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I often find that I do a less than complete work on a feature, especially in the Design phase. I detect several reasons:
I'm over-optimistic
I feel the need to provide quick solutions, so sometimes I fool myself into thinking the design is fool-proof when in fact it's still full of holes, just to get the job done faster. Of course I end up paying dearly later.
I'm aware of this behavior of mine for some time, yet I still find I don't manage to compensate. Have you encountered similar problems? How do you approach solving them?
I use a couple of techniques. The first is a simple paper to-do list. In the morning I write down my tasks for the day. I try to work on a task until I can cross it off. I cross it off only when I'm done to my own satisfaction. My to-do list helps me stay focused. When an interruption comes in, I can consciously choose whether it is important enough to interrupt what I'm doing now.
The second technique I use is to give up on the idea of "done" for a design. Instead, I focus on what I've started calling "successions", where a design goes through predictable stages. Each stage supports the current functionality well and will be succeeded at some point by the next stage. This lets me do a good job, a job I can be proud of, without over-designing.
I have the intuition that there is a small catalog of such successions (like http://www.threeriversinstitute.org/FirstOneThenMany.html) that would cover most of design. In the meantime, I try to remember that "sufficient to the day are the troubles thereof".
I run into this problem a lot.
My solution is a notebook. (The old fashioned paper kind).
I write out how I'm planning on implementing the solution as an bulleted overview list, and then I try and flesh out each point on the list.
Often, during that process, I come across issues I hadn't thought of.
Of course, the 80/20 rule still applies... I still come across things when I'm actually doing the implementation that hadn't occurred to me, but with experience these tend to diminish.
EDIT: If I'm still not sure at the end of this process, I put together a throwaway prototype testbed... It's important to make sure it's throwaway, because otherwise you run the risk of including some nasty hacks in your real codebase.
It's very common to miss edge-cases and detail when you're in the planning phase of a project, especially in the software development field. Please don't feel that this is a personal failing; it's something endemic.
To counter this, many software development methodologies have emerged. Most recently there has been a shift by many development teams to 'agile' methods, where there is a focus on rapid development with little up-front technical design (after all, many complexities are only discovered when you actually begin developing). I'm currently using the Scrum system, which has been excellent in my small team:
http://en.wikipedia.org/wiki/Agile_methods
http://en.wikipedia.org/wiki/Scrum_%28development%29
If you find that your organisation will not accept what they may regard as a radical shift in approach, it may be worth investigating whether they will agree to the development of a prototype system. This means that you could code up a feature to investigate the technologies involved and judge whether it's feasible, without having to commit to full development, a quality bar, testing schedules etc. The prototype should be thrown away once the feasibility has been proved or disproved, then proper development may begin, including all that you've learned in the process.
If your problem is more related to time management, then I'd recommend the Getting Things Done approach (http://en.wikipedia.org/wiki/Getting_things_done). This is pragmatic and simple, concentrating on making you productive without overloading you with information that isn't immediately relevant to your current work. I've found that I get overwhelmed with project/feature ideas at times and it really helps to write everything down and file it for a later time when I have the resources available to work effectively.
I hope this helps and best of luck!
Communication.
The best way to not rush yourself into programming mistakes is communication. Yes, good ol' fashioned accountability. If another person in the office is involved in the process, the better the outcome. If a programmer just takes on the task without any concern for anybody else, then there is a higher possiblity for mistakes.
Accountability Checklist:
How do we support this?
Who needs to know what has changed?
Why are we doing this in the first place?
Will there be anybody who doesn't want this changed?
Will someone else understand how I did this?
How will the user perceive and use this change?
A skepticle comrad is usually good enough to help. Functional Specifications are good, they usually answer all of these thoughts. But, sometimes a conversation with another person can help you with it and you can get changes out the door faster.
I have learned, through years of mistakes (though still making them), that almost anything I want to use repeatedly, or distribute, needs to be designed properly. So getting burned enough times will end your optimism.
When getting pressure from management, I tell them I will have to put in the thought anyway, so I should do it when it's cheap. I think on paper as well, so I can actually prove that I'm doing something and it keeps my fingers on the keyboard, both of which provides a soothing effect to management. ;-)
At the risk of sounding obvious - be pessimistic. I had a few experiences where I thought "that should take a few hours" and it ended up taking a couple days because of all the little things that pop up unexpectedly.
By far the best way I've found to manage things is to (much like Andrew's answer) write out the design and requirements as a starting point. Then I go through and look for weak points in the design, gotchas and additional use cases etc. I try to look at this as a critical exercise - there's no code written yet, so this is the time to be totally ruthless and look for every weak point. Look for error conditions you'll have to handle, and whatever amount of time you think it will take to complete each feature/function, pad that amount by a lot. I've had times where I've doubled my initial estimate and still not been that far off the mark.
It's very hard as a programmer to realistically project debugging time - writing the code is easy to estimate, but debugging that into functioning, valid code is something else entirely. Therefore I find there's no exact science to it but I just pad tasks by a whole bunch, so that I have plenty of breathing room for debugging.
See also Evidence Based Scheduling which is a fascinating concept in scheduling developed by FogCreek for their FogBugz product.
You and the rest of the world.
You need more a more detailed design, more accurate estimate, and the willingness to accept that sometimes the optimal solution is not necessarily the best solution (e.g., you could code some loop in assembler to get optimal performance, but that's going to take a lot longer than just doing
for (i=1; i<=10; i++) {}
). Is the time spent doing it really worth it for an accounting package over a missile system.
I like to designing, but over time I've found that much design up front is a lot like building castles into the sky - it's too much speculation, however well-educated, missing critical feedback from actually implementing and using the design.
So today I'm much more into accepting that while implementing a design I will learn a lot of new stuff about it, and need to feed that learning back into the design. Doing that is a skill that is fun to learn, including the skills to keep a design flexible by keeping it simple, free of duplication and cohesive and decoupled, of changing the design in small, controlled steps (=refactoring), and writing the necessary extensive suite of automated tests that make this kind of changes safe.
This seems to be a much more effective approach to me than getting better at "up front design speculation" - and addtionally it makes me equally well prepared for the inevitable moment when the design needs to be changed due to a simply unforseeable change in the requirements.
Divide, divide, divide. List all the steps that will be required to finish the project, then list all the steps those steps will require to be concluded, and so on until you reach atomic items you are absolutely sure you can finish in a day or less. Add the duration of all these values to arrive at a length of time.
Then double it. Now you have a number that, if depressing, is at least somewhat realistic.
If possible "Sleep on your design" before publishing it. I find after I leave work, I usually think of things I have missed. This usually happens while I am lying in bed before falling asleep or even while showering the next day.
I also find it valuable to have a peer/friend that I trust review what I have before distributing it. Somebody else almost always sees something I didn't think of or miscommunicated.
I like to do as others stated here. Write down in pseudo code what the flow of your app will be. This immediately highlights some detailed areas that may require further attention that where not apparent up front.
Pseudo code is also readable to business users who can verify your approach meets their needs.
Using pseudo code also creates a nice set of methods that could be put to use as an interface in the final solution. Once the pseudo code is fairly tight, look for patterns and review some common GOF patterns. They do not have to be perfect but using them will sheild you from having to rewrite the code later during the revisions that are bound to come along.
Just taking an hour or two write psuedo code, yields some invaluable time saving pieces later on:
1. An object model emerges
2. The program's flow is clearly defined for others
3. It can be used as documentation of your design with some refinement
4. Comments are easier to add and will be clearer for someone else reviewing your code.
Best of luck to you!
I've found that the best way to make sure you've chosen a good design is to make sure that you understand the problem, know the limitations you have, and know what things are must-haves vs. nice-to-haves.
Understanding the problem will involve talking to the people who have the need and keeping them anchored to what needs to get done first instead of how they think it ought to get done. Once you know what actually has to happen, you can go back and talk over requirements about how.
Knowing your limitations may be quite easy: needs to run on the iPhone; has to be a web application; needs to integrate with the already-existing Java code and deployment setup; and so on. It may be quite difficult: you don't know what the potential size of your user base is (hundreds? thousands? millions?); you don't know whether you'll need to localize it (though if you're not sure, assume you will have to).
Must-haves vs, nice-to-haves: this is possibly the most difficult part. Users very often have emotional attachments to "requirements" ("It should look just like Excel") that are not actually part of the "has to happen" stuff. You often have to juggle functionality vs. desires to get an acceptable implementation. You can't always give everyone a pony.
Make sure you write all this down! Even if it evolves along the way, or the design is small, having a "this is what we're planning to do now" guide to refer to when you need ot make a decision about committing resources makes it easier to restrain yourself from implementing a really cool whiz-bang feature instead of a boring must-do.
Since you recognize that you feel the need to provide a quick solution, perhaps it will slow you down to realize that you can probably solve the problem faster and deliver it sooner if you spend more upfront time in design. For instance if you spend 3 hours designing and 30 hours writting code, it probably means that if you spend 6 hours designing you might need to only spend 10 hours writing code. (These are not actual figures just examples). You might try to quantify this for yourself on the next few projects you do. Do a couple where you behave as you normally would and see what ratio of design/codewriting/testing&debugging you actually do. Then on the next project deliberately increase the percentage of time you spend on design phase and see if it does shorten the time needed for the other phases. You will have to try for several projects on this as well to get a true baseline since the projects may be quite different. Do it as a test to see if you can improve your performance on the the other phases and thus deliver a faster product if you spend 20% more time or 50% more time or 100% more time on design.
Remember the later in the process you find the problem with a design the harder (and more time-consuming) it is to fix.
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I'm currently working in a piece of code where both logic and data access are present in the GUI classes. Obviously, I would like to improve on this situation.
The current structure is basically:
Big ball of mud
The ultimate goal is to achieve a DDD-like structure:
DAL
Domain model
Service layer
Presentation model
GUI
So, how would you attack the problem?
Big bang
Define the structure for the final state and push code to its ultimate home.
Divide and conquer
Try to separate the big ball of mud in to two pieces. Repeat until done...
Strangling
Strangle the classes (as described in http://martinfowler.com/bliki/StranglerApplication.html)
Never attempt "Big Bang". It almost always blows in your face, since it's a high-risk, desperate measure when everything else has failed.
Divide and conquer: This works well ... if your world has only two sides. In real software, you have to conquer so many fronts at the same time, you can rarely afford to live in a black-white fantasy.
I guess I've been using something like "Strangling" for most of my career: Gradually morphing bad old code into shiny new code. Here is my recipe:
Start somewhere, it doesn't really matter where. Write a few unit tests to see how to the code really behaves. Find out how often it does what you think it does and how often it doesn't. Use your IDE to refactor the code so you can test it.
After the first day, make a guess whether you've started at the right place to take this monster apart. If so, go on. If not, find a new place and start over.
Advantages of this strategy: It works in small steps, so the risk can be kept in check and if something breaks, if has to be in the code you've been working on last week.
Disadvantage: It takes a whole lot of time and you will feel frustrated because often, progress will just seem so slow until the "knot" pops and suddenly, everything starts fall into place as if by magic.
I'd never heard of the term 'Strangler Application' - I like it. Where possible this would always be a good approach, it certainly minimises risk and is quite pragmatic, chipping away at the big edifice piece by piece.
Where that doesn't work in my experience is where reasonably significant changes are needed right away - changes that will require a bit of refactoring (or a lot of hacking). In that situation I've often found the changes I needed to do were right at the heart of the big ball of mud and there was no option but getting dirty - even what should have been standard maintenance or minor enhancement changes were just horrible and a major refactor was the best option.
For those cases, I'd go with divide and conquer - the first goal I always aim for is testability, once you have that all the rest is so much easier. In fact, that is often one of the main drivers I have for refactoring away from the big ball of mud – that sort of code is often very nearly un-testable, hopefully there are example UI inputs and outputs, but sometimes even that is missing.
So when faced with code where everything is lumped into the UI I usually start by factoring discrete units of functionality into classes and methods, then pushing those parts of code down into a domain or service layer. Doing it bit by bit greatly reduces the chance of breaking something and makes it easier to pin-point where the breaking code was when things do go wrong.
Run whatever test cases you have available at the end of every change and make sure you are still meeting some sort of baseline.
If you write good unit tests as you go you can start reducing the scale of the problem and I've found that it soon becomes practical to take the strangler approach - with decent unit tests or at least the right framework to allow the writing of decent unit tests it becomes much more practical to gradually replace parts of functionality.
I stumbled upon "the Mikado Method" that seems promising for attacking problems of this nature.
http://mikadomethod.wordpress.com/
There is also a talk about the Mikado Method from Øredev 2010.
http://oredev.org/2010/sessions/large-scale-refactorings-using-the-mikado-method
Depends on whether you have to have always a working state, so that you can bug-fix and deploy whenever neccassary, then Devide and Conquer would be a good solution. If you can maintain the old code, while working on a new one (and have the disciplin to apply bug-fixes to both code-bases) a re-write may be a better solution.
If by refactoring, you mean improving the code without modifying the functionality, I'd start by creating an automated regression testing base line. There are plenty of tools out there to help with this. I use TestComlete though there are good cheap alternatives.
Having established a regression test baseline, personally I would then go with divide and conquer, as it in my experience it is the most likely to succeed. Once you have a testing baseline, it matters less which approach you choose.
For me it depends on the situation.
If it is a very small project I'd be tempted to just rewrite it from scratch...however you don't often have that luxury.
Failing that, I'd go for chipping away at it piece by piece. I'd write unit tests to verify the existing functionality and slowly use TDD to transform the code into an elegant and well designed system. Depending on how long this process is going to take it will probably start to look like the StranglerApplication you mentioned above.
BigBang is very risky as you have no easy way of verifying that the updated system does the same thing as the old one.
Divide and Conquer is less risky than BigBang...but if its a large enough system it can wind up being just as problematic as BigBang.
Big bang / Big re-design / rewriting the SW ... or whatever other names will not work for a living SW.
The reasons are:
You still need to support the existing SW with (probably) the same resources you have.
You probably do not have the requirements for rewriting. Your old code has all the requirements embedded inside it. None of your engineers know all the SW domains and all the requirements.
Rewriting will take time. At the end of this time you will find that the existing SW has changed to support things that were required during this time.
your new SW actually split from the original and merge will be needed (which will also take time).
Is a total rewrite an option? In my experience rewriting from scratch can often be more efficient than trying to clean up the existing mess. You cold still keep parts of the existing code but in a new context. And the same goes for the gui and the database if you have one. Rewrite from scratch and take with you what you can use.
Starting with a clean new architecture and moving the old peices of code into this new architecture piece by piece and refactoring it to suit the new arch would be a good option. I think a bottom up approach when moving the functions would be good.
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I've inherited a project where the class diagrams closely resemble a spider web on a plate of spaghetti. I've written about 300 unit tests in the past two months to give myself a safety net covering the main executable.
I have my library of agile development books within reach at any given moment:
Working Effectively with Legacy Code
Refactoring
Code Complete
Agile Principles Patterns and Practices in C#
etc.
The problem is everything I touch seems to break something else.
The UI classes have business logic and database code mixed in. There are mutual dependencies between a number of classes. There's a couple of god classes that break every time I change any of the other classes. There's also a mutant singleton/utility class with about half instance methods and half static methods (though ironically the static methods rely on the instance and the instance methods don't).
My predecessors even thought it would be clever to use all the datasets backwards. Every database update is sent directly to the db server as parameters in a stored procedure, then the datasets are manually refreshed so the UI will display the most recent changes.
I'm sometimes tempted to think they used some form of weak obfuscation for either job security or as a last farewell before handing the code over.
Is there any good resources for detangling this mess? The books I have are helpful but only seem to cover half the scenarios I'm running into.
It sounds like you're tackling it in the right way.
Test
Refactor
Test again
Unfortunately, this can be a slow and tedious process. There's really no substitute for digging in and understanding what the code is trying to accomplish.
One book that I can recommend (if you don't already have it filed under "etc.") is Refactoring to Patterns. It's geared towards people who are in your exact situation.
I'm working in a similar situation.
If it is not a small utility but a big enterprise project then it is:
a) too late to fix it
b) beyond the capabilities of a single person to attempt a)
c) can only be fixed by a complete rewriting of the stuff which is out of the question
Refactoring can in many cases be only attempted in your private time at your personal risk. If you don't get an explicit mandate to do it as part of you daily job then you're likely not even get any credit for it. May even be criticized for "pointlessly wasting time on something that has perfectly worked for a long time already".
Just continue hacking it the way it has been hacked before, receive your paycheck and so on. When you get completely frustrated or the system reaches the point of being non-hackable any further, find another job.
EDIT: Whenever I attempt to address the question of the true architecture and doing the things the right way I usually get LOL in my face directly from responsible managers who are saying something like "I don't give a damn about good architecture" (attempted translation from German). I have personally brought one very bad component to the point of non-hackability while of course having given advanced warnings months in advance. They then had to cancel some promised features to customers because it was not doable any longer. Noone touches it anymore...
I've worked this job before. I spent just over two years on a legacy beast that is very similar. It took two of us over a year just to stabilize everything (it's still broke, but it's better).
First thing -- get exception logging into the app if it doesn't exist already. We used FogBugz, and it took us about a month to get reporting integrated into our app; it wasn't perfect right away, but it was reporting errors automatically. It's usually pretty safe to implement try-catch blocks in all your events, and that will cover most of your errors.
From there fix the bugs that come in first. Then fight the small battles, especially those based on the bugs. If you fix a bug that unexpectedly affects something else, refactor that block so that it is decoupled from the rest of the code.
It will take some extreme measures to rewrite a big, critical-to-company-success application no matter how bad it is. Even you get permission to do so, you'll be spending too much time supporting the legacy application to make any progress on the rewrite anyway. If you do many small refactorings, eventually either the big ones won't be that big or you'll have really good foundation classes for your rewrite.
One thing to take away from this is that it is a great experience. It will be frustrating, but you will learn a lot.
I have (once) come across code that was so insanely tangled that I couldn't fix it with a functional duplicate in a reasonable amount of time. That was sort of a special case though, as it was a parser and I had no idea how many clients might be "using" some of the bugs it had. Rendering hundreds of "working" source files erroneous was not a good option.
Most of the time it is imminently doable, just daunting. Read through that refactoring book.
I generally start fixing bad code by moving things around a bit (without actually changing implementation code more than required) so that modules and classes are at least somewhat coherent.
When that is done, you can take your more coherent class and rewrite its guts to perform the exact same way, but this time with sensible code. This is the tricky part with management, as they generally don't like to hear that you are going to take weeks to code and debug something that will behave exactly the same (if all goes well).
During this process I guarantee you will discover tons of bugs, and outright design stupidities. It's OK to fix trivial bugs while recoding, but otherwise leave such things for later.
Once this is done with a couple of classes, you will start to see where things can be modularized better, designed better, etc. Plus it will be easier to make such changes without impacting unrelated things because the code is now more modular, and you probably know it thoroughly.
Mostly, that sounds pretty bad. But I don't understand this part:
My predecessors even thought it would
be clever to use all the datasets
backwards. Every database update is
sent directly to the db server as
parameters in a stored procedure, then
the datasets are manually refreshed so
the UI will display the most recent
changes.
That sounds pretty close to a way I frequently write things. What's wrong with this? What's the correct way?
If your refactorings are breaking code, particularly code that seems to be unrelated, then you're trying to do too much at a time.
I recommend a first-pass refactoring where all you do is ExtractMethod: the goal is simply to name each step in the code, without any attempts at consolidation whatsoever.
After that, think about breaking dependencies, replacing singletons, consolidation.
If your refactorings are breaking things, then it means you don't have adequate unit test coverage - as the unit tests should have broken first. I recommend you get better unit test coverage second, after getting exception logging into place.
I then recommend you do small refactorings first - Extract Method to break large methods into understandable pieces; Introduce Variable to remove some duplication within a method; maybe Introduce Parameter if you find duplication between the variables used by your callers and the callee.
And run the unit test suite after each refactoring or set of refactorings. I'd say run them all until you gain confidence about which tests will need to be rerun every time.
No book will be able to cover all possible scenarios. It also depends on what you'll be expected to do with the project and whether there is any kind of external specification.
If you'll only have to do occasional small changes, just do those and don't bother starting to refactor.
If there is a specification (or you can get someone to write it), consider a complete rewrite if it can be justified by the foreseeable amount of changes to the project
If "the implementation is the specification" and there are a lot of changes planned, then you're pretty much hosed. Write LOTS of unit tests and start refactoring in small steps.
Actually, unit tests are going to be invaluable no matter what you do (if you can write them to an interface that's not going to change much with refactorings or a rewrite, that is).
See blog post Anatomy of an Anti-Corruption Layer, Part 1 and Anatomy of an Anti-Corruption Layer, Part 2.
It cites Eric Evans, Domain-Driven Design: Tackling Complexity in the Heart of Software:
Access the crap behind a facade
You could extract and then refactor some part of it, to break the dependencies and isolate layers into different modules, libraries, assemblies, directories. Then you re-inject the cleaned parts in to the application with a strangler application strategy. Lather, rinse, repeat.
Good luck, that is the tough part of being a developer.
I think your approach is good, but you need to focus on delivering business value (number of unit tests is not a measure of business value, but it may give you an indication if you are on or off track). It's important to have identified the behaviors that need to be changed, prioritize, and focus on the top ones.
The other piece of advise is to remain humble. Realize that if you wrote something so large under real deadlines and someone else saw your code, they would probably have problems understanding it as well. There is a skill in writing clean code, and there is a more important skill in dealing with other people's code.
The last piece of advise is to try to leverage the rest of your team. Past members may know information about the system you can learn. Also, they may be able to help test behaviors. I know the ideal is to have automated tests, but if someone can help by verifying things for you manually consider getting their help.
I particularly like the diagram in Code Complete, in which you start with just legacy code, a rectangle of fuzzy grey texture. Then when you replace some of it, you have fuzzy grey at the bottom, solid white at the top, and a jagged line representing the interface between the two.
That is, everything is either 'nasty old stuff' or 'nice new stuff'. One side of the line or the other.
The line is jagged, because you're migrating different parts of the system at different rates.
As you work, the jagged line gradually descends, until you have more white than grey, and eventually just grey.
Of course, that doesn't make the specifics any easier for you. But it does give you a model you can use to monitor your progress. At any one time you should have a clear understanding of where the line is: which bits are new, which are old, and how the two sides communicate.
You might find the following post useful:
http://refactoringin.net/?p=36
As it is said in the post, don't discard a complete overwrite that easily. Also, if at all possible, try to replace whole layers or tiers with third-party solution like for example ORM for persistence or with new code. But most important of all, try to understand the logic (problem domain) behind the code.
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I was asked to do a code review and report on the feasibility of adding a new feature to one of our new products, one that I haven't personally worked on until now. I know it's easy to nitpick someone else's code, but I'd say it's in bad shape (while trying to be as objective as possible). Some highlights from my code review:
Abuse of threads: QueueUserWorkItem and threads in general are used a lot, and Thread-pool delegates have uninformative names such as PoolStart and PoolStart2. There is also a lack of proper synchronization between threads, in particular accessing UI objects on threads other than the UI thread.
Magic numbers and magic strings: Some Const's and Enum's are defined in the code, but much of the code relies on literal values.
Global variables: Many variables are declared global and may or may not be initialized depending on what code paths get followed and what order things occur in. This gets very confusing when the code is also jumping around between threads.
Compiler warnings: The main solution file contains 500+ warnings, and the total number is unknown to me. I got a warning from Visual Studio that it couldn't display any more warnings.
Half-finished classes: The code was worked on and added to here and there, and I think this led to people forgetting what they had done before, so there are a few seemingly half-finished classes and empty stubs.
Not Invented Here: The product duplicates functionality that already exists in common libraries used by other products, such as data access helpers, error logging helpers, and user interface helpers.
Separation of concerns: I think someone was holding the book upside down when they read about the typical "UI -> business layer -> data access layer" 3-tier architecture. In this codebase, the UI layer directly accesses the database, because the business layer is partially implemented but mostly ignored due to not being fleshed out fully enough, and the data access layer controls the UI layer. Most of the low-level database and network methods operate on a global reference to the main form, and directly show, hide, and modify the form. Where the rather thin business layer is actually used, it also tends to control the UI directly. Most of this lower-level code also uses MessageBox.Show to display error messages when an exception occurs, and most swallow the original exception. This of course makes it a bit more complicated to start writing units tests to verify the functionality of the program before attempting to refactor it.
I'm just scratching the surface here, but my question is simple enough: Would it make more sense to take the time to refactor the existing codebase, focusing on one issue at a time, or would you consider rewriting the entire thing from scratch?
EDIT: To clarify a bit, we do have the original requirements for the project, which is why starting over could be an option. Another way to phrase my question is: Can code ever reach a point where the cost of maintaining it would become greater than the cost of dumping it and starting over?
Without any offense intended, the decision to rewrite a codebase from scratch is a common, and serious management mistake newbie software developers make.
There are many disadvantages to be wary of.
Rewrites stop new features from being developed cold for months/years. Few, if any companies can afford to stand-still for this long.
Most development schedules are difficult to nail. This rewrite will be no exception. Amplify the previous point by, now, a delay in development.
Bugs that were fixed in the existing codebase through painful experience will be re-introduced. Joel Spolsky has more examples in this article.
Danger of falling victim to the Second-system effect -- in summary, ``People who have designed something only once before try to do all the things they "didn't get to do last time", loading the project up with all the things they put off while making version one, even if most of them should be put off in version two as well.''
Once this expensive, burdensome rewrite is completed, the very next team to inherit the new codebase is likely to use the same excuses for doing another rewrite. Programmers hate learning someone else's code. No one writes perfect code because perfection is so subjective. Find me any real-world application and I can give you a damning indictment and rationale for doing a from-scratch rewrite.
Whether you ultimately rewrite from scratch or not, beginning a refactoring phase now is a good way to both really sit down and understand the problem so that the rewrite will go more smoothly if truly called for, as well as giving the existing codebase an honest look to really see if a rewrite's needed.
To actually scrap and start over?
When the current code doesn't do what you would like it to do, and would be cost prohibitive to change.
I'm sure someone will now link Joel's article about Netscape throwing their code away and how it's oh-so-terrible and a huge mistake. I don't want to talk about it in detail, but if you do link that article, before you do so, consider this: the IE engine, the engine that allowed MS to release IE 4, 5, 5.5, and 6 in quick succession, the IE engine that totally destroyed Netscape... it was new. Trident was a new engine after they threw away the IE 3 engine because it didn't provide a suitable basis for their future development work. MS did that which Joel says you must never do, and it is because MS did so that they had a browser that allowed them to completely eclipse Netscape. So please... just meditate on that thought for a moment before you link Joel and say "oh you should never do it, it's a terrible idea".
A rule of thumb I've found useful is that if given a code base, if I have to re-write more than 25% of the code to make it work or modify it based upon new requirements, you may as well re-write it from scratch.
The reasoning is that you can only patch a body of code so far; beyond a certain point, it's quicker to do over.
There's an underlying assumption that you have a mechanism (such as thorough unit and/or system tests) that will tell you whether your re-written version is functionally equivalent (where it needs to be) as the original.
If it requires more time to read and understand the code (if that is even possible)
than it would to rewrite the entire application, I say scrap it and start over.
Be very carefull with this:
Are you sure you aren't just being lazy and not bothering to read the code
Are you being arrogant about the great code you will write compared to the rubbish anyone else produced.
Remember tested-working code is worth a lot more than imaginary yet-to-be-written code
In the words of our estemed host and overlord, Joel - things you should never do,
it's not always wrong to abandon working code - but you have to be sure about the reason.
I saw an application re-architected within 2 years of its introduction into production, and others rewritten in different technologies (one was C++ - now Java). Both efforts were were not, to my mind, successful.
I prefer a more evolutionary approach to bad software. If you can "componentize" your old app such that you can introduce your new requirements and interface with the old code, you can ease yourself into the new environment without having to "sell" the zero-value (from a biz perspective) investment in rewriting.
Suggested approach - write unit tests for the functionality with which you wish to interface to 1) ensure the code behaves as you expect and 2) provide a safety net for any refactoring that you may wish to do on the old base.
Bad code is the norm. I think IT gets a bad rap from business for favoring rewrites/rearchitecting/etc. They pay the money and "trust" us (as an industry) to deliver solid, extensible code. Sadly, business pressures frequently result in shortcuts that make the code unmaintainable. Sometimes it's bad programmers... sometimes bad situations.
To answer your rephrased question... can code maintenance costs ever exceed rewriting costs... the answer is clearly yes. I don't see anything in your examples, however, that lead me to believe this is your case. I think those issues can be addressed with tests and refactoring.
In terms of business value, I would think it's extremely rare that a real case can be made for a rewrite due solely to the internal state of the code. If the product's customer-facing and is currently live and bringing in money (i.e. is not a mothballed or unreleased product), then consider that:
You already have customers using it. They're familiar with it, and might have built some of their own assets around it. (Other systems that interface to it; products based on it; processes they'd have to change; staff they'd maybe have to retrain). All of this costs the customer money.
Re-writing it might cost less in the long term than making difficult changes and fixes. But you can't quantify that yet, unless your app is no more complex than Hello World. And a re-write means a re-test and a redeploy, and probably an upgrade path for your customers.
Who says the re-write will be any better? Can you honestly say your firm is writing sparkly code now? Have the practices that turned the original code to spaghetti been corrected? (Even if the main culprit was a single developer, where were his peers and management, ensuring quality through reviews, testing, etc.?)
In terms of technical reasons, I'd suggest it could be time for a major rewrite if the original has some technical dependencies that have become problematic. e.g. a third party dependency that's now out of support, etc.
In general though, I think the most sensible move is to refactor piece by piece (very small pieces if it's really that bad), and improve the internal architecture incrementally rather than in one big drop.
Two threads of thought on this one: Do you have the original requirements? Do you have confidence that the original requirements are accurate? What about test plans or unit tests? If you have those things in place it might be easier.
Putting on my customer hat, does the system work or is it unstable? If you've got something that's unstable you've got an argument to change; otherwise you're best of refactoring it bit by bit.
I think the line in the sand is when basic maintenance is taking 25% - 50% longer than it should. There comes a time when maintaining legacy code becomes too costly. A number of factors contribute to the final decision. Time and cost being the most important factors I think.
If there are clean interfaces and you can cleanly delineate module boundaries, then it might be worth refactoring it module by module or layer by layer in order to allow you to migrate existing customers forward into cleaner more stable codebases, and over time, after you've refactored every module, you will have rewritten everything.
But, based on the codereview, doesn't sound like there would be any clean boundaries.
I wonder if the people who vote for scrapping and starting over have ever successfully refactored a large project, or at least seen a large project in poor condition that they think could use a refactoring?
If anything, I err on the opposite side: I've seen 4 large projects that were a mess, that I advocated refactoring as opposed to rewriting. On a couple, there was barely a single line of original code that remained, and major interfaces changed in significant ways, but the process never involved the entire project failing to function as well as it originally did, for any more than a week. (And top-of-trunk was never broken).
Perhaps a project exists that is so severely broken that to attempt to refactor it would be doomed to failure, or perhaps one of the previous projects I refactored would have been better served by a "clean re-write", but I'm not sure I'd know how to recognize it.
I agree with Martin. You really need to weigh the effort that will be involved in writing the app from scratch against the current state of the app and how many people use it, do they like it, etc. Often we may want to completely start from scratch, but the cost far outweighs the benefit. I come across bits of ugly looking code all the time, but I soon realize that some of these 'ugly' areas are really bug fixes and make the program work correctly.
I would try to consider the architecture of the system and see whether it is possible to scrap and rewrite specific well defined components without starting everything from scratch.
What would usually happen is that you can either do that (and then sell that to the customer/management), or that you find out that the code is such a horrible and tangled mess that you become even more convinced that you need a rewrite and have more convincing arguments for it (including: "if we engineer it right, we would never need to scrap the whole thing and do a third rewrite).
Slow maintenance would eventually cause that architectural drift that would make a rewrite more expensive later.
Scrap old code early and often. When in doubt, throw it out. The hard part is convincing non-technical folks of the cost-to-maintain.
So long as the value derived appears to be greater than the cost to operate and maintain, there's still positive value flowing from the software. The question surrounding a rewrite this: "will we get even more value from a rewrite?" Or alternatively "How much more value will we get from a rewrite?" How many person-hours of maintenance will you save?
Remember, the rewrite investment is once only. The return on the rewrite investment lasts forever. Forever.
Focus the value question down to specific issues. You listed a bunch of them above. Stick with that.
"Will we get more value by reducing cost through
dropping the junk that we don't use
but still have to wade through?"
"Will we get more value from dropping the junk that's unreliable and breaks?"
"Will we get more value if we understand it -- not by documenting, but by replacing with something we built as a team?"
Do you homework. You'll have to confront the following show-stoppers.
These will originate somewhere in your executive foodchain from someone who'll respond as follows:
"Is it broken?" And when you say "It's not crashed as such," They'll say "It's not broke - don't fix it."
"You've done the code analysis, you understand it, you no longer need to fix it."
What's your answer to them?
That's only the first hurdle. Here's the worst possible situation. This doesn't always happen, but it does happen with alarming frequency.
Someone in your executive foodchain will have this thought:
"A rewrite doesn't create enough value. Rather than simply rewrite, let's expand it." The justification is that by creating enough value, users are more likely to buy in to the rewrite.
A project where scope is expanded -- artificially -- to add value is usually doomed.
Instead, do the smallest rewrite you can to replace the darn thing. Then expand to fit real needs and add value.
You can only give a definite yes to rewriting in case if you know completely how your application works (and by completely I mean it, not just having a general idea of how it should work) and you know more or less exactly how to make it better. Any other cases and it's a shot in the dark, it depends on too much things. Perhaps gradual refactoring would be safer if it is possible.
If possible, I typically would prefer to rewrite smaller portions of the code over time when I need to refactor a baseline. There are typically many smaller issues such as magic number, poor commenting, etc. that tend to make the code look worse than it actually is. So, unless the baseline is just awful, keep the code and just make improvements at the same time you are maintaining the code.
If refactoring requires a lot of work, I recommend laying out a small re-design plan/todo list that gives you a list of things to work on in order so that you can bring the baseline to a better state. Starting from scratch is always a risky move and you are not guaranteed that the code will be better when you are finished. Using this technique, you will always have a working system that improves over time.
Code with excessively high cyclomatic complexity (like over 100 in a large number of modules) is a good clue. Also, how many bugs does it have / KLOC? How critical are the bugs? How often are bugs introduced when bug fixes are made. If your answer is a lot (I cant remember norms right now), then a rewrite is warranted.
As early as possible. Whenever you get a premonition that your code is slowly turning into an ugly beast that is very likely to consume your soul and give you headaches, and you know the problem is in the underlying structure of the code (so any fix would be a hack, e.g. introduce a global variable), then it's time to start over.
For some reasons people don't like throwing away precious code, but if you feel your better off starting over, you are probably right. Trust your instinct and remember that it wasn't a waste of time, it taught you one more way of NOT approaching the problem. You could (should) always use a version control system so your baby is never really lost.
I do not have any experience with using metrics for this myself, but the
article
"Software Maintainability Metrics Models in Practice" discusses
more or less the same question asked here for two case studies they did.
It starts with the following editor's note:
In the past, when a maintainer
received new code to maintain, the
rule-of-thumb was "If you have to
change more than 40 percent of someone
else's code, you throw it out and
start over." The Maintainability Index
[MI] addressed here gives a much more
quantifiable method to determine when
to "throw it out and start over." This
work was sponsored by the U.S. Air
Force Information Warfare Center and
the U.S. Department of Energy [DOE],
Idaho Field Office, DOE Contract No.
DE-AC07-94ID13223.)
I think the rule was...
The first version is always a throw away
So, if you learned your lesson(s), or his/her lessons, then you can go ahead and write it fresh now that you understand your problem domain better.
Not that there aren't parts that can/should be kept. Tested code is the most valuable code, so if it isn't deficient in any real way other than style, no reason to toss it all out.
When is it good (if ever) to scrap production code and start over?
Never had to do this, but logic would dictate (to me, anyway) that once you pass the inflection point where you're spending more time reworking and fixing bugs in the existing code base than you are adding new functionality, it's time to trash the old stuff and get a fresh start.
If it requires more time to read and understand the code (if that is even possible) than it would to rewrite the entire application, I say scrap it and start over.
I have never completely thrown out code. Even when going from a foxpro system to a c# system.
If the old system worked then why just throw it out?
I have come across a few really bad system. Threads being used where not needed. Horrible inheritance and abuse of interfaces.
It is best to understand what the old code is doing and why it is doing it. Then change it so that it is not confusing.
Of course if the old code doesn't work. I mean can't even compile. Then you might be justified in just starting over. But how often does that actually happen?
Yes, it totally can happen. I've seen money be saved by doing it.
This is not a tech decision, it's a business decision. Code rewrites are long term gains, while "if it ain't totally broke..." is a short term gain. If you are in a first year startup that is focused on getting a product out the door, the answer is usually to just live with it. If you're in an established company, or the errors with the current systems are causing more workload, therefor more company money.. then they might go for it.
Present the problem as best as you can to your GM, use dollar values where you can. "I don't like dealing with it" means nothing. "It'll take twice the time to do everything until this is fixed" means a lot.
I think there are a number of issues here that depend largely on where you are at.
Is the software working well from a customer perspective? (If yes be very careful about changes). I would think there would be little point re-witting unless you were expanding the feature set if the system was working. And are you planning to expand the features and customer base of the software? If so then you have much more reason to change.
As much as anything just trying to understand some else's code even if well written can be difficult, when badly written I would imagine almost impossible. What you describe sounds like something that would be very difficult to expand.
I would take into consideration if the application does what it is intended to do, is required for you to ever make modifications, and are you confident that the app has been thoroughly tested in all scenarios that it will be used in.
Do not invest the time if the app does not need alterations. However, if it doesn't function as you need and you need to control the hours and time invested to make corrections, scrap it and re-write to the standards that your team can support. There's nothing worse than terrible code that you have to support / decipher but still have to live with. Remember, Murphy's Law says it will 10 at night when you'll have to make things work, and that is never productive.
Production code always has some value. The only case where I would truly throw it all out and start again is if we determine the intellectual property is irrevocably contaminated. For example if someone brought large amounts of code from a previous employer, or a large percentage of the code was ripped from a GPLd codebase.
I'm going to post this book every time I see a discussion on Refactoring. Everyone should read "Working Effectively with Legacy Code" by Michael Feathers. I found it to be an excellent book - if nothing else, it's a fun read, and motivational.
When the code has reached a point that is not maintainable or extensible anymore. Is full of short-term hacky fixes. It has lots of coupling. It has long (100+lines) methods. It has database access in the UI. It generates a lot of random, impossible to debug errors.
Bottom line: When maintaining it is more expensive (i.e. takes longer) than rewriting it.
I used to believe in just re-write from scratch, but it is wrong.
http://www.joelonsoftware.com/articles/fog0000000069.html
Changed my mind.
What I would suggested is figuring out a way to properly refactor the code. Keep all existing functionality and test as you go. We have all seen horrible code bases, but it is important to keep the knowledge over time you application has.
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Many times we find ourselves working on a problem, only to figure out the solution being created is far more complex than the problem requires. Are there controls, best practices, techniques, etc that help you control over complication in your workplace?
Getting someone new to look at it.
In my experience, designing for an overly general case tends to breed too much complexity.
Engineering culture encourages designs that make fewer assumptions about the environment; this is usually a good thing, but some people take it too far. For example, it might be nice if your car design doesn't assume a specific gravitational pull, nobody is actually going to drive your car on the moon, and if they did, it wouldn't work, because there is no oxygen to make the fuel burn.
The difficult part is that the guy who is developed the "works-on-any-planet" design is often regarded as clever, so you may have to work harder to argue that his design is too clever.
Understanding trade-offs, so you can make the decision between good assumptions and bad assumptions, will go a long way into avoiding a needlessly complicated design.
If its too hard to test, your design is too complicated. That's the first metric I use.
Here are some ideas to get design more simpler:
read some programming books and articles, and then apply them in your work and write code
read lots of code (good and bad) written by other people (like Open Source projects) and learn to see what works and what does not
build safety nets (unit tests) to enable experimentations with your code
use version control to enable rollback, if those experimentations take wrong turn
TDD (test driven development) and BDD (behaviour driven development)
change your attitude, ask how you can make it so, that "it simply works" (convention over configuration could help there; or ask how Apple would do it)
practice (like jazz players -- jam with code, try Code Kata)
write same code multiple times, with different languages and after some time has passed
learn new languages with new concepts (if you use static language, learn dynamic one; if you use procedural language, learn functional one; ...) [one language per year is about right]
ask someone to review you code and actively ask how you can make your code simpler and more elegant (and then make it)
get years under your belt by doing above things (time helps active mind)
I create a design etc., and then I look at it and try and remove (agressively) everything that doesn't seem to be needed. If it turns out I need it later when I am polishing the design I add it back in. I do this over several iterations, refining as I go along.
Read "Working Effectively With Legacy Code" by Michael C. Feathers.
The point is, if you have code that works, and you need to change the design, nothing works better than making your code unit testable, and breaking your code into smaller pieces.
Using Test Driven Development and following Robert C. Martin's Three Rules of TDD:
You are not allowed to write any production code unless it is to make a failing unit test pass.
You are not allowed to write any more of a unit test than is sufficient to fail; and compilation failures are failures.
You are not allowed to write any more production code than is sufficient to pass the one failing unit test.
In this way you are not likely to get much code that you don't need. You will always be focused on making one important thing work and won't ever get too far ahead of yourself in terms of complexity.
Test first may help here, but it is not suitable for all situation. And it's not a panacea anyway.
Start small is another great idea. Do you really need to stuff all 10 design patterns into this thing? Try first to do it "stupid way". Doesn't quite cut it? Okay, do it "slightly less stupid way". Etc.
Get it reviewed. As someone else wrote, two pairs of eyes are better. Even better are two brains. Your mate may just see a room for simplification, or a problematic area you thought was fine just because you spend many hours hacking it.
Use lean language. Languages such as Java, or sometimes C++ sometimes seem to encourage nasty, convoluted solutions. Simple things tend to span over multiple lines of code, and you just need to use 3 external libraries and a big framework to manage it all. Consider using Python, Ruby, etc. - if not for your project, then for some private use. It can change your mindset to favor simplicity, and to be assured that simplicity is possible.
Reduce the amount of data you're working with by serialising the task into a series of smaller tasks. Most people can only hold half a dozen (plus or minus) conditions in their head while coding, so make that the unit of implementation. Design for all the tasks you need to accomplish, but then ruthlessly hack the design so that you never have to play with more than half a dozen paths though the module.
This follows from Bendazo's post - simplify until it becomes easy.
It is inevitable once you have been a programmer that this will happen. If you seriously have unestimated the effort or hit a problem where your solution just doesn't work then stop coding and get talking to your project manager. I always like to take the solutions with me to the meeting, problem is A, you can do x which will take 3 days or we can try y which will take 6 days. Don't make the choice yourself.
Talk to other programmers every step of the way. The more eyes there are on the design, the more likely an overcomplicated aspect is revealed early, before it becomes too ossified in the codebase.
Constantly ask yourself how you will use whatever you are currently working on. If the answer is that you're not sure, stop to rethink what you're doing.
I've found it useful to jot down thoughts about how to potentially simplify something I'm currently working on. That way, once I actually have it working, it's easier to go back and refactor or redo as necessary instead of messing with something that's not even functional yet.
This is a delicate balancing act: on the one hand you don't want something that takes too long to design and implement, on the other hand you don't want a hack that isn't complicated enough to deal with next week's problem, or even worse requires rewriting to adapt.
A couple of techniques I find helpful:
If something seems more complex than you would like then never sit down to implement it as soon as you have finished thinking about it. Find something else to do for the rest of the day. Numerous times I end up thinking of a different solution to an early part of the problem that removes a lot of the complexity later on.
In a similar vein have someone else you can bounce ideas off. Make sure you can explain to them why the complexity is justified!
If you are adding complexity because you think it will be justified in the future then try to establish when in the future you will use it. If you can't (realistically) imagine needing the complexity for a year or three then it probably isn't justifiable to pay for it now.
I ask my customers why they need some feature. I try and get to the bottom of their request and identify the problem they are experiencing. This often lends itself to a simpler solution than I (or they) would think of.
Of course, if you know your clients' work habits and what problems they have to tackle, you can understand their problems much better from the get-go. And if you "know them" know them, then you understand their speech better. So, develop a close working relationship with your users. It's step zero of engineering.
Take time to name the concepts of the system well, and find names that are related, this makes the system more familiar. Don't be hesitant to rename concepts, the better the connection to the world you know, the better your brain can work with it.
Ask for opinions from people who get their kicks from clean, simple solutions.
Only implement concepts needed by the current project (a desire for future proofing or generic systems make your design bloated).