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

# Unique Sum Constraint

## Problem Statement

Generate an array of unique integers where the sum of all elements equals a specific target. This combines uniqueness constraint with sum constraint, making the solution space more constrained and realistic.

Your task is to write constraints where:
1. All array elements are unique (no duplicates)
2. Each element is in range [1, 10]
3. The sum of all elements equals 21

## Constraints
- Array size: 6 elements
- Element range: [1, 10] (positive integers)
- All elements must be unique
- Target sum: 21
- Example: {1, 2, 3, 4, 5, 6} sums to 21

## Examples

### Example 1:
```
Array: [1, 2, 3, 4, 5, 6]
Sum: 21
All Unique: Yes
```
Explanation: Consecutive integers from 1-6 sum to 21.

### Example 2:
```
Array: [1, 2, 3, 4, 5, 6]
Sum: 21
All Unique: Yes
```
Explanation: Each element appears exactly once, no duplicates.

### Example 3:
```
Array: [1, 2, 5, 6, 3, 4]
Sum: 21
All Unique: Yes
```
Explanation: Same elements in different order.

### Example 4 (Invalid):
```
Array: [5, 5, 2, 3, 4, 1]
Sum: 20
✗ INVALID: Element 5 appears twice, Sum is 20
```
Explanation: Violates both uniqueness and sum constraints.

## Starter Code Pointer

The constraint logic demonstrates:
1. Combining multiple constraints (range, uniqueness, sum)
2. Using `unique {}` for uniqueness constraint
3. Complex constraint satisfaction with limited solution space
