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In my copious free time, I collaborate with a number of scientists (mostly biologists) who develop software, databases, and other tools related to the work they do.
Generally these projects are built on a one-off basis, used in-house, and eventually someone decides "oh, this could be useful to other people," so they release a binary or slap a PHP interface onto it and shove it onto the web. However, they typically can't be bothered to make their source code or dumps of their databases available for other developers, so in practice, these projects usually die when the project for which the code was written comes to an end or loses funding. A few months (or years) later, some other lab has a need for the same kind of tool, they have to repeat the work that the first lab did, that project eventually dies, lather, rinse, repeat.
Does anyone have any suggestions for how to persuade people whose primary job isn't programming that it's of benefit to their community for them to be more open with the tools they've built?
Similarly, any advice on how to communicate the idea that version control, bug tracking, refactoring, automated tests, continuous integration and other common practices we professional developers take for granted are good ideas worth spending time on?
Unfortunately, a lot of scientists seem to hold the opinion that programming is a dull, make-work necessary evil and that their research is much more important, not realising that these days, software development is part of scientific research, and if the community as a whole were to raise the bar for development standards, everyone would benefit.
Have you ever been in a situation like this? What worked for you?
Software Carpentry sounds like a match for your request:
Overview
Many scientists and engineers spend
much of their lives programming, but
only a handful have ever been taught
how to do this well. As a result, they
spend their time wrestling with
software, instead of doing research,
but have no idea how reliable or
efficient their programs are.
This course is an intensive
introduction to basic software
development practices for scientists
and engineers that can reduce the time
they spend programming by 20-25%. All
of the material is open source: it may
be used freely by anyone for
educational or commercial purposes,
and research groups in academia and
industry are actively encouraged to
adapt it to their needs.
Let me preface this by saying that I'm a bioinformatician, so I see the things you're talking about all the time. There's some truth to the fact that many of these people are biologists-turned-coders who just don't have the exposure to best practices.
That said, the core problem isn't that these people don't know about good practices, or don't care. The problem is that there is no incentive for them to spend more time learning software engineering, or to clean up their code and release it.
In an academic research setting, your reputation (and thus your future job prospects) depends almost entirely on the number and quality of publications that you've contributed to. Publications on methods or new algorithms are not given as much respect as those that report new biological findings. So after I do a quick analysis of a dataset, there's very little incentive for me to spend lots of time cleaning up my code and releasing it, when I could be moving on to the next dataset and making more biological discoveries.
I'll also note that the availability of funding for computational development is orders of magnitude less than that available for doing the biology. In a climate where only 10% of submitted grants are getting funded, scientists don't have the luxury of taking time to clean and release their code, when doing so doesn't help them keep their lab funded.
So, there's the problem in a nutshell. As a bioinformatician, I think it's perverse and often frustrating.
That said, there is hope for the future. With second-and-third generation sequencing, in particular, biology is moving into the realm of high-throughput discovery, where data mining and solid computational pipelines become integral to the success of the science. As that happens, you'll see more and more funding for computational projects, and more and more real software engineering happening.
It's not exactly simple, but demonstration by example would probably drive the point home most effectively - find a task the researcher needs done, find someone who did take the time to make a tool w/source available, and point out how much time the researcher could save as a result due to having that tool available - then point out that they could give back to the community in the same fashion.
In effect, what you are asking them to do is become professional developers (with their copious free time), in addition to their chosen profession. Their reluctance is understandable.
Does anyone have any suggestions for how to persuade people whose primary job isn't programming that it's of benefit to their community for them to be more open with the tools they've built?
Give up. Seriously, this is like teaching a pig to sing. (I can say this because I used to be a physicist so I know what they're like.)
The real issue is that your colleagues are rewarded for scientific output measured in publications, not software. It's hard enough in computer science to get recognized for building software; in the other sciences, it's nearly impossible.
You can't sell good development practice to your biology friends on the grounds that "it's good for you." They're going to ask "should I invest effort in learning about good software practice, or should I invest the same effort to publish another biology paper?" No contest.
Maybe framing it in terms of academic/intellectual responsibility would help, to a degree - sharing your source is, in many ways, like properly citing your sources or detailing your research methodology. There are similar arguments to be made for some of the "professional software developer" behaviors you'd like to encourage, though I think releasing the code is probably an easier sell on these grounds than other things which could require significantly more work.
Actually, asking any busy project team to include in their schedule time for making their software suitable for adoption by another team is extremely hard in my experience.
Doing extra work for the public good is a big ask.
I've seen a common pattern of "harvesting" after the project is complete, reflecting that immediate coding for reuse tends to get lost in the urgency of the day.
The only avenue I can think of is if the reuse is within an organisation with a budget for a "hunter gatherer", someone whose reason for being there is IT.
You may be on more of a win for things such as unit tests because they have immediate payback for the development.
For one thing, could we please stop teaching biologists Perl? Teaching non-professional programmers a write-only language is practically guaranteed to lead to unmaintainable, throw-away code. Python fills the same niche, is just as easy to learn (it's even used to teach kids programming!), and is much more readable.
Draw parallels with statistics. Stats is a crucial part of scientific research, and one where the only sensible advice is: either learn to do it properly, or get an expert to do it for you. Incorrectly-done stats can completely undermine a paper, just as badly-written code can completely undermine a public database or web resource.
PS: This blog is very good, but getting them to read it will be an uphill struggle: Programming for Scientists
Chris,
I agree with you to a degree, but in my experience what ends up happening is that in their eagerness to publish you end up with too many "me too" codes and methods, which don't really add to the quality of science. If there was a little more thought about open sourcing code and encouraging others to contribute (without necessarily getting publications out of it) then everyone would benefit.
Definitely agree that a separation between the scientific programmers and the software engineers is a good thing, especially for production applications. But even for scientific programming, the quality of my code would have been so much better if I had followed good practices at the time.
In my experience the best way of getting people to program cleanly is to show a good example when you're working with them.
eg: "I never spend hopeless days debugging my code because the first things I code are automated unit tests that will pinpoint problems when they are small and easily detectable"
or: "I'm very bad at keeping track of versions of things, but sometimes my new code does break what did work before. So I use svn/git/dropbox to keep track of things for me"
In my experience that kind of statement can raise the interest of "biologists that learned how to script".
And if you need to collaborate on a bigger project, make it clear that you have more experience and that everything will go more smoothly if things are done your way.
Regarding publication of code, current practice is indeed frustrating. I would like to see a new journal like Source Code for Biology and Medecine, where code is peer-reviewed and can be published, but that has no (or very low) publication costs. Putting code on sourceforge or others is indeed not "scientifically worth it" because it doesn't make a line on your publication list, and most code is not revolutionary enough to warrant paying $1,000 for publication in Source Code for Biology and Medecine or PLoS One...
You could have them use a content management system, like Joomla. That way they only push content and not code.
I wouldn't so much persuade as I would streamline the process. Document it clearly, make video tutorials and bundle some kind of tool chain that makes it ridiculously easy to get source repositories set up without requiring them to become experts in something that isn't their main field.
Take a really good programmer who already knows best practices, ask your scientists to teach him what they need and what they do, eventually the programmer will have minimum domain knowledge (I suspect it takes between 1 and 3 years depending on the domain) to do what scientists asks for.
Developers always learn another domain of competency, because most of their programs are not for developers, so they need to know what the "client" do.
To be devil's advocate, is teaching scientists to be good software engineers the right thing to do? Software in research is usually very purpose specific - sometimes to the point where a piece of code needs to run successfully only once on a single data set. The results then feed into a publication and the goal is met. And there's a high risk that your technique or algorithm will be superseded by a better one in short order. So, there's a real risk that effort spent producing sparkling code will be wasted.
When you're frustrated by wading through a swamp of ill-formed perl code, just think that the code you're looking at is one of the rare survivors. Mountains of such code has been written, used a few times, then discarded never to see the light of day again.
I guess I'm just saying there's a big place in research for smelly heinous one-off prototype code. There are good reasons why such code exists. It may not be pretty, but if it gets the job done, who cares? We can always hire a software engineer to write the production-ready version later, IF it turns out to be justified, and let our scientists move on.
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The organization that I currently work for seems to be heading in the direction of dictating to software developers which tools, languages, frameworks, etc. must be used. However, nobody has convinced me that this is a good thing. The main argument I have heard is that it will make training easier. But, after developing software for over 10 years, I've never relied on training to learn how to use an IDE, programming language, or anything else; so I just can't relate.
With the rapid speed at which technology evolves, and the s-l-o-w-n-e-s-s at which I know the standards will adapt, I am concerned that my customers will have requirements that I won't be able to easily implement or won't be able to implement as efficiently as I should. For example, if there is a UI requirement for an auto-complete feature in a web app, and no API has been approved for this yet, I would need to implement auto-complete myself as opposed to using one of the many APIs that provide it out of the box.
A more radical example is if my customers wanted to have Google Wave features. In that case I would want the flexibility of configuring my development environment (including the IDE) and selecting appropriate frameworks (ex: GWT) to use.
Please provide feedback on whether or not you think that software developer tools, languages, etc should be standardized and a few points to support your argument.
There is a lot of benefit for standardization. My organization has fairly set standards on what technology we will use. We realize strong benefits in the following areas ...
Hiring. It is easy to describe what technologies we are looking for and make sure our recruiters are looking for the right people.
License/Software costs. I can buy enterprise licenses easily. It gives me the opportunity to keep costs down by letting me spend more with a smaller number of vendors and thus get more leverage.
Consistency of delivery. Our teams have a very good idea of what projects will take to build, rollout and maintain because they have done it with success before (and they know the pitfalls too).
Agility. I can have one team take over for another or one individual take over for another more easily because of standardization.
Quality. We have peer reviews across teams as well as QA across teams.
Without a consistent use of a technology stack, tools, languages and frameworks, these types of benefits would be more difficult to realize. I am not closed off to new technologies, but there has to be a concrete reason beyond "what if I want to ..."
A major issue with standardization is that once standards are out there, they get stamped in concrete and are difficult to change. This is why our corporate IT environment is stuck on IE 6, and the best change control system we have access to is CVS. Given this situation, some developers break the rules, and some find jobs at more innovative companies.
You have a mixed bag here.
I wouldn't standardize on IDEs, because every developer works differently. Those who are insanely proficient in emacs may see their performance suffer if forced to use Visual Studio. I optimize my Visual Studio experience with a 30" monitor and find it incredibly productive.
However, standardizing on some tools, such as SCons or make or something to build products is perfectly reasonable.
Banning some libraries and having a process where new libraries are either approved or not is also very reasonable. I know lots of companies that ban boost, or JQuery, or ban open source libraries in general, etc. And they had good reasons for doing it. I know I got fairly upset when an intern incorporated some random "security" library he found on the internet without running it by anyone.
In the end every company is different. You have to be standardized enough to avoid serious complications and issues as people come and go, or as new products are formed and organizational structures change. But you have to be flexible enough to avoid re-inventing every wheel you need.
The important thing is to have clear reasons for adopting a certain tool or banning some other tool or library. You can't just have management dictate that thou shalt use this and not that without consulting the engineering team and making the decision for good reasons. And once decisions are made those reasons should be written down and clearly communicated.
And also, if, in the end, your favorite tool or library isn't adopted, please don't whine about it. Be adaptable and do your job, or find a new one that makes you happier.
I once worked for a manager who felt the need to innovate at every level of his software development operation. Every development tool had to be cutting edge (preferably in beta). Many of the tools he asked us to use didn't have good documentation, and training was not available. Ultimately, most of the technology we tried simply didn't work. We wasted a lot of time churning through new technologies, only to dump them when it became clear we couldn't make progress.
I tried to make the case that innovation is perfect in the area where your value proposition lies. Innovation can also be used judiciously where standard techniques fail. But for most mundane tasks, using tried-and-true tools and methods should be the default. Less risk, less cost, less management attention needed. So you can focus time and energy on the areas where innovation has the most benefit.
So I think standardization has an important role. But blindly saying everything must be standard is just as sure to fail as my manager who thought everything must be innovative.
The number one argument in favor of standardization is that it maximizes the ability of the organization as a whole to use a common body of knowledge. Don't know how custom web controls are built in ASP.NET/C#? Ask Bill down the hall who has the knowledge. If you use different tools, such organizational wisdom is cut off at the knees. While it is not good to be restricted to a least common denominator (and hopefully your management will realize this) you should not overlook the benefits of shared experience!
UPDATE: I do not agree that innovation and standardization are polar opposites. Indeed, would we have nearly the level of web innovation if we still had the mishmash of networking standards characteristic of the 1980s? No we would not. Of course, we might have more innovation on new low-level networking protocols but is that really worth it? In its place, we've had an explosion of creativity within the bounds of TCP/IP and the Web standards (http, html, etc.)
The trick is knowing how to standardize without using it as an argument for closing down all new exploration. For example, we use only ASP.NET/C#/SQL Server in my company but I'm perfectly open to the use of new tools within this framework (we recently adopted the DevExpress reporting package, for example, supplanting the earlier standard).
Standardization is a must for a productive development team. However that doesn't mean that you can't revist the standards from time to time to adjust them to new technologies and trends.
Whether you develop operations software for internal clients, or products for external clients, there is no compelling reason not to standardize. You certainly did not give one.
Had you seen how companies are struggling with holding heterogenous products together that have been maintained for 10 years or more, and are now a conglomerate of various technologies that developers at some point thought made sense, you would not have asked this question.
From the top of my head, I could name at least 2 well-known software companies that will be driven out of business because their cost of maintenance has become so high that they can no longer compete (but I won't).
I think the misconception here is that suppressing individualism would supress innovation. That is simply not true. It is poor technical leadership that suppresses innovation.
One unpleasant consequence of standardization is that it tends to stifle innovation.
Innovation is scary. It involves cost and risk.
Standardization is not scary. It reduces cost and risk in the short term. Until your competitors have created a game-changing innovation. Then standardization is very costly.
It depends on the organization I think. One like Microsoft, yes, there should be a bit of a standard. A small business with one IT department, no. A larger business with several offices around the world ... maybe.
it all depends :-P
Assuming the organization has a broad suite of enterprise applications to manage, I'd say no for the following reasons, though I may be taking the message of everything being the same a bit too literally:
Compromise on using best-of-breed for systems, e.g. if all the databases are to be MS-SQL then any Oracle DB solution is thrown out. This would also apply to the fact that everyone using an IDE has to use the same one whether they be doing Data Warehouse report development, web applications, console applications or winForms. I'm thinking of systems like ERP, CRM, SCM, CMS, SSO and various other TLAs, FLAs, and SLAs. (LA = Letter acronyms for a decoding hint if you need it)
Upgrading by committee is another interesting issue. Where if each team can choose their tools and have one person that decides it is to upgrade things, e.g. start using Visual Studio 2008 instead of Visual Studio 2005, now have to determine at what threshold is it worth it to upgrade everyone simultaneously which may be a big headache if there are more than a few developers. For example, over the past 10 years when would there be IDE changes, framework changes, etc.?
Exceptions to the standards. Could a contractor bring in something not used in the organization if they believe it helps them build better software, e.g. Resharper or other add-ons that some contractors believe are very worthwhile that the organization doesn't want to spend the money to get? What about legacy systems that may make the standard become a bit unwieldy, e.g. this was built in ASP.Net 1.1 and so everyone has to have VS 2003 installed even if most will never use it?
Just my thoughts on this.
There are several good reasons to standardize.
First, it allows the enterprise better organizational flexibility, if everybody is more or less familiar with the same things. It also allows people to help each other better. I can't help with problems in the ASP.NET stuff, and there's not all that many people who can help me on the C++ side.
Second, it reduces support problems and expenses. Oracle and SQL Server are both decent products, but using both for similar functions is only going to cause problems. Not to mention that I've been in shops using several widely different platforms to do similar things, and it wasn't fun.
Third, there are some things that just have to be standardized. We couldn't operate half with VS 2005 and VS 2008, since we keep project files under source control. We had to pick a time and convert over.
Fourth, in some businesses, it simplifies the regulatory problems. I don't know what business you're in. I work at a place where we can get away with making mistakes right now, but I've also contracted at a bank and a utility, where it's necessary to be able to show auditors that everything is going in a standard way.
Fifth, it can simplify procurement, if you're dealing with software that costs money.
This doesn't particularly limit us, since if there's something we need that isn't standardized on we just go ahead and get it or do it.
If you want to make a business case against standardization, you'll need to have a business-related argument. Your argument seems to be that you won't be able to implement features the user wants, and that is a consideration. Got another argument?
There's nothing wrong with standardizing on an IDE that is rich enough to be configured for individual developers.
However, do make sure that you don't prevent individual developers from using additional tools, as long as the tools are licensed and that the use of the tool by one developer doesn't require all other developers to use it.
For instance, I happen to use NORMA to help me design databases. The output is SQL Server DDL (or anything else I want). I can make the DDL part of the project without making my NORMA source part of it. Later developers do not need to use NORMA to work on the project.
On the other hand, if I decided to use the Configuration Section Designer to create configuration sections, then future developers would also have to use it. A decision would need to be made about whether to use that tool.
The company I work for uses C#, ASP.NET, JavaScript and generates HTML. The advantages over and above those mentioned above are that there is a perception of improved velocity for maintenance and adaptive changes. The disadvantages include generating some boredom for people who are technically savvy (geeky) and prefer to use a mix and match of languages, depending on what they fancy is better suited, or for 'performance reasons'.
Technical and personal supervision is always good to have when you are developing as fast as you can to meet tight deadlines and competing in a highly saturated market for web development.
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I'm a new software architect/lead, coming up with software design for a team of software developers. I'm coming up with the requirement spec, interface header files, and visio software design docs, and build plan, etc.
My question is: what do the rest of the team do during this period? I'm certainly engaging them in the design, but we dont need the whole team actively working on what I'm doing all the time.
Are there any good books for new software architect?
Generally the various stages overlap, so there will be some coding during design etc. There are a lot of things to do besides that. They can be reviewing unfamiliar technology that is going to be used, setting up source control system, reviewing business requirements, reviewing your documents to make sure they make sense and are clear. There is a lot of other work to be done besides programming.
What a software team does while the lead does the design is very different from company to company. On my company we try to work on the design while the developers are finalizing other projects or solving bugs.
Another approach that I've taken when starting a whole new project is to get the developers to work on the design as well - people with a good understanding of the requirements can help you designing smaller parts of the system and writing the specs for them. Others can work on mockups, frameworks. This worked rather well for the small software team I led in a previous job (4 developers in total).
I also found it useful to have other team members research parts I'm unsure of (or even validating that things I think should work will indeed work), such as:
Investigating whether an external API provides the features we need
Writing a small proof of concept or technology demonstrator
Create an API mockup (header file, interface or REST endpoint) to investigate whether the API looks useful.
As other have said, you typically want a ramp-up period during the first part of the project, and through the first iteration. You're planning on building this iteratively, aren't you? Start with a core team (nor more than 3-4 people, since you're going to need to communicate heavily with each other) to help you explore the requirements, get a basic data model in place, identify and setup any frameworks, identify and setup build and test tools. Some coding activities typically take place in the design phase: for UI mockups, run-ahead prototypes of technically sensitive areas (whatever risks you have should be mitigated by explirative coding: be they new technologies, undocumented interfaces to integrated systems, or unstable requirements).
But coders in the design phase should help with the design, in order to get their buy-in, and to help train up the rest of the team during the first iterations. Your role during this is to ensure that the major nonfunctional requirements (e.g. are known, prioritized, are met by the design, and can be tested). You should also collaborate with the project lead or whoever else is responsible for staffing and financing in order to sketch out the iterations and the staffing levels needed. Ensure the solution can be built iteratively, and aim at implementing only a basic structure during the first iteration, both to build confidence, and to eliminate risks. (Sometimes, you can push major risks to the second iteration, and focus the first towards confidence and team building.)
And of course, be sure you are not designing every detail. You should be able to use every design artifact in the next iteration (and elaborate them later as needed). Since design decisions are expensive to change, try to postpone them. However, some influence the entire solution (for instance, the data model, or your approach to security) and absolutely must be at least outlined up front. This isn't waterfall. This is just not closing your eyes and hoping a viable architecture will emerge by magic.
But design proceeds throughout the iterations. It's just that you do less of it as you go along, and with lesser impact on the solution (unless you're unlucky... and then things get expensive).
Stop doing the useless things you do and just start coding with them! ;)
If there is no overlap with another ongoing project, getting them involved as you're doing is great, maybe push it a little further by having them prototype and present the plus and minus of alternative technologies (APIs, frameworks, libraries, etc...) that your project could use.
As a new software architect, I can recommend some books that helped me understand the role of the architect (but of course not to master it):
Fundamentals of Software Architecture An Engineering Approach:
This book gives good modern overview of software architecture and its many aspects, good place to start if you are a beginner or broaden your knowlage.
Software Architecture in Practice:
Explains what software architecture is, why it's important, and how to design, instantiate, analyze, evolve, and manage it in disciplined and effective ways.
Software Architect's Handbook:
This book takes you through all the important concepts, right from design principles to different considerations at various stages of your career in software architecture. It begins by covering the fundamentals, benefits, and purpose of software architecture.
Clean Architecture: A Craftsman's Guide to Software Structure and Design:
Learn what software architects need to achieve and how to achieve it, master essential software design principles and see how designs and architectures go wrong.
Software Architecture: The Hard Parts:
An advanced architecture book, with this book, you'll learn how to think critically about the trade-offs involved with distributed architectures.
Usually there's another project they can work on, but...
I have my team review the project specs/requirements and put together a basic/preliminary structure to get them already thinking through the application and working out specific questions.
When we convene at the table to discuss the plan they already have an idea of what the project is and requires and in some cases, they present questions I may have missed or overlooked.
Although it's too late now, a good way to approach it is to move the architect over before his current project has ended. Start freeing him up at like 25% then work your way up to 75-100% on the new project a month or two before it starts (maybe more depending on how much analysis and customer interaction there is).
On a trivial project (let's say 2 man-years) it might not be necessary, but anything bigger than that can end up in chaos if somebody doesn't at least get the analysis right before everybody jumps aboard.
If your team does not have any other projects to work on, ask experienced programmers of your your team to come up with at prototype so that you can create a requirement doc according to the needs of the client.
Also programmers novice to the technologies being used in the team could utilize this time to familiarize themselves with the technologies on which your team is going to develop the project.
architect != designer
Chances are that all of your developers can help with the design; let them. Architects don't have to be "lone wolves" and do everything themselves. You lay out the guidelines and the principles and the scaffolding, rough in the wiring, and let your developers flesh out the details - whether it is drawing Visio diagrams or building prototypes to mitigate unknowns/risks.
Migrate towards Agile/XP and away from waterfall methods, and you'll find the team a lot more help.
When making the general design, it's very handy to have programmers create proof-of-concepts. Do that especially with parts of the system that could end up being show stoppers if they don't work in the way you plan to do them, so you can think of alternatives, and adjust the design.
That's going to help you to make the right design-decisions before moving entirely into a certain direction.
Just doing a design, and then moving on and start coding is a sure way to mess up a project. You won't realize that your design is not feasible (or just plain sucks) until you're half-way coding, and by then it's too late to make radical changes.
You'll waste time mitigating non-existing problems during the design, and you'll run into unforeseen problems during implementation.
I'm at a point in my freelance career where I've developed several web applications for small to medium sized businesses that support things such as project management, booking/reservations, and email management.
I like the work but find that eventually my applications get to a point where the overhear for maintenance is very high. I look back at code I wrote 6 months ago and find I have to spend a while just relearning how I originally coded it before I can make a fix or feature additions. I do try to practice using frameworks (I've used Zend Framework before, and am considering Django for my next project)
What techniques or strategies do you use to plan out an application that is capable of handling a lot of users without breaking and still keeping the code clean enough to maintain easily?
If anyone has any books or articles they could recommend, that would be greatly appreciated as well.
Although there are certainly good articles on that topic, none of them is a substitute of real-world experience.
Maintainability is nothing you can plan straight ahead, except on very small projects. It is something you need to take care of during the whole project. In fact, creating loads of classes and infrastructure code in advance can produce code which is even harder to understand than naive spaghetti code.
So my advise is to clean up your existing projects, by continuously refactoring them. Look at the parts which were a pain to change, and strive for simpler solutions that are easier to understand and to adjust. If the code is even too bad for that, consider rewriting it from scratch.
Don't start new projects and expect them to succeed, just because your read some more articles or used a new framework. Instead, identify the failures of your existing projects and fix their specific problems. Whenever you need to change your code, ask yourself how to restructure it to support similar changes in the future. This is what you need to do anyway, because there will be similar changes in the future.
By doing those refactorings you'll stumble across various specific questions you can ask and read articles about. That way you'll learn more than by just asking general questions and reading general articles about maintenance and frameworks.
Start cleaning up your code today. Don't defer it to your future projects.
(The same is true for documentation. Everyone's first docs were very bad. After several months they turn out to be too verbose and filled with unimportant stuff. So complement the documentation with solutions to the problems you really had, because chances are good that next year you'll be confronted with a similar problem. Those experiences will improve your writing style more than any "how to write good" style guide.)
I'd honestly recommend looking at Martin Fowlers Patterns of Enterprise Application Architecture. It discusses a lot of ways to make your application more organized and maintainable. In addition, I would recommend using unit testing to give you better comprehension of your code. Kent Beck's book on Test Driven Development is a great resource for learning how to address change to your code through unit tests.
To improve the maintainability you could:
If you are the sole developer then adopt a coding style and stick to it. That will give you confidence later when navigating through your own code about things you could have possibly done and the things that you absolutely wouldn't. Being confident where to look and what to look for and what not to look for will save you a lot of time.
Always take time to bring documentation up to date. Include the task into development plan; include that time into the plan as part any of change or new feature.
Keep documentation balanced: some high level diagrams, meaningful comments. Best comments tell that cannot be read from the code itself. Like business reasons or "whys" behind certain chunks of code.
Include into the plan the effort to keep code structure, folder names, namespaces, object, variable and routine names up to date and reflective of what they actually do. This will go a long way in improving maintainability. Always call a spade "spade". Avoid large chunks of code, structure it by means available within your language of choice, give chunks meaningful names.
Low coupling and high coherency. Make sure you up to date with techniques of achieving these: design by contract, dependency injection, aspects, design patterns etc.
From task management point of view you should estimate more time and charge higher rate for non-continuous pieces of work. Do not hesitate to make customer aware that you need extra time to do small non-continuous changes spread over time as opposed to bigger continuous projects and ongoing maintenance since the administration and analysis overhead is greater (you need to manage and analyse each change including impact on the existing system separately). One benefit your customer is going to get is greater life expectancy of the system. The other is accurate documentation that will preserve their option to seek someone else's help should they decide to do so. Both protect customer investment and are strong selling points.
Use source control if you don't do that already
Keep a detailed log of everything done for the customer plus any important communication (a simple computer or paper based CMS). Refresh your memory before each assignment.
Keep a log of issues left open, ideas, suggestions per customer; again refresh your memory before beginning an assignment.
Plan ahead how the post-implementation support is going to be conducted, discuss with the customer. Make your systems are easy to maintain. Plan for parameterisation, monitoring tools, in-build sanity checks. Sell post-implementation support to customer as part of the initial contract.
Expand by hiring, even if you need someone just to provide that post-implementation support, do the admin bits.
Recommended reading:
"Code Complete" by Steve Mcconnell
Anything on design patterns are included into the list of recommended reading.
The most important advice I can give having helped grow an old web application into an extremely high available, high demand web application is to encapsulate everything. - in particular
Use good MVC principles and frameworks to separate your view layer from your business logic and data model.
Use a robust persistance layer to not couple your business logic to your data model
Plan for statelessness and asynchronous behaviour.
Here is an excellent article on how eBay tackles these problems
http://www.infoq.com/articles/ebay-scalability-best-practices
Use a framework / MVC system. The more organised and centralized your code is the better.
Try using Memcache. PHP has a built in extension for it, it takes about ten minutes to set up and another twenty to put in your application. You can cache whatever you want to it - I cache all my database records in it - for every application. It does wanders.
I would recommend using a source control system such as Subversion if you aren't already.
You should consider maybe using SharePoint. It's an environment that is already designed to do all you have mentioned, and has many other features you maybe haven't thought about (but maybe you will need in the future :-) )
Here's some information from the official site.
There are 2 different SharePoint environments you can use: Windows Sharepoint Services (WSS) or Microsoft Office Sharepoint Server (MOSS). WSS is free and ships with Windows Server 2003, while MOSS isn't free, but has much more features and covers almost all you enterprise's needs.
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Our system (exotic commodity derivative trade capture and risk management) is being redeveloped shortly. One proposal that I have heard is that a rule engine will be incorporated to make it easier for the end-users (commodities traders, so fairly sophisticated) to make certain changes to the business logic.
I am a little skeptical of rules engines. The agilist in me wonders if they are just a technical solution to a process problem... ie. it takes too long for our developers to respond to the business's need for change. The solution to that problem should be a more collaborative approach to development, better test coverage, more agile practices all around.
Hearing about situations where a rule engine was truly a boon (especially in a trading environment) would be certainly helpful.
I've seen two applications that used the Blaze Rete engine from Fair Issac.
One application slammed thousands of rules into a single knowledge base, had terrible memory problems, has become a black box that few understand. I would not call that a success, but it is running in production.
Another application used decision trees to represent on the order of hundreds of questions on a medical form to disposition clients. It was done so elegantly that business people can update the rules as needed, without having to involve a developer. (Still has to be deployed by one, though.) I'd call that a great success.
So it depends on how well focused the problem is, the size of the rule set, the knowledge of the developers. My prejudice is that simply making a rules engine a single point of failure and dumping rules into it probably isn't a good approach. I'd start with a data-driven or table-driven approach and grow that until a rules engine was needed. I'd also strive to encapsulate the rules engine as part of the behavior of an object. I'd hide the rules engine from users and try to partition the rules space into the domain model.
I don't know if I'd say they're ever truly a boon, but I think they can certainly be valuable. I worked on a system for a few years in the insurance industry, where a rules engine was employed quite successfully to allow the business users to create rules that determined what policies were legal, depending on the state.
For instance, if you had to have a copay in certain states, or certain combinations of deductible and copay were not allowed, either because of product considerations, or because it was simply illegal due to state law.
The number of states that the company operated in, along with the constant change in rules (quarterly) would make this a dizzying coding practice. More importantly, it's not in the expertise of a programmer. It adds extra pointless communication where the end user is describing the rule to be put in effect to a programmer who is not an insurance industry expert like they are.
Designed correctly, a rules engine can still enable a workflow system that allows for good testing. In this case, the rules were stored in a database, and there were QA and PROD databases. So the BA's could test their rules in QA, and then promote them to PROD.
As with anything, its usually about the implementation, and not the actual technique.
Yes, Microsoft has a Business Rule Engine (BRE) in BizTalk that has been used successfully for years. I've heard that they've had clients buy BizTalk (very expensive) just for the BRE.
In my experience, the practicality of having a business user update the rules is slim to none. It usually takes a technical person to work the business rules editor.
A rule engine is little more than something that executes declarative statements. They come with two primary advantages (that I see):
Your business logic is maintained from a single place instead of being sprinkled throughout application code. Technically, a well-designed application should already do this with the architecture, regardless of a rule engine being present or not.
You need to worry [less] about dependencies between declarative statements. The rule engine should be smart enough to decide the order to run rules based on dependencies. You may find that some rule engines support a sequential ordering of rules within a ruleset or calling rulesets (groups of rules) in a particular order, but this isn't really in the spirit of declarative programming. Many rule engines use Rete (an algorithm) to decide when to schedule the execution of declarative statements.
I suspect most, if not all, rule engines add more overhead than if you were to write the best possible program that doesn't use a rule engine. This is similar to how writing code in assembly is generally faster than a compiler (but you usually don't write assembly because it's more convenient and productive to use higher-level abstractions).
If you were to stop here, then you would probably use programmers to maintain rules and use a rule engine as a convenient way to build a business logic tier in your application. Some rule engines offer something called templates that let you define templates for rules. The advantage here is that non-technical users are supposed to be able to write their own rules and modify existing rules.
A rule engine is one more tool in your tool chest that, when used properly, can be valuable.
The problem with many of these rule engines are the lack of speed and the fact that replacing or augmenting rules can break existing working rules in subtle ways. So you still have to re-test the system thoroughly after each rule change. So you're basically just exchanging one computer language for another one - one with a much smaller base of users. As another poster mentioned, I've yet to see a business analyst successfully use a rule engine. You need a programmer anyway.
I certainly have, but can't publicly talk about them, but its likely you have interacted with one several times this year ;)
I see it in 2 camps: the logic programmers and the business users. Different tools target different sets, some both. The successful cases of business users have only worked when it was a subset of the logic, and they also had a way to define test cases and run them themselves (and they are prepared to think logically).
Logic programmers are rarer, but can often be found coming from non imperative programming backgrounds (they are also the sort of people that find functional programming intuitive).
Keep in mind at the end of the day even with visual tools, if you are telling a computer to do something it is still programming.
I work with lots of vendors in the space and one of the great things about this is that I get to talk to lots of their customers. So, yes, hundreds of companies have got exactly the benefits they were promised - increased agility, better business/IT collaboration, easier regulatory compliance, better consistency of decision making, lower maintenance costs, faster times to market etc.
Over and over again, across all the major vendors and the open source players, I see that used correctly - to automate and improve high-volume operational decisions with many rules, rules that change a lot, rules that interact in complex ways or rules with a high business domain content - business rules management systems work.
Really.
My experience is limited to (i)not much and (ii)prolog; but I can safely say that a rule engine can help you express propositional concepts much cleaner than procedural code.
Rules engines are routinely used in the insurance business. I've worked on systems with hundreds (600ish) rules that were implemented in a rules engine. It worked very well.
Do you have a credit rating? A FICO score, perhaps? That's Fair Isaac COrporation, the developers of the Blaze rules engine.
For a while I worked for the PEATE distributed computing project which was developing a system for calculation of large scale, high volume atmospheric data. The system had three parts to it: the data manager, the scheduler, and the algorithm execution component. There could be any number of any of these components, all done through web services, but what it allowed for was for different researchers to execute arbitrary jobs against arbitrary data, and also allowed for different scheduling mechanisms to be plugged in as requirements changed.
I left the project before it got too far off the ground, but this seems like it could potentially fit the scenario, and serve as another example for some kind of rule engine. That being said, however, if the original developers are still going to be the one's making the algorithms to run, I can't see too much benefit in having a rule engine unless it handled a substantial overhead that each rule or algorithm would incur on it's own.
This sounds like a bit more involved than a simple rule engine, but such an architecture could feasibly apply to a rule engine as well.