Go Happens-Before Analysis: Detecting Potential Data Races

Understanding the happens-before relationship is crucial for writing correct concurrent programs in Go. This challenge focuses on implementing a simplified happens-before analysis to detect potential data races by identifying unsynchronized memory accesses across goroutines.

Problem Description

Your task is to build a Go program that analyzes a given set of concurrent operations (represented as a simplified execution trace) and determines if any unsynchronized data accesses could lead to a data race. A data race occurs when two or more goroutines access the same memory location, and at least one of the accesses is a write, and none of the accesses are synchronized.

You will be given a sequence of events, each representing an operation performed by a goroutine on a specific memory location. Each event will specify:

• The goroutine ID
• The memory location ID
• The type of access (read or write)
• Whether the access is synchronized (e.g., via a mutex lock/unlock, channel send/receive).

Your program should output a list of all potential data races detected.

Key Requirements:

• Implement a function that takes a list of Event structs as input.
• For each memory location, track all accesses across all goroutines.
• For each memory location, determine if there's a potential data race by checking for unsynchronized concurrent writes and reads/writes.
• An access is considered synchronized if it happens between a corresponding Lock and Unlock operation for that goroutine and memory location, or between a Send and Receive operation on a channel associated with that memory location. For simplicity, assume locks are always properly paired and channels are used for synchronization on the specific memory location.
• Output should be a list of DataRace structs, each detailing the conflicting goroutines, memory location, and the conflicting operations.

Expected Behavior: The analysis should identify situations where:

1. Goroutine A writes to location X, and Goroutine B writes to location X, and neither access is synchronized.
2. Goroutine A writes to location X, and Goroutine B reads from location X, and neither access is synchronized.

Edge Cases:

• Multiple goroutines accessing the same memory location.
• Synchronized access to a memory location, followed by unsynchronized access.
• Cases where a memory location is only read.
• Empty input list of events.

Examples

Example 1:

Input:
[
  {GoroutineID: 1, LocationID: "A", Type: "write", Synchronized: false},
  {GoroutineID: 2, LocationID: "A", Type: "write", Synchronized: false},
]
Output:
[
  {GoroutineID1: 1, GoroutineID2: 2, LocationID: "A", Operation1: "write", Operation2: "write"},
]
Explanation: Both goroutines 1 and 2 write to location "A" without synchronization, leading to a data race.

Example 2:

Input:
[
  {GoroutineID: 1, LocationID: "B", Type: "write", Synchronized: false},
  {GoroutineID: 1, LocationID: "B", Type: "lock", Synchronized: true},
  {GoroutineID: 2, LocationID: "B", Type: "read", Synchronized: false}, // This read is not synchronized with G1's write
  {GoroutineID: 1, LocationID: "B", Type: "unlock", Synchronized: true},
  {GoroutineID: 2, LocationID: "B", Type: "read", Synchronized: false}, // This read is not synchronized with G1's write
]
Output:
[
  {GoroutineID1: 1, GoroutineID2: 2, LocationID: "B", Operation1: "write", Operation2: "read"},
]
Explanation: Goroutine 1 writes to "B". Then, Goroutine 2 reads from "B". Although Goroutine 1 later unlocks, the write and read are not synchronized, creating a potential data race. Note that the lock/unlock operations themselves don't constitute data access, but rather synchronization for subsequent accesses. For this problem, we assume `Synchronized: true` on lock/unlock means that any *subsequent* access *within* the lock scope is synchronized. Any access *outside* of a lock scope is not.

Example 3:

Input:
[
  {GoroutineID: 1, LocationID: "C", Type: "write", Synchronized: true}, // Synchronized write
  {GoroutineID: 2, LocationID: "C", Type: "read", Synchronized: false}, // Unsynchronized read
]
Output:
[]
Explanation: Goroutine 1's write to location "C" is marked as synchronized. Therefore, it does not form a data race with Goroutine 2's unsynchronized read.

Example 4: (More complex synchronization)

Input:
[
  {GoroutineID: 1, LocationID: "D", Type: "write", Synchronized: false},
  {GoroutineID: 1, LocationID: "D", Type: "lock", Synchronized: true},
  {GoroutineID: 2, LocationID: "D", Type: "read", Synchronized: false}, // This read happens *during* G1's lock
  {GoroutineID: 1, LocationID: "D", Type: "unlock", Synchronized: true},
  {GoroutineID: 2, LocationID: "D", Type: "read", Synchronized: false}, // This read happens *after* G1's unlock
]
Output:
[
  {GoroutineID1: 1, GoroutineID2: 2, LocationID: "D", Operation1: "write", Operation2: "read"},
]
Explanation: Goroutine 1 writes to "D". This write is not synchronized. Then, Goroutine 1 acquires a lock. While the lock is held, Goroutine 2 reads from "D". The problem definition implies that an access *during* a lock is synchronized *if* `Synchronized: true` is set for that access. However, here the read is marked `Synchronized: false`. The critical point is that the *initial* write by G1 is unsynchronized, and the read by G2 happens *after* the write and without the write being synchronized. The lock/unlock actions on G1 don't retroactively synchronize the initial write. The second read by G2 also happens after G1's unlock and is also unsynchronized. The data race is between the initial unsynchronized write of G1 and the unsynchronized read of G2.

Constraints

• The number of events will be between 0 and 1000.
• Goroutine IDs will be positive integers.
• Location IDs will be non-empty strings.
• Access types will be "read" or "write".
• Synchronized flags will be boolean.
• The program should complete within 2 seconds.

Notes

• This is a simplified model. Real-world happens-before analysis involves a more complex graph-based approach considering channel communication, mutexes, waitgroups, and other synchronization primitives.
• Focus on the core logic of identifying conflicting memory accesses across goroutines when synchronization is absent or not properly applied to the specific access.
• You can define your own struct types for Event and DataRace to represent the input and output.
• Consider how to efficiently group events by memory location and then by goroutine to perform the analysis.
• The Synchronized flag on a lock or unlock event itself indicates the presence of a synchronization barrier for operations between them, assuming the operations are for the same lock/resource. For simplicity in this challenge, if an Event related to data access has Synchronized: true, it's considered safe for that specific access. If Synchronized: false, it's potentially unsafe.