## Ranking programmers
-There are many metrics which folks use to rank programmers. You've likely seen these metrics manifest themselves in different ways: competition sites, numbers of commits to projects, productivity measurements, time to turn-around code, and good ol' fashioned gut feelings. We do it to ourselves and others. We compare our work against the work of our peers and folks that we admire. But that can lead us to make comparisons that aren't objective or based on all of the data. I can compare myself against folks who do low-level programming and find that I don't measure up in that realm. Never mind that I haven't done a whole lot of low-level programming; the comparison is valid. Or I can compare myself against folks who were mentored by programmers whose names are legendary in the field. I will find gaps between my knowledge and their knowledge, because I didn't have access to those mentors (or worse: I didn't take advantage of the mentors that I did have access to. Whoops!). Comparisons like these are unhelpful and lead us into punishing ourselves for not being someone else. We look at our projects and our history and conclude that we're not that other person, nor could we ever be that other person.
+There are many metrics which folks use to rank programmers. You've likely seen these metrics manifest themselves in different ways: competition sites, numbers of commits to projects, productivity measurements, time to turn-around code, and good ol' fashioned gut feelings. We do it to ourselves and others. We compare our work against the work of our peers and folks that we admire, but that can lead us to make comparisons that aren't objective or based on all of the data. I can compare myself against folks who do low-level programming and find that I don't measure up in that realm. Never mind that I haven't done a whole lot of low-level programming; the comparison is valid. Or I can compare myself against folks who were mentored by programmers whose names are legendary in the field. I will find gaps between my knowledge and their knowledge, because I didn't have access to those mentors (or worse: I didn't take advantage of the mentors I could have accessed. Whoops!). Comparisons like these are not helpful and lead us into punishing ourselves for not being someone else. We look at our projects and our history and conclude that we're not that other person, nor could we ever be that other person.
-The major problem with ranking programmers (or really anything for that matter) is that ranking systems are based on one set of criteria. There is no real standard for ranking programmers. Sites that rank programmers based on numbers of problems solved or difficulty of problems solved have only determined that there are a set of programmers who really enjoy solving these sorts of problems. They've also determined these sets of programmers will spend the time and effort to solve these problems and will be competitive in solving these problems. It tells us little about the programmer's abilities outside of that domain.
+The major problem with ranking programmers (or really anything for that matter) is that ranking systems are based on one set of criteria. There is no real standard for ranking programmers. Sites that rank programmers based on numbers of problems solved or difficulty of problems solved have only determined that there are a set of programmers who really enjoy solving these types of problems. They've also collected a set of programmers who will spend the time and effort to solve these problems and will be competitive while solving them. It tells us little about the programmer's abilities outside of that domain.
-We can find other metrics to rank programmers. One classic metric is reviewing how many lines of code a programmer used in order to solve a problem (this is sometimes referred to as "code golf", where the fewer number of lines of code the better the solution). Or we can see how "clean" the solution is (clean being another nebulous term). We can look at the Big O notation of the code that a programmer generates or how well the code adapts to various circumstances. We can count the number of cycles a particular piece of code takes in order to run and benchmark it against similar code. Very little of this tells us anything about the programmer themselves. What it does tell us is that the programmer has experience that lead them to that particular solution. It tells us that the programmer has seen these sorts of problems before and cared deeply enough about the problem to think hard enough about how to make a better solution. We learn that the programmer devoted time and energy to practice these sorts of problems. What it doesn't show us is an overall measurement of the programmer's skills or abilities. It's similar to the apocryphal tale of a brilliant professor. This professor was an absolute genius in his field and was one of the go-to people for answers about his subject. But despite his brilliance he was unable to understand how to change a tire on a car. Does that mean the professor was not as brilliant as folks claimed him to be? Hardly. It means the professor spent more time thinking about his profession than he spent thinking about changing tires. The same is true for programmers. If a programmer spends most of their time solving a particular set of problems they will eventually become skilled at those sorts of problems. But if they struggle with a different sort of problem it doesn't discount their overall skills; it just points out areas they might want to work on.
+There are also other metrics to rank programmers. One classic metric is reviewing how many lines of code a programmer used in order to solve a problem (this is sometimes referred to as "code golf", where the fewer number of lines of code the better the solution). We can argue how "clean" the solution is (clean being another nebulous term). We can determine the "Big O notation", a notation used to describe the performance or complexity of the algorithms that a programmer used in their code. We can stress test the code to determine how well the code adapts to various circumstances. We can count the number of cycles a particular piece of code takes in order to run and benchmark it against similar code. Very little of this tells us anything about a particular programmer. What it does tell us is that the programmer has experience that lead them to that particular solution. It tells us that the programmer has seen these sorts of problems before and cared deeply enough about the problem to think hard enough about how to make a better solution. We learn that the programmer devoted time and energy to practice these sorts of problems. What it doesn't show us is an overall measurement of the programmer's skills or abilities. It's similar to the apocryphal tale of a brilliant professor. This professor was an absolute genius in his field and was one of the go-to people for answers about his subject, but despite his brilliance he was unable to understand how to change a tire on a car. Does that mean the professor was not as brilliant as folks claimed him to be? Hardly. It means the professor spent more time thinking about his profession than he spent thinking about changing tires. The same is true for programmers. If a programmer spends most of their time solving a particular set of problems they will eventually become skilled at those sorts of problems. But if they struggle with a different sort of problem it doesn't discount their overall skills; it just points out areas they might want to work on.
## Measuring programmer output
projects / themediocreprogrammer.git / commitdiff