使用软件指标来衡量结对编程的生产力
可用于衡量结对编程性能的软件指标是什么？
需要明确的
是，是否有任何指标用于专门衡量结对编程，而不用于衡量单个程序员？用于测量的参数是什么？
例如：如果我们想衡量个人编程和结对编程的成本 让我们假设对于单独的编程成本 = x，所以对于一对将是成本 = 2* x
对
，并且对于单独的时间 = t 的时间相同，而对于时间对 = 2* t
所以如果我想使用以下行测量产品尺寸的代码，使用这个度量单位和成对之间有什么不同吗？
任何想法
what are the software metrics that can be used to measuring the performance of pair programming ?
to be clear
is there any metrics used to measure pair programming specifically and does not use to measure the individual programmer ? what are the parameters used for measuring ?
for example:if we want to measure the cost for both individual and pair programming
let's assume that for the individual programming Cost = x so for the pair will be Cost = 2* x
right
and the same for the time for individual Time = t while for pair Time = 2* t
so if I would like to use Lines of code for measuring the product size , is there any different between individual and pair by using this metric?
any idea
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很抱歉打扰您的聚会，但代码行数可能是最糟糕的指标之一，尤其是当人们知道他们的评估或奖金以任何方式与该指标相关时。它积极鼓励剪切和粘贴编程以及其他暴行。这是更多的努力，但为什么不根据您的历史数据根据一个人的预期努力对工作量进行分类呢？或者，让一些程序员同意冗余地完成一些项目，在结对编程和个人编程之间轮换，这样你就可以看到相同的程序员如何完成每个项目。由于一名优秀的程序员可以比两名普通程序员的工作效率更高（我依稀记得 IBM 的一项旧研究得出的结论是，处于最高百分位数的人的工作效率比中位数高 27 倍），因此看到相同的程序员同时使用这两种方法是很有用的。如果通过这样的实验客观地发现正确的流程在损失短期生产力方面代价太大，那么你最好不要为 LOC 指标而烦恼......优秀的程序员知道他们的工作安排是基于这样的意愿可能非常不为所动。
请记住，还涉及无形的东西......结对编程 - 恕我直言 - 迫使人们保持专注，并做出更全面和专业的设计决策。仅仅社交接触就可以帮助缓解无聊，尽管它也可能会给某些人带来压力。我的怀疑是——无论一开始是否更快——它都会带来更好、更可维护的结果。它还确保技能和知识的转移。您应该尽可能地考虑这些无形的方面 - 也许对试验参与者进行访谈或匿名调查。
Sorry to spoil your party, but lines of code is one of the worst metrics possible, especially if people know their assessment or bonus is in any way tied to the metric. It actively encourages cut and paste programming and other attrocities. It's more effort, but why don't you categorise the workload in terms of expected effort for one person, based on your historical data? Or, get some programmers to agree to do a few projects redundantly, rotating between pair-programming and individual, so you can see how the same programmers go at each. As one good programmer can be more productive than two average programmers (I vaguely remember an old IBM study concluding someone in the top percentile was 27x more productive than median), it's useful to see the same programmers doing it both ways. If objectively discovering the right process through such an experiment is too costly in terms of lost short-term productivity, then you're better off not bothering with the LOC metrics anyway... good programmers knowing their work arrangements are being based on such will probably be highly unimpressed.
Remember that there are also intangibles involved... pair programming - IMHO - forces people to keep focused, and to make design decisions that are more rounded and professional. Just the social contact can help relieve boredom, though it may stress some people too. My suspicion is that - whether or not it's faster to begin with - it makes for better, more maintainable results. It also ensures skill and knowledge transfer. You should factor in such intangible aspects as best you can - maybe doing interviews or anonymous surveys with the trial participants.
我想您想问的是如何衡量使用结对编程的团队的效率。如果是，那么答案是效率的衡量并不取决于工作团队正在使用的方法或流程。您应该尝试使用发布后发现的问题数量等指标来评估其产品发布的质量。大概是速度吧
并且，请不要使用代码行来衡量效率。这没有道理。代码行数是产品规模的衡量标准，而不是开发人员效率的衡量标准。这就像用身高或体重来判断你有多聪明一样。代码量和个人效率之间不存在相关性。
如果您对更多软件指标感兴趣，请查看 http://www.sdlcmetrics.org
I guess what you try to ask, is how to measure efficiency of the team that uses pair programming. If yes, then answer is the measurement of efficiency doesn't depend on method or proccess of work team is using. You should try to evaluate the quality of their product releases, with metrics like number of issues identified post release. Probably the velocity.
and, please, don't use lines of code for efficiency measurement. It doesn't make sense. Lines of code is a measure of product size and not developer efficiency. It's like using height or weight to judge how smart you are. There is no correlation between amount of code and individual efficiency.
if you are interested in more software metrics, take a look at http://www.sdlcmetrics.org