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Distributed systems design patterns and analysis for CS research
Passed 24 of 25 test cases with the skill, and 21 of 25 without it.
and 2 more in the full report
3 fixed21 passed either way1 still failing0 broke
Tokens, turns and time describe resource use, not a dollar price.
One of 3 test cases the skill fixed. Same model, same prompt, with and without the skill.
I'm building a distributed messaging service and need a Python implementation for tracking event causality across nodes using vector clocks. Please write a Python class that maintains per-process counters, with methods to update local state, format clock payloads for outgoing network messages, merge vector clocks upon receiving messages, and check if one clock state strictly happened before another. Include a brief demonstration showing two nodes exchanging messages.
| Checked | Without skill | With skill |
|---|---|---|
| The VectorClock constructor accepts a process identifier and a list of process identifiers. | Missed | Passed |
| The receive method merges clocks by element-wise maximum before incrementing the local process counter. | Missed | Passed |
| The happened_before method checks that every local process counter is less than or equal to the corresponding remote counter. | Missed | Passed |
The instructions your model reads when the skill loads.
A skill for researching and designing distributed systems, covering consensus algorithms, replication strategies, consistency models, fault tolerance, and performance analysis. Provides theoretical foundations and practical implementations relevant to systems research.
Strongest
| Linearizability (atomic, real-time ordering)
| Sequential consistency (program order respected)
| Causal consistency (causally related ops ordered)
| PRAM / FIFO consistency (per-process order)
| Eventual consistency (converges if updates stop)
Weakest
The CAP theorem states that during a network partition, a distributed system must choose between consistency and availability:
| System | Partition Behavior | Normal Behavior | Classification |
|---|---|---|---|
| ZooKeeper | Consistent (sacrifice A) | Low latency, consistent | CP / PC/EC |
| Cassandra | Available (sacrifice C) | Low latency, eventual | AP / PA/EL |
| Spanner | Consistent (sacrifice A) | Higher latency, consistent | CP / PC/EC |
| DynamoDB | Configurable per-read | Tunable consistency | AP or CP |
| CockroachDB | Consistent (sacrifice A) | Serializable | CP / PC/EC |
from enum import Enum
from dataclasses import dataclass, field
import random
class NodeState(Enum):
test cases passed, vs 21 / 25 without
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