正式验证是计算机科学的理论领域之一。

从历史上看，这一领域是晦涩难懂的，但是AI的最新进展可能会将其带到前面和中心。

In the realm of computer science, few areas are as theoretical and hold as high a threshold for practical application as formal verification. It essentially takes the tools of mathematical logic and applies them to verifying whether statements are correct.

在计算机科学领域，很少有理论上的领域像正式验证那样具有实际应用的高阈值。从本质上讲，它采用了数学逻辑的工具，并将其应用于验证语句是否正确。

This field has remained largely in the academic sphere, but recent advances in AI may finally bring it front and center.

该领域主要保持在学术领域，但AI的最新进展最终可能使它成为领先和中心。

I spoke with Clark Barrett, a professor of computer science at Stanford, who tells of a software bug that once led to the explosion of a rocket. The software ran an instance that forced it to convert a floating-point number into an integer. This caused the program to crash and the rocket to explode. A formal verification of the code would have avoided that problem.

我与斯坦福大学计算机科学教授克拉克·巴雷特（Clark Ba​​rrett）进行了交谈，他讲述了一个曾经导致火箭爆炸的软件错误。该软件运行了一个实例，该实例迫使其将浮点数转换为整数。这导致程序崩溃，火箭爆炸。对代码的正式验证将避免这个问题。

Compiling is the weakest form of verification. A stronger form would be to run a battery of test cases. To see this more clearly, consider a function that divides two numbers. Without doing any internal checks, that function could run on any numerical inputs. If your test cases excluded 0, your function would still compile. But the edge case of 0 in the denominator would cause the program to crash. Only a formal verification would catch this because it’s not sufficient just to evaluate the functions on the different inputs, but rather to assess the function on its underlying logic.

编译是验证的最弱形式。更强大的形式是运行一系列测试用例。要更清楚地看到这一点，请考虑一个划分两个数字的函数。无需进行任何内部检查，该功能就可以在任何数值输入上运行。如果您的测试用例不包括0，则您的功能仍将编译。但是分母中0的边缘情况会导致程序崩溃。只有正式验证才能捕捉到这一点，因为它不足以评估不同输入的功能，而是要评估其基础逻辑的功能。

The bar for formal verification is high, and the tools are obscure and hard to use. Outside of the Mars rover, they have not had wide acceptance. But the one possible exception today is cloud services. Cloud providers allow customers to enter their own query logic when using their services. An error in the query logic, such as inadvertently typing “or,” instead of “and” can have existential consequences, giving everyone access instead of no one. As such, companies like AWS are now recruiting computer scientists in formal verification by the hundreds.

正式验证的标准很高，工具晦涩难懂。在火星漫游者之外，他们没有得到广泛的接受。但是今天可能的一个例外是云服务。云提供商允许客户在使用服务时输入自己的查询逻辑。查询逻辑中的一个错误，例如无意中键入“或”而不是“和”可以带来存在的后果，可以使每个人访问而不是没有人。因此，像AWS这样的公司现在正在招募数百人进行正式验证的计算机科学家。

The big use case will be formally verifying code written by AI. As AI tools improve, more code will be written by AI, and we need fast and cheap ways to verify this code beyond simply compiling it. That’s where formal verification could have its Super Bowl moment. There is now a big research effort underway to deploy these formal verification tools at scale to AI-generated code.

大用例将是由AI编写的代码正式验证的。随着AI工具的改善，AI将编写更多代码，我们需要快速，便宜的方法来验证此代码，而不是简单地编译该代码。这就是正式验证可能拥有超级碗时刻的地方。现在，正在进行大量的研究工作，将这些正式验证工具按大规模部署到AI生成的代码。

This could have an enormous impact, making software bugs a thing of the past. Not only would software be written faster with AI, but it would be better too.

这可能会产生巨大的影响，使软件错误成为过去。不仅可以使用AI编写软件，而且还会更好。

What about Bitcoin?

那比特币呢？

Once these formal verification tools arrive, I’m eager to see how Bitcoin would fare. But the early answer here is that Bitcoin should fare well because it uses several strict forms of logic that give it its high security. For example, full nodes of the network check signatures (through SigOps) when verifying transactions. If the signature fails, the transaction will never enter the mempool, nor be included in a block. Similarly, miners win a block only if their hash of the block header lies below the difficulty target. And a transaction is valid only if the inputs exceeds its outputs.

这些正式验证工具到达后，我渴望看到比特币的票价。但是这里的早期答案是，比特币应该很好，因为它使用了几种严格的逻辑形式，使其具有很高的安全性。例如，在验证交易时，网络的完整节点检查签名（通过sigops）。如果签名失败，则交易将永远不会进入MEMPOOL，也不会包含在块中。同样，矿工只有当他们的块标头的哈希在难度目标以下时才能赢得一个障碍。仅当输入超过其输出时，交易才有效。

In other words, the logic in Bitcoin is fully deterministic. There is no uncertainty about the rules of the protocol. And because of this, there is little room for software bugs, evidenced by the lack of hacks over the last 15 years.

换句话说，比特币中的逻辑是完全确定性的。协议规则没有不确定性。因此，软件错误几乎没有空间，这证明了过去15年中缺乏黑客攻击。

That said, Bitcoin is still an example of social computing. You could say that it is technically vulnerable to collusion if, for example, every single miner in the world agreed to fork the chain. That could happen in theory. But that's where economics comes in: It would not be in the miner's interest to do so.

也就是说，比特币仍然是社交计算的一个例子。您可以说，例如，如果世界上的每个矿工都同意为链条分叉，那么它在技术上很容易受到勾结。从理论上讲，这可能发生。但这就是经济学的来源：这样做并不符合矿工的利益。