我们对数千个编程面试的分析结果 #1887
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我们对数千个编程面试的分析结果 #1887
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tanglie1993
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@sqrthree ，校对认领 |
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@zhangqippp 好的呢 🍺 |
zhangqicode
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Jul 16, 2017
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| *Note: I wrote most of the words in this post, but the legendary *[*Dave Holtz*](https://twitter.com/daveholtz)* did the heavy lifting on the data side. See more of his work on *[*his blog*](http://daveholtz.net/)*.* | ||
| *注意：我写了这个帖子中的绝大部分内容，但传说中的 *[*Dave Holtz*](https://twitter.com/daveholtz)* 完成了数据处理的主要工作。我们可以在 *[*他的博客*](http://daveholtz.net/) *中看到他的其它成果。* |
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排版规则：斜体文字使用加粗样式代替
所以这一段排版应该是下面这样：
注意：我写了这个帖子中的绝大部分内容，但传说中的 Dave Holtz 完成了数据处理的主要工作。我们可以在 他的博客 中看到他的其它成果。
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| More likely than not, what you read and learn in this first, “exploratory” phase of the interview process will inform how you choose to prepare moving forward. | ||
| 更有可能，你在面试流程的“解释性”的第一步中学到的知识，将会告诉你如何准备、如何前往下一步。 |
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你在面试流程的“解释性”的第一步中学到的知识
你在面试流程的第一个“探索性”阶段中学到的知识
| - Most interview guides are written from the perspective of one company. While Company A may really value efficient code, Company B may place more of an emphasis on high-level problem-solving skills. Unless your heart is set on Company A, you probably don’t want to give too much weight to what they value. | ||
| - People lie sometimes, even if they don’t mean to. In writing, companies may say they’re language agnostic, or that it’s worthwhile to explain your thought process, even if the answer isn’t quite right. However, it’s not clear if this is actually how they act! We’re not saying that tech companies are nefarious liars who are trying to mislead their applicant pool. We’re just saying that sometimes implicit biases sneak in and people aren’t even aware of them. | ||
| - A lot of the “folk knowledge” that you hear from friends and acquaintances may not be based in fact at all. A lot of people assume that short interviews spell doom. Similarly, everyone can recall one long interview after which they’ve thought to themselves, “I really hit it off with that interviewer, I’ll definitely get passed onto the next stage.” In the past, [we’ve seen that people are really bad at gauging how they did in interviews](http://blog.interviewing.io/people-are-still-bad-at-gauging-their-own-interview-performance-heres-the-data/). This time, we wanted to look directly at indicators like interview length and see if those actually matter. | ||
| - 绝大多数面试指南是从一个公司的角度写的。可能A公司很重视高效的代码，而B公司更重视的是高级的问题解决能力。除非你一心想去A公司，否则你大概不想太侧重于他们所关心的能力。 |
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排版规则：中英文之间需要增加空格
可能A公司很重视高效的代码，而B公司更重视的是高级的问题解决能力。除非你一心想去A公司，否则你大概不想太侧重于他们所关心的能力
可能 A 公司很重视高效的代码，而 B 公司更重视的是高级的问题解决能力。除非你一心想去 A 公司，否则你大概不想太侧重于他们所关心的能力
| - People lie sometimes, even if they don’t mean to. In writing, companies may say they’re language agnostic, or that it’s worthwhile to explain your thought process, even if the answer isn’t quite right. However, it’s not clear if this is actually how they act! We’re not saying that tech companies are nefarious liars who are trying to mislead their applicant pool. We’re just saying that sometimes implicit biases sneak in and people aren’t even aware of them. | ||
| - A lot of the “folk knowledge” that you hear from friends and acquaintances may not be based in fact at all. A lot of people assume that short interviews spell doom. Similarly, everyone can recall one long interview after which they’ve thought to themselves, “I really hit it off with that interviewer, I’ll definitely get passed onto the next stage.” In the past, [we’ve seen that people are really bad at gauging how they did in interviews](http://blog.interviewing.io/people-are-still-bad-at-gauging-their-own-interview-performance-heres-the-data/). This time, we wanted to look directly at indicators like interview length and see if those actually matter. | ||
| - 绝大多数面试指南是从一个公司的角度写的。可能A公司很重视高效的代码，而B公司更重视的是高级的问题解决能力。除非你一心想去A公司，否则你大概不想太侧重于他们所关心的能力。 | ||
| - 人们有时会撒谎，虽然可能不是故意的。他们可能会写“我们不关心具体的编程语言”，或是“哪怕答案不正确，解释你的思路也是值得的”。但是，实际上他们未必会这样做！我们并不是说科技公司是故意误导求职者的骗子。我们只是认为：有时候不明显的偏见会偷偷产生，人们甚至没有意识到它。 |
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解释你的思路也是值得的
解释你的思路也是有价值的
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https://www.merriam-webster.com/dictionary/worthwhile
我觉得应该翻译成“值得“。
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| > *“We’re talking about practice!”* -Allen Iverson | ||
| > *“我们正在讨论的是练习！”* ——阿伦·艾弗森 |
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排版
“我们正在讨论的是练习！” ——阿伦·艾弗森
“我们正在讨论的是练习！” —— 阿伦·艾弗森
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| That said, one of the most common mistakes we’ve observed qualitatively is people choosing languages they’re not comfortable in and then messing up basic stuff like array length lookup, iterating over an array, instantiating a hash table, and so on. | ||
| 我们观察到的最常见的错误之一是：人们选择自己并不熟悉的语言，然后弄错了查看数组长度、遍历数组、创建哈希表之类的基本操作。但这只是我们定性的结论，没有统计数据支持。 |
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但这只是我们定性的结论，没有统计数据支持。
这句话貌似没有原文
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原文只有qualitatively这个词。我觉得单独拆出一句话来解释这个词比较好。
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| > *“God help me, I’ve gone native.”* — Margaret Blaine | ||
| > *“救命，我已经变成本地人了。”* — Margaret Blaine |
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“救命，我已经变成本地人了。”
“救命，我已经变成本地人了。”
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| We restrict this analysis to C++, Java and Python because these are the three languages where we had a good mixture of interviews where the company did and did not use that language.** The results here are mixed. When the interview language is Python or C++, there’s no statistically significant difference between the success rates for interviews where the interview language is or is not a language in the company’s stack. However, interviewers who interviewed in Java were more likely to succeed when interviewing with a Java shop **(p=0.037). | ||
| 我们把这个分析限制在 C++, Java 和 Python ，因为这三种语言都有很多公司用和不用它们。**结果并不一致。对于 Python 和 C++而言，面试者使用的语言是否在公司的技术栈内，并不会对成功率产生显著的影响。但是，使用 Java 的面试者在使用 Java 的公司面试时，更有可能成功**(p=0.037)。 |
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建议全局调整一下加粗的设置，** 与内容之间空格导致有些加粗的生效有问题，比如这一行从内容上看
结果并不一致。对于 Python 和 C++而言，面试者使用的语言是否在公司的技术栈内，并不会对成功率产生显著的影响。但是，使用 Java 的面试者在使用 Java 的公司面试时，更有可能成功
这一段结果才是应该被加粗的，而上面几段文字则不需要加粗
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| **Furthermore, no matter what, poor technical ability seems highly correlated with poor communication ability — regardless of language, it’s relatively rare for candidates to perform well technically but not effectively communicate what they’re doing (or vice versa)**, largely (and fortunately) debunking the myth of the incoherent, fast-talking, awkward engineer. | ||
| **另外，无论如何，技术能力似乎和沟通能力紧密相关——不管什么语言，技术表现很好的面试者沟通能力不好，是很罕见的，反之亦反。**, 这很大程度上拆穿了工程师往往笨拙、语无伦次的谣言。 |
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| *Want to become awesome at technical interviews and land your next job in the process? *[*Join interviewing.io*](http://www.interviewing.io)*!* |
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@tanglie1993 可以先根据第一位校对者的意见进行调整了哈。 |
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@sqrthree 申请校对 |
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@yzgyyang 妥妥哒 🍻 |
yzgyyang
reviewed
Jul 18, 2017
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| If you’re reading this post, there’s a decent chance that you’re about to re-enter the crazy and scary world of technical interviewing. | ||
| 如果你正在读这个帖子，很有可能，你正打算重新进入疯狂而可怕的技术面试的世界。 |
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| Either way, the first step in the interviewing process is usually to read a bunch of online interview guides (especially if they’re written by companies you’re interested in) and to chat with friends about their experiences with the interviewing process (both as an interviewer and interviewee). | ||
| 无论哪种情况，面试流程的第一步，通常是读一堆在线面试指南（特别是由你感兴趣的公司写的那些），并和朋友们聊起他们面试（作为面试官和面试者）的经验。 |
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并和朋友们聊起他们面试（作为面试官和面试者）的经验
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并和朋友们聊起他们面试（作为面试官和面试者）面试的经验
| - A lot of the “folk knowledge” that you hear from friends and acquaintances may not be based in fact at all. A lot of people assume that short interviews spell doom. Similarly, everyone can recall one long interview after which they’ve thought to themselves, “I really hit it off with that interviewer, I’ll definitely get passed onto the next stage.” In the past, [we’ve seen that people are really bad at gauging how they did in interviews](http://blog.interviewing.io/people-are-still-bad-at-gauging-their-own-interview-performance-heres-the-data/). This time, we wanted to look directly at indicators like interview length and see if those actually matter. | ||
| - 绝大多数面试指南是从一个公司的角度写的。可能A公司很重视高效的代码，而B公司更重视的是高级的问题解决能力。除非你一心想去A公司，否则你大概不想太侧重于他们所关心的能力。 | ||
| - 人们有时会撒谎，虽然可能不是故意的。他们可能会写“我们不关心具体的编程语言”，或是“哪怕答案不正确，解释你的思路也是值得的”。但是，实际上他们未必会这样做！我们并不是说科技公司是故意误导求职者的骗子。我们只是认为：有时候不明显的偏见会偷偷产生，人们甚至没有意识到它。 | ||
| - 你从朋友或认识的人那里听到的传闻并不一定有事实根据。很多人认为短的面试意味着失败。同样，每个人都可以回忆起一个很长的面试，在这面试结束后他们以为：“我成功打动了面试官，我肯定可以进入下个阶段”。过去， [我们发现人们衡量自己面试表现的能力相当差](http://blog.interviewing.io/people-are-still-bad-at-gauging-their-own-interview-performance-heres-the-data/)。现在，我们打算直接观察诸如面试时长之类的指标，看看它们是否真的重要。 |
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| At my company, [interviewing.io](http://interviewing.io), we’re uniquely positioned to approach technical interviews and their outcomes in a data-driven way. We have a platform where people can practice technical interviewing anonymously. And if things go well, they can unlock the ability to interview anonymously, whenever they’d like, with top companies like Uber, Lyft, and Twitch. | ||
| 在我的公司 [interviewing.io](http://interviewing.io)中，我们用独特的数据驱动方式去分析技术面试及其结果。我们有一个平台，可以让面试者匿名练习技术面试。如果事情顺利，他们可以解锁匿名参加真实面试的功能。他们可以在任何时间参加 Uber, Lyft, 和 Twitch等顶级公司的面试。 |
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Uber, Lyft, 和 Twitch等顶级公司
Uber, Lyft 和 Twitch 等顶级公司
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| The cool thing is that both practice interviews and real interviews with companies take place within the interviewing.io ecosystem. As a result, we’re able to collect quite a bit of interview data and analyze it to better understand technical interviews, the signal they carry, what works and what doesn’t, and which aspects of an interview might actually matter for the outcome. | ||
| 有意思的是，练习面试和真实面试都发生在 interviewing.io 生态系统内。结果，我们可以收集到相当多的面试数据，用来分析并帮助我们更好地理解技术面试：它们传递的信号，什么有用，什么没有用，以及面试的哪些方面可能真的影响结果。 |
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| **Furthermore, no matter what, poor technical ability seems highly correlated with poor communication ability — regardless of language, it’s relatively rare for candidates to perform well technically but not effectively communicate what they’re doing (or vice versa)**, largely (and fortunately) debunking the myth of the incoherent, fast-talking, awkward engineer. | ||
| **另外，无论如何，技术能力似乎和沟通能力紧密相关——不管什么语言，技术表现很好的面试者沟通能力不好，是很罕见的，反之亦反。**, 这很大程度上拆穿了工程师往往笨拙、语无伦次的谣言。 |
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| All in all, this post was our first attempt to understand what does and does not typically lead to an interviewer saying “you know what, I’d really like to hire this person.” Because all of our data are observational, its hard to make causal claims about what we see. | ||
| 总而言之，我们试图探究是什么使得面试官说：“你知道吗，我真的想雇佣这个人。”。这个帖子是我们的首次尝试。由于所有的数据都是观察数据，声称其中有因果联系是很困难的。 |
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@sqrthree @tanglie1993 校对完成，翻译很棒！ |
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@tanglie1993 两位校对者都已经校对好了~ 可以来根据校对意见进行调整了哈 ┏ (゜ω゜)=☞ |
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修改完毕。 |
linhe0x0
requested changes
Jul 22, 2017
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| > * 原文作者：[Aline Lerner](https://medium.freecodecamp.org/@alinelernerllc) | |||
| > * 译文出自：[掘金翻译计划](https://github.com/xitu/gold-miner) | |||
| > * 本文永久链接：[https://github.com/xitu/gold-miner/blob/master/TODO/we-analyzed-thousands-of-coding-interviews-heres-what-we-learned.md](https://github.com/xitu/gold-miner/blob/master/TODO/we-analyzed-thousands-of-coding-interviews-heres-what-we-learned.md) | |||
| > * 译者： | |||
| > * 译者：tanglie1993[https://github.com/tanglie1993] | |||
| > * 校对者： | |||
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| # We analyzed thousands of coding interviews. Here’s what we learned. | ||
| # 我们对数千个编程面试的分析结果 |
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哈哈哈标题要一个就行了啊。应该是添加文章时的失误，麻烦你改下吧。
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| *Note: I wrote most of the words in this post, but the legendary *[*Dave Holtz*](https://twitter.com/daveholtz)* did the heavy lifting on the data side. See more of his work on *[*his blog*](http://daveholtz.net/)*.* | ||
| ** 注意：我写了这个帖子中的绝大部分内容，但传说中的 [Dave Holtz](https://twitter.com/daveholtz) 完成了数据处理的主要工作。我们可以在 [他的博客](http://daveholtz.net/) 中看到他的其它成果。** |
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| At my company, [interviewing.io](http://interviewing.io), we’re uniquely positioned to approach technical interviews and their outcomes in a data-driven way. We have a platform where people can practice technical interviewing anonymously. And if things go well, they can unlock the ability to interview anonymously, whenever they’d like, with top companies like Uber, Lyft, and Twitch. | ||
| 在我的公司 [interviewing.io](http://interviewing.io)中，我们用独特的数据驱动方式去分析技术面试及其结果。我们有一个平台，可以让面试者匿名练习技术面试。如果事情顺利，他们可以解锁匿名参加真实面试的功能。他们可以在任何时间参加 Uber, Lyft, 和 Twitch等顶级公司的面试。 |
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| At my company, [interviewing.io](http://interviewing.io), we’re uniquely positioned to approach technical interviews and their outcomes in a data-driven way. We have a platform where people can practice technical interviewing anonymously. And if things go well, they can unlock the ability to interview anonymously, whenever they’d like, with top companies like Uber, Lyft, and Twitch. | ||
| 在我的公司 [interviewing.io](http://interviewing.io)中，我们用独特的数据驱动方式去分析技术面试及其结果。我们有一个平台，可以让面试者匿名练习技术面试。如果事情顺利，他们可以解锁匿名参加真实面试的功能。他们可以在任何时间参加 Uber, Lyft, 和 Twitch等顶级公司的面试。 |
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| > *“We’re talking about practice!”* -Allen Iverson | ||
| > **“我们正在讨论的是练习！”** ——阿伦·艾弗森 |
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| You might imagine that different languages lead to better interviews. For instance, maybe the readability of Python gives you a leg up in interviews. Or perhaps the fact that certain languages handle data structures in a particularly clean way makes common interview questions easier. We wanted to see whether or not there were statistically significant differences in interview performance across different interview languages. | ||
| 你可能认为，使用不同的语言会使面试得到更好的结果。比如，Python的可读性会对面试有帮助。或者，有些语言处理数据结构的方式特别干净，会让常见的面试问题变得简单。我们想看看，使用不同的语言是否会对面试结果产生显著影响。 |
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| To investigate, we grouped interviews on our platform by interview language and filtered out any languages that were used in fewer than 5 interviews (this only threw out a handful of interviews). After doing this, we were able to look at interview outcome and how it varied as a function of interview language. | ||
| 我们把自己平台上的面试按照语言分组，并过滤掉了面试数量小于5个的语言（这只删去了少量的几个面试）。然后，我们就可以看到面试结果随语言变化的函数。 |
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| Although we don’t do a pairwise comparison for every possible pair of languages, the data below suggest that generally speaking,** there aren’t statistically significant differences between the success rate when interviews are conducted in different languages. **(There were more languages than these on our platform, but the more obscure the language, the less data points we have. For instance, all interviews in [Brainf***](https://en.wikipedia.org/wiki/Brainfuck) were clearly successful. Kidding.) | ||
| 虽然我们没有把所有语言逐对比较，但是下面的数据显示，总的来说，** 不同语言的面试通过率没有显著的差异。 **（我们的平台上还有其它的语言，但语言越没名气，我们的数据点就越少。例如，所有用 [Brainfuck](https://en.wikipedia.org/wiki/Brainfuck) 的面试都很成功。开个玩笑。） |
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| The chart below gives a summary of this data. The x-axis shows the percentage of code executions that were error-free in a given interview. So an interview with 3 code executions and 1 error message would count towards the “30%-40%” bucket. The y-axis indicates the percentage of all interviews that fall in that bucket, for both successful and unsuccessful interviews. Just eyeballing the chart below, one gets the sense that on average, successful candidates run more code that goes off without an error. But is this difference statistically significant? | ||
| 下面的表给出了数据的一个概要。X 轴显示了所有执行次数中没有错误的代码的比例。所以，如果代码执行了3次，但只有1条错误信息，就算在 “30%-40%” 一栏中。Y轴显示所有面试中，成功和失败的面试处于该区域的比例。看一看下面的表就会发现，平均情况下成功的面试者会写出更多的没有错误的代码。但这种差异是否是显著的呢？ |
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好了。 |
linhe0x0
previously approved these changes
Jul 26, 2017
linhe0x0
approved these changes
Jul 26, 2017
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已经 merge 啦~ 快快麻溜发布到掘金专栏然后给我发下链接，方便及时添加积分哟。 |
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我还是找不到发布到专栏的地方啊啊啊啊啊啊。 |
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找小编吧。2333 |
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反馈链接加积分啦 ，专栏权限也给你开通了 |
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Issue: #1830