2 - 1 = 1$. Tested! tested_count = 2.
4. Device 3: Battery 1. Actual: $1 - 2 = -1$. (Treat as 0). Skip.
5. Device 4: Battery 3. Actual: $3 - 2 = 1$. Tested! tested_count = 3. Total tested = 3.

Common mistakes candidates make

• Modifying the array: Using a nested loop to subtract 1 from the rest of the array, which leads to $O(N^2)$ complexity.
• Negative batteries: Not realizing that once a battery reaches 0, it doesn't matter if it goes "more negative"—it's still not going to be tested.
• Logic confusion: Decrementing the battery of previous devices instead of only subsequent ones.

Interview preparation tip

Look for "Global State" opportunities. If an operation affects everything after a certain point, try to represent that effect with a single variable (like an offset or counter) rather than updating the entire dataset.