Developer catches three silent system bugs in one day before they caused real damage

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A developer working on an automated stock analysis system identified and resolved three separate issues in a single day, all of which had been failing invisibly without obvious symptoms. The first problem involved a local LLM server lacking an output length cap, allowing the model to occasionally generate tens of thousands of tokens unchecked for up to tens of minutes; a new silence-based progress monitor was designed to detect future stalls regardless of task size. The second issue stemmed from an earlier fix that increased model input length, which unexpectedly caused inference speed to drop nearly 2.7 times during evening hours when other programs consumed GPU memory and forced partial CPU offloading. The third bug involved a widely used trading-calendar library that still classified a newly reinstated South Korean public holiday as a regular trading day, which could have triggered a cascade of incorrect automated analyses had it not been caught before the date arrived. The developer noted that all three flaws shared a common trait: none produced visible errors in normal conditions, underscoring the risk of assuming that silence means correctness.

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