SystemVerilog Testbench Introduction

SystemVerilog Testbench Architecture

APB Interface

APB Transaction

APB Generator

APB Driver

APB Driver Phase 2

APB Monitor

APB Scoreboard

APB Environment

APB Testbench Top

RISC-V Processor (YARP) Interface

YARP Transaction

YARP Generator

YARP Driver

YARP Data Memory Model

YARP Monitor

YARP Scoreboard

YARP Testbench Top

DVCon 26 Hackathon Problem

Array Sum Limit

Array Index Sum Limit

Ball Draw No Repeat

Conditional Even Probability

Even Odd Index Value

Five Consecutive Ones

Frequency Constraint

Grouped Ones

Index Value Range

Leap Year

Matrix Rotation

Non Adjacent Ones

Power of 4

Dynamic Ranges

Recent Four Unique

Row Max Unique

Subarray Max Sum

Three Duplicates Only

Tic Tac Toe

Unique 3D Array

Weighted Popcount

Unique Sum

Split Array into Queues

# Weighted Popcount Distribution

## Problem Statement

Generate a 10-bit vector where the number of 1s (popcount/population count) is uniformly distributed across all possible counts from 1 to 10.

Each possible popcount value (1, 2, 3, 4, 5, 6, 7, 8, 9, 10) should have an equal 10% probability of being generated.

This constraint ensures fair distribution of bit patterns across different Hamming weights.

## Constraints
- Vector size: 10 bits
- Popcount range: 1 to 10 (exactly one 1, two 1s, ..., or all ten 1s)
- Distribution: Each popcount value has exactly 10% probability (equal weighting)
- Valid patterns: Any 10-bit vector with 1-10 ones

## Examples

### Example 1:
```
1111100000 (or any other arrangement with exactly 5 ones)
Explanation: Exactly 5 bits are set to 1
```

### Example 2:
```
0000000001 (or 0000000010, or any single bit set)
Explanation: Exactly 1 bit is set to 1, 9 bits are 0
```

### Example 3:
```
1111111111
Explanation: All 10 bits are set to 1
```

### Example 4:
```
- Sample 1: 1010101010 (popcount = 5)
- Sample 2: 1111111111 (popcount = 10)
- Sample 3: 0000000001 (popcount = 1)
- Sample 4: 1111000000 (popcount = 4)
- Sample 5: 1110000000 (popcount = 3)
...running 1000 samples...
Output: Distribution shows roughly 10% samples for each popcount value 1-10
Explanation: The statistical distribution validates equal weighting
```

### Example 5:
```
1111111111 (popcount = 10)
Valid (popcount = 10)
Explanation: 10 ones, within the allowed range [1:10]
```

### Example 6:
```
0000000000 (popcount = 0)
Invalid
Explanation: Popcount 0 is not in the allowed range [1:10]
```
