Mythical man month: 10 lines per developer day(blog.ndepend.com) |
Mythical man month: 10 lines per developer day(blog.ndepend.com) |
1. Don't know the code base or problem domain. So they'll spend months getting up to speed.
2. Will increase the communication overhead (now each person has to coordinate with up to 9 others, not just 4).
On the small scale of this example, you may see good results. 5 more people isn't a huge amount of communication overhead, and if they're experienced (perhaps even formerly worked on the same or similar project) then you'll see an immediate drop in productivity and then a quick rise back to the new baseline. But will that hold with another 10 people? 20 more beyond that? Each doubling will not continue to halve the time to develop the project, there are limits, and at some point the returns will be negative. The additional people will slow it down. Not just the initial slow-down, but also the new baseline after things settle will be lower than before adding them.
sits back waiting to be told how badly I suck and something about code churn and patterns
If you're pushing up 0 lines of code on a day where you had no meetings or interruptions, and you aren't working on something truly novel and near-impossible, you took the day off on the company dime. And everybody you worked with noticed, and if you do it regularly - they are just waiting for everybody to reach their breaking point with you so they can push to get rid of you. Sure, you'll find a new job and do it again, but you'll still not have anybody's respect.
Who does that?
The correct thing is to manage expectations and then do the work. Unfortunately there are many lazy developers (or people in any sort of job) who won't be productive with even the most simple tasks.
70000/(22*11*10) = ~29 LOC / day
However this math is a bit off because in the course of such 10 years I wrote quite a number of side projects, but still, max ~50 LOC / day.
I don't have hard figures to easily consult but I'd guess that I'm at about your average in total, but then on the days when I'm refactoring/debugging existing stuff, honestly it could be like 3 lines a day, or 5, or just planning/sketching something out.
It's like the old mechanic trope. It's not hard to replace a bolt, what's hard is knowing which bolt to replace and where.
On my most productive (in my own estimation) brownfield days in recent memory, the codebase would generally shrink by several hundred LOC.
I also find that a huge factor in my code production rate on brownfield projects might not have much to do with me, because it's factors like, "Is the code well-documented, easy to understand, and backed by tests that make the intended behavior clear? Or do I have to start by burning days or weeks on wrangling with Chesterton's Fence?"
And, on the other side of it, when is documenting and cleaning my own code to guard some future maintainer from that situation vital, and when am I burning a day of my own time to save someone else only an hour in expectation? All I know for sure in that situation is that, if my manager is assiduously counting LOC, ticket close rate, anything like that, then game theory demands that I should never bother to spend an extra hour on making it more maintainable if I expect that the cost of that decision will be born by one of my teammates. The 10X rockstar developer at a previous team of mine taught me that lesson in a rather brutal manner.
With projects I work on, I'll often write a few thousands lines of foundation in a couple weeks, then I'm adding a line here and there as needed. The first 1000 lines are always easy. The next 10 can take days.
If I'm pounding out the same boilerplate code I've written for every greenfield app, I can go at a phenomenal speed. But if I'm put into code I'm not very familiar with, 98% of my effort is understanding the existing code and 2% of it is making that 1-10 LOC change.
I remember when I was prototyping an OpenGL thing on SunOS or a Renderman on same (maybe Solaris?), I was working ALL of the time and cranking out LOTS of code. Then refactor-refactor, fix technical debt, slowly add features without breaking, more automated tests, more platforms, and then, tada! My effective rate of coding (measured by LoC) was depressingly low.
I guess that I'm happy that it appears that I'm effective and relatively efficient, but I'm not the LoC-cranking-out machine that I thought I was. Sobering.
Where, then, does all this time go? Sometimes it's reading existing code. Sometimes it's learning about a new algorithm by reading blogs and papers. Sometimes it's developing test programs to iron out a bug or test out some new code.
There used to be one chap in the office that got all the hard problems - the seriously hard problems. Some of this was figuring out why USB couldn't transition from low-speed mode to high-speed mode reliably (USB is quite hard to probe due to frequency), or figuring out why the application crashed one in a million boots.
Some of our most valuable developers committed the least amount of code, but saved our arses more times than I can count.
Like measuring productivity by how many hours people spend at their desks. Utterly pointless, but really easy so it becomes the default measure.
Trying to explain to professional managers that there is no foolproof way of measuring developer productivity is a really hard conversation that I've had more than once. I'm assuming the OP's target market is exactly these people, so I don't really blame them for succumbing to the pressure.
Enough to see it, not so many that you can’t see everything else.
Same with lines of code, except that instead of a photographer, there is an observing project manager.
If I had been pressured to start writing code immediately it would have been more difficult to comprehend the codebase, thus slower, or even worse I would have introduced anti-features or bugs.
My experience so far is a team of developers can deliver 30-100 LoC per day of front-end code.
The team size is of little consequence. It's been hilariously consistent across projects and companies I've been in.
Maybe this was true when people were writing operating systems in assembly language - which is the time and context in which The Mythical Man Month was written.
Lines of code per day really is a pretty meaningless measure but having said that there is at least some truth to it, in that any developer who is writing a typical 21st century application and getting only 10 lines of code per day written, should really examine if they are in the right job.
It remains to be seen if our estimates are any better.
500 LOC feature: Add a new route that does something boring; 5 story points.
5 LOC feature: Fix mysterious performance degradation in X; 13 story points.
What do you do to keep up a fast pace in a big project without throwing quality out? They say TDD increases your speed overall, according to a few case studies I found (15% longer to code, but 40% less bugs, so faster finish times overall etc)
"being productive === adding features" is a very negative way to think about development, and exactly the sort of mindset that leads to projects that grind to a halt under the weight of tech debt. Good software comes from all the parts of the process, including maintenance of the code base to reduce drag on features you'll write in the future. When you write requirements, do refactoring, test things, write documentation, etc you are being productive. Your future self will thank you for the effort you put in to the non-code work now.
The goal of software development is to deliver chargeable value to customers.
When you refactor code you do not deliver value to customers and since you have spent time and resources to do that your overall productivity from a business point of view has in fact dropped.
There are multiple Dilbert strips on this topic.
But one of the things that hasn't changed is that we haven't really come up with any better metrics than time spent and nr. of things changed per time unit. There are a lot of people complaining these things are not representative (for the last five decades) but not a whole lot of people coming up with better productivity metrics and even fewer that did the leg work of actually validating their work in something that might pass scientific scrutiny (which is hard). If you do work in this space, you'll find yourself citing articles that are decades old.
These days, I tend to look at the activity statistics on github projects when joining a new project. It tells me in a glance of an eye who are the movers and shakers on a project in terms of lines of code added/removed and amount of commits and the time distribution of those commits. It's not perfect and doesn't tell you the complete story but it it's rarely completely wrong. Usually it's quite easy to spot patterns like Weekends, Christmas, vacations, and that people tend to get back energized from a good break (a little spike in productivity).
Also these numbers confirm the notion of a 10x programmer: a handful of people tends to be responsible for the vast majority of commits and line changes. Not all software engineers are created equally. Diffstats on pull requests tell me a lot as well; though of course these numbers are inflated by e.g. refactorings (more so on languages that have proper tools for this). But refactoring is a good thing and combined with code reviews tell you a lot about the quality of engineering.
Anymore, my daily average LOC is probably negative since I tend to rescue floundering projects. I usually avoid object-oriented (OO) programming whenever possible, as I've found that functional one-shot code taking inputs and returning outputs, with no side effects, using mostly higher order functions, is 1 to 2 orders of magnitude smaller/simpler than OO code.
Also I have a theory that OO itself is what limits most programs to around 1 million lines of code. It's because the human mind can't simulate the state of classes with mutable variables beyond that size. Shoot, I have trouble simulating even a handful of classes now, even with full tracing and a debugger.
I'd like to see us move past LOC to something like a complexity measurement of the intermediate code or tree form.
And on that note, my gut feeling is that none of this even matters. The world's moving towards results-oriented programming, where all that matters is maximizing user satisfaction over cost of development. So acceptance test-driven development (ATDD) should probably be highest priority, then behavior-driven tests (BDD), then unit tests (TDD). On that note, these take at least as long to write as the code itself. I'd even argue that they express the true abstractions of a program, while the code itself is just implementation details. Maybe we should be using user stories implemented per day as the metric.
10 LOC/day is ridiculous. Think about Brad Fitzpatrick, Fabrice Bellard, John Carmack. They would never accomplish anything like they did with those 10 LOC.
You have to have dedication and really good text editing skills. Being smart is nothing if you can't write code fast enough. Good skills with tools like shell, debugger, version control are important as well.
Another problem is that dev collectives these days tend to bully and punish those with higher performance. There are several reasons for that 1) most devs do an absolute minimum just not to get fired 2) job security is a thing, you won't make your project look too simple or complete as this might end your contract 3) at least 90% of hype is from idiots and by idiots. Idiots are a heavy tax on any engineering 4) frameworks, tools and methodologies are often designed for a different scale 5) ceremonia, overcomplication of development processes, treating devs like anonymous, interchangeable units
I'm male in my 40s with a CS degree. I work from home most of the time.
That is, honestly list out roughly what all code the naive way will touch or generate. Without making assumptions about cheating the metric. If you can bring yourself to that, you can probably give better estimates than you'd expect.
Instead, we seem to constantly look for ways to cheat the metric. With no real reason to do so. Other than push the cheating/gaming into a harder sector?
Then when it comes to understanding your software costs - it helps you to put some numbers to features. Yes it is dark art but so is all other financial magic. When it comes to maintenance or re-engineering software - LOCs and past numbers can be useful but are not the only determinant of future development costs. There is the agile backlog / planning poker school of thought which is certainly an improvement and valuable running the project but when it comes to large scale software projects it is not an answer I would like to rely on when the project needs a price tag before day one.
It is one metric. If you work in any company purely run on metrics - if you ask me - run once you see a better place. If you work in any company not measuring what it does - run now!
Not only that, but the higher-level concept I took away is that, given the size of his features (~6k loc), it takes about 75 days to write a feature. Assuming those are workdays, that's 15 weeks, a little over a quarter. And, indeed, tech companies do seem to measure their process and projections in quarters, and everything tends to slip to the right a bit, on average.
Also, the code coverage numbers line up with other estimates I've seen: life-critical systems should have upwards of 95% code coverage. Standard project: 85-90% coverage.
But: -As a 1-man-band I also do the support, documentation, testing, website, marketing etc. So coding is only part of what I do. -I don't think the article defines what a LOC is. Does it include headers? Does it include auto generated code?
How do you score this for lines of code per day. ?
> I've added 700k lines of code and deleted 747k (yay negative!).
Interesting that if you divide the added lines by the 7 years, and figure 250 days/year, he's phenomenally productive
700,00 / 7 / 250 = 400 lines of code per day, sustained over 7 year!
You have to start by defining your terms of reference and make sure you are comparing like with like.
LoC added or removed is not a very good metric for anything.
Except if I see a big negative number on a PR, it is usually a great thing. I still have to check what was removed but it usually mean that things are easier to understand.
Of course, any time I have to add a new Windows Forms dialog to our install/config utility, there's a couple thousand lines of code-behind added to the repo...
3 +
3 +
3 +
3 +
3 +
3 +
3 +
3 +
3 +
3 +
3 +
3 +
3 +
3 +
3 = 45
And so is 3 * 15.
So what's this obsession about it? Is it managers who can't or don't want to properly evaluate the performance of the people they're managing?
A good construction engineer builds a house using LESS concrete that others.
I'd rather be a good software engineer than a "x10 developer".
Many software roles require what I would call Home Depot skill levels. People at Home Depot take semi-finished materials in a kit and fix their toilet, without understanding how it works.
Likewise, some journeyman skilled developer and “code” a sign in page with an API without understanding the engineering process around OAuth.
The problem is many business people don’t understand anything beyond the Home Depot kit... they see stuff on the shelf and don’t understand that at some level that engineering side of the work needs to be done to create something novel. Reinforcing that notion are vendors hawking products.
That said, I probably don't want to be building a house from scratch with my level of skills and should hire someone with specialized knowledge. Likewise it's also an important skill to know when you will be in over your head and when you need to hire someone to get a job done correctly
I think those of us in roles like this can actually bang out a lot more LOC than somebody working on lower level problems, because we aren't solving hard problems, we're using basic data structures and tossing them between (usually/hopefully) well documented interfaces. If that's the case, LOC is just about the worst metric you could imagine.
Expecially because the big picture is easily stated: Write the least amount of clean code while providing value.
(PS: code is liability)
However in many cases, code is for; edge cases, input sanitization, type checking, null checking, graceful failure, logging... etc
Remember, [1] Docker can be implemented in a 100 LOC bash script, that doesn't mean it's a good implementation...
After I left, I heard the company 10x programmer replaced it with 10KLOC of C++. (sigh)
I once had a senior manager who insisted that developers made at least one commit a day (an internal GitHub like tool gamified this: number of lines committed since last month / top committers in the team etc), and those that didn't, had to up their game.
It was frustrating to say the least as this was not the only metric. There were a handful and, frankly, many made a mockery of it by doing just as much or less work than before but achieving or even surpassing the said metrics.
It worked pretty good because there was only a team of 4-5 people on any product at any time so someone just removing TODOs and not fixing the issues pointed out by the TODOs would have been caught.
I used to work for a company that bills their customers for dev hours spent. The software they put together worked fabulously well - in the production of billable dev hours.
In college I was used to be able to churn immense amount of code. Even if most of it was useless, I'm not well adjusted for long productive-less periods.
How did your manager react to these times ? no remarks ? nagging ? trusting ?
It's also a hell of a lot of fun... which is why it's not really what you get paid for. What you get paid for is the long, tedious slog of the real world: maintaining existing business logic, teasing out user requirements in a domain you don't really understand, dealing with other developers who have different preferences and skill levels, doing variations of the same thing instead of exploring new domains and technologies. You spend a lot of days in meetings that should have been emails.
It's not all drudgery, and it's both more fun and better paid than 99% of the jobs in the world, but it's not picking the wondrous low-hanging fruit that you did in college.
For me, it is really a top down approach. I can work on goals that take years to accomplish. But the key is to break them down into smaller and smaller bits until you have work items that show progress on a small enough scale to be easily observable. And part of this is sometimes research, so I can't measure myself in terms of code or features. But each task usually has a way to define progress.
It is of course the main metric for global warming, but it can be used badly or very well. Just like Lines of Code, it's hard to even get the measurement right. Do you measure it in the sun, or the shade? Do you measure it in a city which is relevant to the where most people feel the effects, or in the country so you get a repeatable environment. Similarly does LOC include comments and blank lines, what about patches - how do you count them? In terms of LOC per day, so you measure a single person who is churning out the code, or the entire team including the designers and documenters, and do you include the time after the project is completed doing support because of bugs?
I don't think you can blame the "temperature metric" for the bad ways it's measured or used. And I don't think you can blame Lines Of Code all of it's bad outcomes either.
I'm not sure it is that far off over several years. If you look at Google, and say there are 52 * 5 days * 10 lines of code, 2600 lines of code per developer. Extrapolate that to 20 years times how many developers and list on code that is currently used, would it be that far out?
People over-estimate the sustainability of short term coding lines per day, versus multi-year coding.
Here's an example: https://github.com/sumatrapdfreader/sumatrapdf is code written by 2 people (me and another guy).
It's written, documented, tested and bug fixed.
It's 110k lines of code. And it's tight. Good luck removing 10k lines of code and not loosing any functionality.
Assuming 10 lines per day and round-the-clock 365 days of working, that's 30 man-years of work. 15 years for 2 people.
I didn't spend 15 years writing it. It's a part-time effort over 10 years.
The 10 lines per day is off by at least an order of magnitued.
And I don't claim to be spectacularly productive. Jonathan Blow wrote 90k lines of code for Braid in 1 or 2 years.
Are you sure about that?
I don't think so.
I have not read it for years, but my vague recollection of The Mythical Man Month is that 10 lines a day as a full time professional programmer is a reasonable expectation if you are writing IBM mainframe operating systems in assembly language in the 1970s.
It not meant to be saying that hey a programmer is busy with lots of other things like testing documentation etc.
Brooks actually meant it, and it was true, at the time, with 1970s hardware, with 1970s development tools, with 1970s collaboration, 1970s compilers/assemblers, 1970s source control, with 1970s level of understanding of computers and software, with 1970s waterfall style project management. And, critically, writing your 10 lines as part of a (relatively speaking) gigantic project for the time. Back then projects did not come much bigger than writing an operating system.
Can you imagine trying to get your bit written of some gigantic project where probably no-one has any idea what the fuck is going on, where the source code is, what version is what, who is working on what and how its all meant to tie together. The miracle is that they could get any operating system at all written. Many, many operating system projects failed entirely in the 1970's and 1980's.
I'm happy to be proven wrong, cause as I say I haven't read that book for a long long time.
In terms of lines of changes total in git merges, multiply it by 10 or more.
edit: updated loc numbers to include some file types that I forgot about
I spent a day with just a pencil and paper, considering each detail of the algorithms and came up with several key insights which reduced the whole thing to about 1k lines of code. The reduction was a combination of C macros (which I wouldn't use today, but I'd use higher-order functions to accomplish the same thing now) and just smart generic code (no special handling of an add operator versus a multiplication operator, they were both binary operators; differentiating the output for each case happened in one place at the end).
That was when I found out I liked deleting code. I'll happily reduce a code base by 90% if the result is clearer and easier to maintain or extend.
And then 'getting rid of code' is the most wonderful feeling in the world.
Getting rid of unneeded code is like clipping toe-nails that are way too long. (It must be done!)
It's like cleaning a disgusting floor in the bathroom (it can't wait).
It's like fixing ugly grammar and spelling mistakes.
It's like sanding and painting that old fence the really needed some attention.
If its taking 100 lines to do something and I can rewrite in 10, then that's a lot less places for bugs to hide. That's less than one screen of code for the next person to read / comprehend. In most cases its a win (though I will admit that sometimes comprehension is easier with less concise code).
At some point, I close the patient, discarding a lot of that. At the end of the day, ideally it looks pretty minimal--just what's needed and no more.
Does anyone give a shit about metrics any more? I seem to recall the whole metrics thing fizzled out entirely about 15 years ago.
What's that law? Something like "Once a number becomes a goal, it ceases to be a useful measure."
I also know these examples and I know the people who are writing them. "Copy & Paste" coding is just more convenient for them instead of writing a loop, fizzling with brackets, indation or whatever. They don't produce high entropy code.
1) use silly, useless metrics that are of a sort management will accept anyway,
2) uselessly tag along with initiatives in areas that are easier to measure (sales, marketing kind of though their metrics are still usually bad, just no-one cares),
3) start a year ago gathering data for a baseline for bad development metrics,
4) start 2-3 years ago gathering data for good development metrics, though they’ll probably still be pretty limited and narrow.
We picked 1 and 2 of course. What a waste of time. I wish anyone who wanted to be more than a line worker anywhere had to answer some basic questions about games and measuring things. Not just in development, managers and directors everywhere are, on average, terrible at it as far as I can tell.
I can write boilerplate much much faster than I can type, either I or the community have scripted that shit :D
You can't rewrite much without the risk of breaking things, so you need a lot more testing. There's a lot of value in the code, so there's more to leverage to add functionality, but the other side is there's more to learn and analyze to efficiently leverage. And when there's lots more teams working on the code, there's more of it and it changes faster than you can expect to fully comprehend; you're continually analyzing and learning.
When I'm off on my own, spiking a new service or library, I can churn out 10k to 20k lines a month; it's very easy when it's greenfield, when there's no team coordination overhead, when you don't need to refactor other people's stuff when you redesign, you don't need to go through full code review cycle, the whole thing fits inside your skull etc. But that doesn't last forever, and it's not business as usual for feature development.
Fixing a gnarly bug might take several days of investigation and end up with a 1 line fix; and delivering that fix might make the difference in avoiding 6 or 7 figures worth of revenue churn. Does that mean it's 10000x less productive?
It's not that far off. I'm taking your example as rather confirming the point rather than refuting it.
When I worked on a big project (several million lines of code) I routinely would code less than 10 lines per day.
For you. For the average developer, on the large scale, I think it is closer to the truth than you'd think.
(Also, not a fan of back-jumping 'goto's or putting executables in git repos. And s/supressing/suppressing/g)
You seem like a fine programmer, but I don't think this invalidates MMM.
Edit: you made Sumatra?? I’ve been using that for a decade, thank you so much for creating it! I put it on all my family’s machines, it’s the fastest PDF reader I’ve found
If you want to be a team lead, though, or even just have people follow your lead, I find that not only do you want to worry about these costs, but you need to talk openly about them, and be seen addressing it. Most devs follow the ones they trust, no matter what title they have.
On all the projects where we tried to build people up instead of get shit done, we were consistently getting more shit done at the two year mark, if not sooner. Any idiot can ship a version 1.0.0, but it takes some talent (and luck) to ship version 2.3.0
From what I’ve seen, Postgres followed a similar model, and if you look at the performance benchmarks over time, it has progressively narrowed the gap with each major release. That kind of momentum is something worth sacrificing for.
This may depend on the extent to which your organization conforms to the Peter principle.
I have no idea how I would try to count that if I wanted to measure “productivity.”
Apply a few of these kinds of comparisons using different metrics, and you may be able to improve your estimates.
The way you put it, you're optimizing for only one side of the books. The fact is that the value in a company is not in minimal clean code; it's in a recurring revenue stream, and ideally profits. Provide the most value with code which has low interest payments. Everything else being equal, smaller code has lower interest payments, but everything else isn't always equal. And depending on cash flow and market opportunity, maximizing value and to hell with minimal clean code - throwing money & devs at the problem - can make sense.
I think the spirit of the comment you replied to was closer to the "clear and concise" methodology rather than the "as short as is humanly possible" methodology.
Few reasons:
1. I find devs (including me) tend to do too few commits instead of too many. Smaller, tighter commits are better, but it's really tempting to try and do an entire feature in one commit.
2. If someone has spent a couple of days working on something without committing it, I'd be concerned that they're stuck, or spinning wheels. I'd check in on them. Not in a bad "you're not working hard enough" way, but in a "do you need help?" way.
3. If someone often spent more than a day without writing anything they could commit, I'd check in on them. Again, like 2. above, not in a "dammit work harder!" way, but maybe it's an indication that they're getting handed the really hard problems, or that they need some more training, or that they're going through some personal stuff, or something.
but measuring lines in each commit is pointless/futile, as is measuring number of commits in a day.
> If someone has spent a couple of days working on something without committing it, I'd be concerned that they're stuck, or spinning wheels. I'd check in on them.
This is more reasonable. Working without review leads to worse fiascoes the longer it goes.
Also encourages testing work to be formally coded and just done interactively. If a test is good enough to compile, commit it as work in progress even if it has a bug and/or incomplete if you've reached a good point you'll like to build upon. Make a tweak, compiles, commit it.
If you've spent most of your day writing a test, but it's complicated and will require even more work before you'd even try to compile and run, commit it WIP before going home.
'This code was already worked on and we paid for it... it can't surely be that bad'
If you deliver something broken it's better than delivering nothing... you'd be surprised how often we get 'We'll improve it later' compared to 'You didn't deliver anything?'
You do though, by reducing the future cost of delivering features. That has tremendous value. Find a company that sees good engineering as a long term investment rather than a short term way of extracting money from customers and you'll enjoy software development a lot more.
It absolutely is customer facing value. If shipping this feature 2 weeks later means you can ship the next 10 features in 6 months, and the alternative is shipping this feature today but with so much tech debt that you ship the next 10 features in 12 months, then that is value the customer will see.
Similarly, if your code is so shitty that you're adding bugs to the backlog faster than you're able to fix them, that's a negative for the customer. If instead you spend 2 weeks refactoring so that your bugs+ rate is lower than your bugs- rate, that's customer value right there!
I cannot understand how you don't seem to understand this basic premise of a b2c relationship. Users don't just care about the features they have today, and if your competitor gets to market slower than you but has twice the features a year or two later (due to less tech debt), you're gonna be left in the dust.
reputation and trust are hard to measure, and the effect is delayed. unless you have the killer app or feature, with the internet now, word will get out. many a company has tanked their reputation.
iteration speed also makes you vulnerable to be leapfrogged. Azure vs AWS seems to me to be this. a lot of Azure stuff is great now, some of that is hindsight, but real innovation at AWS is also rare. their developer tools, aka code*, are completely underwhelming. as is cloudwatch. ec2, s3, dynamo, and general lock-in are just enough to keep a lot of people.... for now.
Refactoring is an internal activity. It's part of the cost of development.
Yes I will, because the cost of development will be lower. That makes my customers happy so they give me more work. I'll also have fewer defects which improves my reputation which means I can charge more.
No, your customers don't care two hoots about that.
I mostly write software for SaaS companies. Their customers (the end users of the software) don't care about it much besides seeing fewer problems and getting to use better software, but my customers (the people who own the software) really do.
Do most jobs have a team chat to talk about it before going into actual work ?
At their most objective best, everyone on a given development team can gain some insight into the work of others, and how hard it might be.
These session can also be a great way to share knowledge, as developers with different levels of experience and specialisations collectively examine high level goals.
In that, you all have a fair opportunity to either share opinions on the best way to achieve a task, or just merely learn something from someone else about tools or techniques you're unfamiliar with.
And for insightful managers, it's also a great opportunity to communicate high level aims and objective, and occasionally, also break those objectives down, transparently, and explore them.
At worse, estimation sessions can be used as a tool to bully dissenting or inquisitive coders.
Even in it's least positive guise, collective estimation sessions are still valuable. At the very least, you have the opportunity to agree, as a group, on what is, and what isn't going to take 10 or 1000 odd SLOC. You'll also have a better idea (if only slightly better in some cases), of how long that n SLOC will take to write.
I once worked on a product and identified an ability to eliminate 100K lines of poorly written, inconsistent tracing code into a robust ~250 line file using AspectJ. Management threw a sh-t fit and thought the risk was untenable.
I think what had happened is somebody had designed the file and everybody else followed suit patching stuff on - the entire codebase for that app was well below average. they had front end devs who didn’t know any JavaScript. In 2016. I lasted 6 months before I nope.png’d the fuck out.
It’s still not the worst application I’ve ever worked on though
For some reason all calls were dog slow. Like minutes for simple pages.
Profiling revealed the class in question - and we were spending all our time in deserializing strings.
Copied the latest version of that class from the FB repo and luckily the interfaces were the same.
Worked for the next two years until we finally deprecated the PHP stuff.
It was a support nightmare, so we built a common library and collapsed the code base by 70%. Each tool was probably in the -8k eslocs range. Thankfully it wasnt c++.
1: Google is giving a much higher number but they all seem to go back to the same estimate which is more hand-wavy than a printed source I found in college when researching it. Sorry I don't have it to source. The other number from that source was 1800 published words per day if you start from his first published book, which is absurd, since new authors tend to be much less prolific.
I've another thought on the topic as well, which is that I have a friend who hired a lot of former newspaper journalists circa 08 when there were mass layoffs in that industry. He said they were able to most consistently churn out content for his book over other writers, but that it was significantly lower quality, and needed a lot more rework and polish. For him the tradeoff was worth it, and he organized his time and resources around this increased quantity. But this adds to the idea that you really can't look at pages/day (or LOC/day) on an individual basis either, since it's the whole pipeline that matters. And if you really want to improve total output, you need to look at variables outside of individual contributors. Things like code reviews and QA can perhaps greatly increase total output.
I'm no expert in aircraft, but I'm guessing that in both cases the relationship between progress and the metric in question is logarithmic: The first bits to be put place represent the bulk of the (weight|LOC), but only a relatively small percentage of overall time and effort.
;)
(At least, that's how it tended to go for the ones I was making as a kid.)
It's surprising how few managers value objective estimation. But the problem I suppose, is what it does to the working relationship the rest of the company has with their software development team.
Basically, to allow a team of developers such an 'indulgence', every worker in a given business, including senior managers, have to accept that all interactions with the development team, are led by the development team.
That takes a lot of trust, and you'll rarely find that level of trust outside of a startup.
Edit:
I'm not arguing that refactoring isn't necessary or important. It is. But it should be kept to a minimum because it really is a pure cost and does not deliver anything of value to end users.
Your customers are the engineering teams of software business. They sometimes need to refactor their code. But their business would prefer they didn't because that's money spent on something invisible to end users (the end customers).
Specifically in my own case, the company I work for writes software for (mostly) software product companies. When we plan what to do in a sprint 'refactoring' is part of that. We literally charge for the time we spend doing it. How long we spend refactoring is agreed by the customer's project / product manager. They understand why it's necessary and important, and they want us to do it.
Plus, AspectJ is something that you have to be careful with. It injects code at the start or end of methods that can do arbitraty things and the method source code doesn't indicate that this is happening. So it has a great potential for code obfuscation.
In C#, with the various frameworks - including on the API level with ASP.Net - you can use attributes to decorate the classes/methods with your aspects and it’s pretty easy to see what it’s doing.
You get the runtime binding basically by just using dependency injection as you always do.
I have yet to find any equivalent to this .NET world. Especially of you're using EF. Either you use ADO and have your try/catch/finally with manual transaction management, or you have the EF context which is just one big blob you hope succeeds at the end.
It just came back to EF Core in 2.1
https://www.google.com/amp/s/codewala.net/2018/05/06/transac...
[Transaction]
DoYourBusinessWork() { ...; AlsoAudit(); }
[Transaction(RequiresNew, NoRollbackFor(AuditException)]
AlsoAudit() { ... }
You could put the logic in attributes but I don’t consider a transaction a cross cutting concern. It would create a spooky action at a distance situation.