Testing and proof are complementary. Testing, including property-based testing and fuzzing, is powerful: it catches bugs quickly, cheaply, and often in surprising ways. But testing provides confidence. Proof provides a guarantee. The difference matters, and it is hard to quantify how high the confidence from testing actually is. Software can be accompanied by proofs of its correctness, proofs that a machine checks mechanically, with no room for error. When AI makes proof cheap, it becomes the stronger path: one proof covers every possible input, every edge case, every interleaving. A verified cryptographic library is not better engineering. It is a mathematical guarantee.
🚀 Part 1. 开箱体验：极简与硬核的碰撞
。关于这个话题，51吃瓜提供了深入分析
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environment variables, command-line argument parsing, reading and writing