这是我用来快速筛选掉大部分申请者的15秒编码测试。
Here is the 15 sec coding test I used to instantly filter out most applicants

原始链接: https://josezarazua.com/im-a-former-cto-here-is-the-15-sec-coding-test-i-used-to-instantly-filter-out-50-of-unqualified-applicants/

为了有效筛选大量远程开发者申请者,应侧重于*淘汰*不合格的候选人,而非寻找合格的候选人。一种出奇有效的方法是设计一个看似简单的编码问题,使其能够通过心算轻松解决。 示例问题——一个包含基本算术的短循环——包含一个微妙的错误(隐藏的等号),旨在让那些依赖复制粘贴到解释器或AI工具的人出错。正确答案(1)表明具有很强的心理编码能力,而错误答案(-11)则表明依赖外部工具。 MonetizeMore的测试显示,大约50%的人使用了AI/解释器,47%的人正确解决了问题,3%的人回答错误。有趣的是,一些最初失败的候选人在发现正确答案后重新申请,其中一人成为一名宝贵的员工。虽然并非万无一失,但这种方法通过将处理能力提高一倍,大大加快了候选人筛选速度。

## Hacker News 讨论:15秒编码测试筛选申请者 一位 Hacker News 用户分享了一篇博客文章的链接,详细介绍了一种用于快速筛选求职者的 15 秒编码测试 ([josezarazua.com](https://josezarazua.com))。该测试依赖于一个微妙的 CSS 技巧——一个隐藏的等号——来确定候选人是心算解决问题还是通过复制粘贴到 AI 工具中。 讨论很快偏离了主题。许多评论者质疑该测试的有效性和公平性。人们对依赖屏幕阅读器的视力障碍用户的可访问性表示担忧,因为隐藏的字符可能导致错误答案。另一些人指出,阅读模式甚至基本的代码编辑器都会显示隐藏的字符,从而使测试失去意义。 一些用户提倡更具对话性的面试,重点关注候选人表达思维过程和最近经验的能力。有人建议该测试可能会无意中筛选掉那些喜欢验证代码执行或利用现有工具的优秀候选人。一个关键的结论是关于一个简单的测试是否真的能识别有价值的技能,或者只是奖励特定的问题解决方法。
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原文

If you have a remote position open, your challenge is not attracting the correct candidate, it’s filtering out the bad ones, because you’ll have hundreds or thousands of them.

This my favorite technique:
Add a programming knockout question to the application process that is so simple to solve that only* unqualified developers will not do it manually.

Here’s the question:


result = 0
for x in [3,3,5]:
    if x >= 3:
        result = result - x
    else:
        result = result + x

What is result?

Reveal the answer

If you got 1, congratulations, you have wired your brain to easily interpret code.

If you got -11, you copy pasted it somewhere. The trick is that there’s a hidden equal sign.

The logic of course is that for a good programmer it would be more of a hassle to copy, open an interpreter or ChatGPT, paste it, run it, then answer, than just run the code in their head.

I used a very similar question while I was CTO at MonetizeMore. Interesting things happened:

50% of candidates got the AI/Interpreter answer.

47% Answered the question correctly.

3% Answered incorrectly.

A few candidates resubmitted the application after getting the answer wrong (we didn’t tell them), one of those candidates was a great hire.

One candidate posted the incorrect question to a forum, and got an answer. So when subsequent candidates Googled the incorrect question, they got the wrong answer.

*I should say this method is not perfect, and you’ll get false negatives, but I see it more as doubling your ability to process candidates, or reducing in half your recruitment time.

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