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Graph/deadlock-contention-masked-progress

AntiPattern

Deadlocks and Hidden Contention

deadlock-contention-masked-progress

Locking and concurrency mechanisms interact in ways that either deadlock (cyclic lock waits) or mask progress (queues report success while dropping work), causing systems to stall or lose data despite apparent synchronization.

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Updated6/27/2026

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30 linked nodes

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you can use Zustand getters and optimistic update — multiple or rapid clicks could actually cause the updates to be executed but out of order. Tension: no optimistic update so u see that delay (lag) you said about.

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handle a scenario when the code is fine but backend went offline — prefetching data with usePrefetchQuery. Tension: prefetch works.

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As long as you lock more than a single thing at a time, you risk deadlocks. — lock more than a single thing at a time. Tension: You hold B waiting for A, they hold A waiting for B. Outcome: one of you has to abort or you're stuck.

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If true, staleness checks for cached data will be bypassed, but missing data will be requested from the server. Tension: Default: false. Outcome: To force full offline mode, use --offline.

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provided it's called within the same process — workers might be pre-forked. Tension: the cache doesn't work across processes. Outcome: each process got its own cache.

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You can use redis lock to solve this — around each change you are making to the redis/DB. Outcome: put this lock around each change you are making to the redis/DB.

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I suggests you use rapyer, Which takes special care to handle deadlock problems. — Since you are using json models. Tension: deadlock problems.

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any time you have an I/O bound process with lots of idle time — waiting for user input, waiting for a TLS handshake. Tension: wrapping it in an async task can let other code run.

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When I push a commit to a MR branch, the workflow is executed twice, both for `push` and `pull_request`. Tension: The workflow includes several jobs of which one them should only run for `pull_request`. Outcome: Maybe a bit late, but you could use Concurrency:.

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I know that it is recommended to use `select..for update skip locked` — under high data volume and frequent updates/deletions. Tension: it can lead to performance degradation. Outcome: `skip locked` is the cheapest option.

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bound it with a "progress ceiling" — a process emitting bytes but making NO semantic progress. Tension: a process emitting bytes but making NO semantic progress (livelock) would be shielded forever. Outcome: re-arms recovery after a long no-progress window even while bytes flow.

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you have such an id that is called transaction id. Tension: If none of that is available either. Outcome: you can create a (sort of) mutex variable (let's call it `lock`).

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In general this calls for a mutex. — If the language does not provide mutexes out of the box. Outcome: you can create a mutex.

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if you're concerned about the password persisting somewhere either on disk or after your program terminates. Tension: password persisting somewhere either on disk or after your program terminates. Outcome: Lock the memory backing the string such that it c.

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Cause of the deadlock.

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Use virtual threads for blocking DB/IO work to improve scalability under the same small pool, or switch to a reactive database driver/event-loop model to avoid blocking carrier threads; adjust concurrency/throttling accordingly (semaphore/backpressure) rather than assuming the current JDBC + thread pool design remains optimal.

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use a set to define which are currently running, and remove from set at end rather than before calling `process(client)` — You could use a counter (AtomicInteger) instead of `HashSet`, or `Semaphore`. Tension: your locks don't prevent more than MAX_THREAD_POOL running threads at once. Outcome: which is intended for this type of use.

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I am seeing an increase in latencies in requests that do succeed — I have a logic of the sort :. Tension: none of them enforce a timeout on the total duration of the request. Outcome: Then properly close the connection in a finally / try-resource block.

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Use synchronization primitives, locks, or other publication mechanisms that establish a happens-before between the write and subsequent read

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after the system restarts. Tension: wouldn't it be a waste of DB space if I'm storing millions of tasks that I only ever need to process once. Outcome: store the last offset in cache and then continue processing data from the last checkpoint.

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producer-consumer design to process a list of objects. Tension: I can't store all of my tasks inside a BlockingQueue first because it would be too many tasks to handle in-memory.

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Mysql driver 9.0.0+ (currently 9.1.0) has ReentrantLock(s) now — IF they were not hooked on mysql internal synchronized blocks. Tension: it should have helped. Outcome: and it should work as this enabled the virtual thread to go do something else.

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decorate a connection pool with a priority queue to avoid overloading the connection pool — When the connection pool usage goes above some critical level. Tension: start throttling requests and maybe even drop low priority requests from the queue all together.

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Only if all threads of your program use `seq_cst` memory order for operations and fences. — The C++ guarantee of sequential consistency for data-race free programs only applies if all atomic operations are `seq_cst`, or if you use equivalent fences. Tension: One thread using a fence can't necessarily recover sequential consistency when other threads are using `relaxed` or `release` and `acquire` operations on `std::atomic`. Outcome: use `seq_cst` memory order for operations and fences.

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There are workarounds, depending on your usecase — calling `.notify_one()` / `.notify_all()` on a destructed `std::atomic`. Tension: There is a C++ Paper - P2616R4 - which would fix this problem. Outcome: using `std::binary_semaphore` delegating `.wait()` and `.notify_xxx()` to a separate atomic variable that has a longer lifetime manually call the futex syscalls and bypass the stdlib.

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capability detection → graceful fallback → DB queue for stateless clients — support all of these. Tension: There's no single mechanism that works everywhere. Outcome: capability negotiation is the only viable pattern.

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Cache in OnAwake — Key s&box performance patterns from the optimizer skill:. Tension: GetComponent every frame. Outcome: Physics work in OnFixedUpdate.

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Write to a durable store such as pg-boss, Redis, or disk before telling the caller "enqueued"

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Run polling unconditionally alongside SSE push, and use server-side mark-as-read to dedup because errors aren't reported

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the server instructions list locked tools — the server dynamically reports locked tools in its welcome message on each connection. Tension: it would be helpful to have a canonical reference in the forum. Outcome: the server dynamically reports locked tools in its welcome message on each connection.

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