Simulating Weak Memory Consistency in Go

Concurrency is a cornerstone of modern software development, but managing it effectively requires a deep understanding of how multiple threads or goroutines interact with shared memory. This challenge aims to explore the nuances of weak memory consistency models, specifically within the Go programming language, by simulating scenarios where the order of memory operations can lead to unexpected outcomes. Understanding these concepts is crucial for writing correct and performant concurrent Go programs.

Problem Description

Your task is to implement a simulation that demonstrates the behavior of a weak memory model in Go. You will create a scenario involving multiple goroutines accessing and modifying shared variables. The goal is to observe how the Go runtime, which implements a rather strong memory model but can still exhibit interesting behaviors under certain concurrent conditions, allows for potential reordering of operations that might not occur in a strictly sequential program.

Specifically, you need to:

Define a shared state: This will likely involve a few integer variables that multiple goroutines will read from and write to.
Create multiple goroutines: These goroutines will execute a specific sequence of operations on the shared state. The sequence should be designed to potentially reveal memory reordering.
Implement a test runner: This will launch the goroutines, wait for them to complete, and then collect and analyze the final state of the shared variables.
Observe and analyze results: The core of the challenge is to run the simulation many times and collect statistics on the observed outcomes. You should be able to identify patterns that would not be possible under a strong memory model.

Key Requirements:

The simulation must use Go's concurrency primitives (goroutines, channels, mutexes if necessary for synchronization within a goroutine's critical section, but not to prevent the inter-goroutine reordering effects you are trying to demonstrate).
The operations within each goroutine should be simple but designed to create potential race conditions if memory ordering is not carefully considered.
The test runner should be able to execute the simulation a large number of times (e.g., 10,000 or more) to gather statistically significant data.
You need to report the frequency of certain "unexpected" outcomes.

Expected Behavior:

In a strong memory model, certain sequences of operations might be guaranteed to execute in the order they appear in the code. In a weak memory model, the compiler or hardware might reorder these operations for performance. For this challenge, you should aim to create a scenario where a goroutine might observe a variable having a value that it shouldn't have based on a strict sequential execution. For example, a goroutine might read a value of a variable after another goroutine has written to it, but before that second goroutine has written to a different, logically related variable.

Edge Cases:

Race Conditions: While the goal is to observe weak memory effects, your design should acknowledge the inherent risk of race conditions. You are not necessarily solving race conditions with locks for the purpose of this demonstration, but rather illustrating how Go's memory model can produce certain behaviors even when races could occur.
Goroutine Scheduling: The unpredictable nature of goroutine scheduling adds another layer of complexity.

Examples

This challenge is more about demonstrating a principle than a single input/output pair. The "input" is the code structure you design, and the "output" is the statistical distribution of results after many runs.

Conceptual Example Scenario:

Imagine two goroutines, goroutineA and goroutineB, sharing two integer variables, x and y, initially both 0.

goroutineA:

x = 1
y = 1

goroutineB:

Reads y.
Reads x.

Possible Observations and Analysis:

Under a strong memory model, goroutineB would typically observe:

y = 0, x = 0 (if it reads before goroutineA writes)
y = 1, x = 0 (if goroutineA writes y but not x before goroutineB reads x)
y = 0, x = 1 (if goroutineA writes x but not y before goroutineB reads y)
y = 1, x = 1 (if goroutineA writes both before goroutineB reads x)

However, in a weaker memory model (or even in Go under specific conditions), goroutineB could potentially observe:

Output: y = 0, x = 1

Explanation: This outcome suggests that goroutineA wrote x = 1 and then y = 1, but goroutineB observed x = 1 before it observed the write to y (or logically after the write to y completed, but the read of x happened before the read of y completed its effect). This implies a reordering where the write to x became visible to goroutineB before the write to y.

Your task would be to design such a scenario, run it thousands of times, and report how often this "unexpected" outcome (e.g., y = 0, x = 1) occurs.

Constraints

The simulation should run on standard Go installations.
The number of goroutines involved in the core simulation loop should be small (e.g., 2-4).
The number of iterations for the test runner should be at least 10,000 to gather sufficient data.
The operations within each goroutine must be simple assignments or reads of integers.

Notes

This challenge is designed to be educational. While Go's memory model is generally considered strong, exploring scenarios that could lead to surprising results helps build intuition about concurrency. Consider using atomic operations or channels strategically to control the visibility of writes if you want to force specific orders for comparison, but the core of the demonstration should rely on Go's default memory ordering guarantees. The goal is to make the potential for reordering visible through repeated execution. Think about how you can design the shared state and goroutine logic to maximize the chances of observing non-sequential behavior.