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When developing XPages applications it seems to have become very popular to mainly use Java methods and beans instead of server-side JavaScript (SSJS). SSJS of course takes longer to execute because the code has to be evaluated at runtime. However, can anyone provide information about the QUANTITATIVE gain in performance when using Java? Are there any benchmarks for how much the execution times differ, for example depending on the length of the SSJS code or the functions used?
You have to use your own benchmarks. The increase in time might not be measurable. It is more around capabilities and your development process. Switching from SSJS to Java an expecting an instant increase in performance most likely won't happen.
Unless of course Java allows you to code things differently. So most of the decisions are based on capabilities, not speed. You are most welcome to run some tests and share the insights. What you can expect e.g. opening a document in SSJS vs. Java: the difference should be in the space of a rounding error, since most of the time is needed for the C call below.
SSJS and Java run at almost the same speed after the SSJS has been evaluated, so you have some onramp time and similar speed thereafter.
I agree about the performance gain being negligible. I will chime in to say this. Right now I am trying to learn to support an existing XPages application written without using any java, and entirely in SSJS. There is code here, there, and everywhere. It is very hard to follow.
Depending on your environment, you should consider programmer productivity when considering how to build your applications, especially when you know both. Productivity for you, and those coming after you.
Stephan's answer is right on point: though Java as a language IS faster (you'd probably see performance gains proportional to the complexity of the block of code more than the number of operations running), the primary benefit is program structure. My experience has been that using Java extensively makes my code much cleaner, easier to debug, and MUCH easier to understand after coming back to it months later.
One of the nice side effects of this structural change does happen to be performance, but not because of anything inherent to Java: by focusing on classes and getters/setters, it makes it easier to really pay attention to expensive operations and caching. While you CAN cache your data excellently in SSJS using the various scopes, it's easier for your brain - both now and after you've forgotten what you did next year - to think about that sort of thing in Java.
Personally, even if Java executed more slowly than SSJS but the programming models in XPages were the same as they are now, I would still use Java primarily.
You are asking about the pure processing performance - the speed of the computer running the code. And as Stephen stated Java is going to be a "little" faster because it doesn't need to do the extra step of the string parsing the code first. Ok in the big picture that's really not a big deal.
I think the real "performance" gain that you get by moving to Java in XPages is cleaner code with more capabilities. Yes you're putting a lot of code in SSJS Libraries. And that can work really well. But I assume those are more individual functions that you use over and over rather then true objects that you can put in memory and they're they're when you need them. When you get your core business logic inside Java Objects in my experience the speed of development goes significantly faster. It's not even close.
Take the Domino document object. That's a rather handy object. Imagine if it wasn't an "object" but simply a library of 50 or so functions that you need to first paste into each database. Doesn't seem right. And of course in the Domino API it's not just the domino object. There's like 60 or so different objects!
Typical XPages with Java development moves much - not all - but much of the code away from the .xsp page and into Java Classes which are very similar to custom classes on LotusScript. The not only creates separation between frontend code - making the .xsp pages easier to work with - but puts the business logic inside Java which is similar to working to the the Domino backend objects. So then the backend gets easier to work with, maintain and add onto.
And that's where a big part of the development speed improvements come from.
Getting back to your original question, which is about computer speed. I would suggest that it's much easier to cache frequently used data via Java Objects and managed beans then it is with SSJS. Not having to hit the disc as much would be a real speed advantage.
I would recommend you to consider performance gain in a wider context.
performance gain in quicker running?
performance gain in typing?
performance gain in not making mistakes because of the editor?
performance gain of using templating in the Java editor?
performance gain in better reusability, eventually to server-wide plugins?
performance gain in being comfortable building your own classes to hold complex objects?
performance gain in easier debugging?
performance gain in being comfortable with Validators, Converters, Phase Listeners, VariableResolvers etc?
performance gain in being comfortable looking at Extension Libraries to investigate or extend?
performance gain of being able to find answers more easily on StackOverflow or Google because you're using a standard language vs a proprietary language?
performance gain in using third party Java code like Apache Commons, Apache POI etc?
To be honest, when you have got that far and understand how much code is run during a page load or partial request, performance gain in runtime of Java vs SSJS is minimal compared to something like using loaded where possible instead of rendered. The gains of Java over SSJS are much wider, and I have not even mentioned the gains in professional development.
My answer is way too long for a stackOverflow answer, so as promised, here is a link to my blog post about this issue. Basically it has nothing to do with performance, but with Maintainability, Readability, Usability
I am working on projects basically ecommerce type. our architect has got instructions from client to use PLINQ as its much more beneficial than LINQ, as they works in parallel and uses all cores of the processors, resulting in quick responses. Client suggestion is PLINQ + Repository if possible.
So I just want to know, which one is good to follow in small and medium app. Is it feasible to use Plinq + Repository. As per my findings, I found Plinq has more overhead than linq if we are not handling the stuffs properly. Please help me.
It is impossible to answer this question without knowing far more details about your application. PLINQ has overhead to fan out the workload to worker threads and then coordinate the work amongst them. If you are processing hundreds of thousands of entities and have a meaningful amount of work to do for each one, then yes it can benefit. In the end, the only way to really know if PLINQ will benefit you is to profile using a realistic data set.
When a for loop has a small body, it might perform more slowly than the equivalent sequential loop. Slower performance is caused by the overhead involved in partitioning the data and the cost of invoking a delegate on each loop iteration. To address such scenarios, the Partitioner class provides the Partitioner.Create method, which enables you to provide a sequential loop for the delegate body, so that the delegate is invoked only once per partition, instead of once per iteration.
See here.
This applies to PLINQ.
See here for PLINQ.
LOL.
He who pays the piper calls the tune
Generally though, this is an engineering issue. Talk to the architects and clients and work out what what metrics they will be using to measure the performance of the deliverables.
Then using these metrics find the optimal solution Linq, PLinq or other and then report back your findings.
In the main all technologies are good for something and the size of the app is measured in different ways. So your term 'small' is meaningless.
My company currently runs a third-party simulation program (natural catastrophe risk modeling) that sucks up gigabytes of data off a disk and then crunches for several days to produce results. I will soon be asked to rewrite this as a multi-threaded app so that it runs in hours instead of days. I expect to have about 6 months to complete the conversion and will be working solo.
We have a 24-proc box to run this. I will have access to the source of the original program (written in C++ I think), but at this point I know very little about how it's designed.
I need advice on how to tackle this. I'm an experienced programmer (~ 30 years, currently working in C# 3.5) but have no multi-processor/multi-threaded experience. I'm willing and eager to learn a new language if appropriate. I'm looking for recommendations on languages, learning resources, books, architectural guidelines. etc.
Requirements: Windows OS. A commercial grade compiler with lots of support and good learning resources available. There is no need for a fancy GUI - it will probably run from a config file and put results into a SQL Server database.
Edit: The current app is C++ but I will almost certainly not be using that language for the re-write. I removed the C++ tag that someone added.
Numerical process simulations are typically run over a single discretised problem grid (for example, the surface of the Earth or clouds of gas and dust), which usually rules out simple task farming or concurrency approaches. This is because a grid divided over a set of processors representing an area of physical space is not a set of independent tasks. The grid cells at the edge of each subgrid need to be updated based on the values of grid cells stored on other processors, which are adjacent in logical space.
In high-performance computing, simulations are typically parallelised using either MPI or OpenMP. MPI is a message passing library with bindings for many languages, including C, C++, Fortran, Python, and C#. OpenMP is an API for shared-memory multiprocessing. In general, MPI is more difficult to code than OpenMP, and is much more invasive, but is also much more flexible. OpenMP requires a memory area shared between processors, so is not suited to many architectures. Hybrid schemes are also possible.
This type of programming has its own special challenges. As well as race conditions, deadlocks, livelocks, and all the other joys of concurrent programming, you need to consider the topology of your processor grid - how you choose to split your logical grid across your physical processors. This is important because your parallel speedup is a function of the amount of communication between your processors, which itself is a function of the total edge length of your decomposed grid. As you add more processors, this surface area increases, increasing the amount of communication overhead. Increasing the granularity will eventually become prohibitive.
The other important consideration is the proportion of the code which can be parallelised. Amdahl's law then dictates the maximum theoretically attainable speedup. You should be able to estimate this before you start writing any code.
Both of these facts will conspire to limit the maximum number of processors you can run on. The sweet spot may be considerably lower than you think.
I recommend the book High Performance Computing, if you can get hold of it. In particular, the chapter on performance benchmarking and tuning is priceless.
An excellent online overview of parallel computing, which covers the major issues, is this introduction from Lawerence Livermore National Laboratory.
Your biggest problem in a multithreaded project is that too much state is visible across threads - it is too easy to write code that reads / mutates data in an unsafe manner, especially in a multiprocessor environment where issues such as cache coherency, weakly consistent memory etc might come into play.
Debugging race conditions is distinctly unpleasant.
Approach your design as you would if, say, you were considering distributing your work across multiple machines on a network: that is, identify what tasks can happen in parallel, what the inputs to each task are, what the outputs of each task are, and what tasks must complete before a given task can begin. The point of the exercise is to ensure that each place where data becomes visible to another thread, and each place where a new thread is spawned, are carefully considered.
Once such an initial design is complete, there will be a clear division of ownership of data, and clear points at which ownership is taken / transferred; and so you will be in a very good position to take advantage of the possibilities that multithreading offers you - cheaply shared data, cheap synchronisation, lockless shared data structures - safely.
If you can split the workload up into non-dependent chunks of work (i.e., the data set can be processed in bits, there aren't lots of data dependencies), then I'd use a thread pool / task mechanism. Presumably whatever C# has as an equivalent to Java's java.util.concurrent. I'd create work units from the data, and wrap them in a task, and then throw the tasks at the thread pool.
Of course performance might be a necessity here. If you can keep the original processing code kernel as-is, then you can call it from within your C# application.
If the code has lots of data dependencies, it may be a lot harder to break up into threaded tasks, but you might be able to break it up into a pipeline of actions. This means thread 1 passes data to thread 2, which passes data to threads 3 through 8, which pass data onto thread 9, etc.
If the code has a lot of floating point mathematics, it might be worth looking at rewriting in OpenCL or CUDA, and running it on GPUs instead of CPUs.
For a 6 month project I'd say it definitely pays out to start reading a good book about the subject first. I would suggest Joe Duffy's Concurrent Programming on Windows. It's the most thorough book I know about the subject and it covers both .NET and native Win32 threading. I've written multithreaded programs for 10 years when I discovered this gem and still found things I didn't know in almost every chapter.
Also, "natural catastrophe risk modeling" sounds like a lot of math. Maybe you should have a look at Intel's IPP library: it provides primitives for many common low-level math and signal processing algorithms. It supports multi threading out of the box, which may make your task significantly easier.
There are a lot of techniques that can be used to deal with multithreading if you design the project for it.
The most general and universal is simply "avoid shared state". Whenever possible, copy resources between threads, rather than making them access the same shared copy.
If you're writing the low-level synchronization code yourself, you have to remember to make absolutely no assumptions. Both the compiler and CPU may reorder your code, creating race conditions or deadlocks where none would seem possible when reading the code. The only way to prevent this is with memory barriers. And remember that even the simplest operation may be subject to threading issues. Something as simple as ++i is typically not atomic, and if multiple threads access i, you'll get unpredictable results.
And of course, just because you've assigned a value to a variable, that's no guarantee that the new value will be visible to other threads. The compiler may defer actually writing it out to memory. Again, a memory barrier forces it to "flush" all pending memory I/O.
If I were you, I'd go with a higher level synchronization model than simple locks/mutexes/monitors/critical sections if possible. There are a few CSP libraries available for most languages and platforms, including .NET languages and native C++.
This usually makes race conditions and deadlocks trivial to detect and fix, and allows a ridiculous level of scalability. But there's a certain amount of overhead associated with this paradigm as well, so each thread might get less work done than it would with other techniques. It also requires the entire application to be structured specifically for this paradigm (so it's tricky to retrofit onto existing code, but since you're starting from scratch, it's less of an issue -- but it'll still be unfamiliar to you)
Another approach might be Transactional Memory. This is easier to fit into a traditional program structure, but also has some limitations, and I don't know of many production-quality libraries for it (STM.NET was recently released, and may be worth checking out. Intel has a C++ compiler with STM extensions built into the language as well)
But whichever approach you use, you'll have to think carefully about how to split the work up into independent tasks, and how to avoid cross-talk between threads. Any time two threads access the same variable, you have a potential bug. And any time two threads access the same variable or just another variable near the same address (for example, the next or previous element in an array), data will have to be exchanged between cores, forcing it to be flushed from CPU cache to memory, and then read into the other core's cache. Which can be a major performance hit.
Oh, and if you do write the application in C++, don't underestimate the language. You'll have to learn the language in detail before you'll be able to write robust code, much less robust threaded code.
One thing we've done in this situation that has worked really well for us is to break the work to be done into individual chunks and the actions on each chunk into different processors. Then we have chains of processors and data chunks can work through the chains independently. Each set of processors within the chain can run on multiple threads each and can process more or less data depending on their own performance relative to the other processors in the chain.
Also breaking up both the data and actions into smaller pieces makes the app much more maintainable and testable.
There's plenty of specific bits of individual advice that could be given here, and several people have done so already.
However nobody can tell you exactly how to make this all work for your specific requirements (which you don't even fully know yourself yet), so I'd strongly recommend you read up on HPC (High Performance Computing) for now to get the over-arching concepts clear and have a better idea which direction suits your needs the most.
The model you choose to use will be dictated by the structure of your data. Is your data tightly coupled or loosely coupled? If your simulation data is tightly coupled then you'll want to look at OpenMP or MPI (parallel computing). If your data is loosely coupled then a job pool is probably a better fit... possibly even a distributed computing approach could work.
My advice is get and read an introductory text to get familiar with the various models of concurrency/parallelism. Then look at your application's needs and decide which architecture you're going to need to use. After you know which architecture you need, then you can look at tools to assist you.
A fairly highly rated book which works as an introduction to the topic is "The Art of Concurrency: A Thread Monkey's Guide to Writing Parallel Application".
Read about Erlang and the "Actor Model" in particular. If you make all your data immutable, you will have a much easier time parallelizing it.
Most of the other answers offer good advice regarding partitioning the project - look for tasks that can be cleanly executed in parallel with very little data sharing required. Be aware of non-thread safe constructs such as static or global variables, or libraries that are not thread safe. The worst one we've encountered is the TNT library, which doesn't even allow thread-safe reads under some circumstances.
As with all optimisation, concentrate on the bottlenecks first, because threading adds a lot of complexity you want to avoid it where it isn't necessary.
You'll need a good grasp of the various threading primitives (mutexes, semaphores, critical sections, conditions, etc.) and the situations in which they are useful.
One thing I would add, if you're intending to stay with C++, is that we have had a lot of success using the boost.thread library. It supplies most of the required multi-threading primitives, although does lack a thread pool (and I would be wary of the unofficial "boost" thread pool one can locate via google, because it suffers from a number of deadlock issues).
I would consider doing this in .NET 4.0 since it has a lot of new support specifically targeted at making writing concurrent code easier. Its official release date is March 22, 2010, but it will probably RTM before then and you can start with the reasonably stable Beta 2 now.
You can either use C# that you're more familiar with or you can use managed C++.
At a high level, try to break up the program into System.Threading.Tasks.Task's which are individual units of work. In addition, I'd minimize use of shared state and consider using Parallel.For (or ForEach) and/or PLINQ where possible.
If you do this, a lot of the heavy lifting will be done for you in a very efficient way. It's the direction that Microsoft is going to increasingly support.
2: I would consider doing this in .NET 4.0 since it has a lot of new support specifically targeted at making writing concurrent code easier. Its official release date is March 22, 2010, but it will probably RTM before then and you can start with the reasonably stable Beta 2 now. At a high level, try to break up the program into System.Threading.Tasks.Task's which are individual units of work. In addition, I'd minimize use of shared state and consider using Parallel.For and/or PLINQ where possible. If you do this, a lot of the heavy lifting will be done for you in a very efficient way. 1: http://msdn.microsoft.com/en-us/library/dd321424%28VS.100%29.aspx
Sorry i just want to add a pessimistic or better realistic answer here.
You are under time pressure. 6 month deadline and you don't even know for sure what language is this system and what it does and how it is organized. If it is not a trivial calculation then it is a very bad start.
Most importantly: You say you have never done mulitithreading programming before. This is where i get 4 alarm clocks ringing at once. Multithreading is difficult and takes a long time to learn it when you want to do it right - and you need to do it right when you want to win a huge speed increase. Debugging is extremely nasty even with good tools like Total Views debugger or Intels VTune.
Then you say you want to rewrite the app in another lanugage - well this isn't as bad as you have to rewrite it anyway. THe chance to turn a single threaded Program into a well working multithreaded one without total redesign is almost zero.
But learning multithreading and a new language (what is your C++ skills?) with a timeline of 3 month (you have to write a throw away prototype - so i cut the timespan into two halfs) is extremely challenging.
My advise here is simple and will not like it: Learn multithreadings now - because it is a required skill set in the future - but leave this job to someone who already has experience. Well unless you don't care about the program being successfull and are just looking for 6 month payment.
If it's possible to have all the threads working on disjoint sets of process data, and have other information stored in the SQL database, you can quite easily do it in C++, and just spawn off new threads to work on their own parts using the Windows API. The SQL server will handle all the hard synchronization magic with its DB transactions! And of course C++ will perform a lot faster than C#.
You should definitely revise C++ for this task, and understand the C++ code, and look for efficiency bugs in the existing code as well as adding the multi-threaded functionality.
You've tagged this question as C++ but mentioned that you're a C# developer currently, so I'm not sure if you'll be tackling this assignment from C++ or C#. Anyway, in case you're going to be using C# or .NET (including C++/CLI): I have the following MSDN article bookmarked and would highly recommend reading through it as part of your prep work.
Calling Synchronous Methods Asynchronously
Whatever technology your going to write this, take a look a this must read book on concurrency "Concurrent programming in Java" and for .Net I highly recommend the retlang library for concurrent app.
I don't know if it was mentioned yet, but if I were in your shoes, what I would be doing right now (aside from reading every answer posted here) is writing a multiple threaded example application in your favorite (most used) language.
I don't have extensive multithreaded experience. I've played around with it in the past for fun but I think gaining some experience with a throw-away application will suit your future efforts.
I wish you luck in this endeavor and I must admit I wish I had the opportunity to work on something like this...
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I had a piece of work thrown out due to a single minor spec change that turned out not to have been spec'ed correctly. If it had been done right at the start of the project then most of that work would have never have been needed in the first place.
What are some good tips/design principles that keep these things from happening?
Or to lessen the amount of re-working to code that is needed in order to implement feature requests or design changes mid implementation?
Modularize. Make small blocks of code that do their job well. However, thats only the beginning. Its usually a large combination of factors that contribute to code so bad it needs a complete rework. Everything from highly unstable requirements, poor design, lack of code ownership, the list goes on and on.
Adding on to what others have brought up: COMMUNICATION.
Communication between you and the customer, you and management, you and the other developers, you and your QA department, communication between everyone is key. Make sure management understands reasonable timeframes and make sure both you and the customer understand exactly what it is that your building.
Take the time to keep communication open with the customer that your building the product for. Make milestones and setup a time to display the project to the customer at each milestone. Even if the customer is completely disappointed with a milestone when you show it, you can scratch what you have and start over from the last milestone. This also requires that your work be built in blocks that work independent of one another as Csunwold stated.
Points...
Keep open communication
Be open and honest with progress of product
Be willing to change daily as to the needs of the customers business and specifications for the product change.
Software requirements change, and there's not much one can do about that except for more frequent interaction with clients.
One can, however, build code that is more robust in face of change. It won't save you from throwing out code that meets a requirement that nobody needs anymore, but it can reduce the impact of such changes.
For example, whenever this applies, use interfaces rather than classes (or the equivalent in your language), and avoid adding operations to the interface unless you are absolutely sure you need them. By building your programs that way you are less likely to rely on knowledge of a specific implementation, and you're less likely to implement things that you would not need.
Another advantage of this approach is that you can easily swap one implementation for another. For example, it sometimes pays off to write the dumbest (in efficiency) but the fastest to write and test implementation for your prototype, and only replace it with something smarter in the end when the prototype is the basis of the product and the performance actually matters. I find that this is a very effective way to avoid premature optimizations, and thus throwing away stuff.
modularity is the answer, as has been said. but it can be a hard answer to use in practice.
i suggest focussing on:
small libraries which do predefined things well
minimal dependencies between modules
writing interfaces first is a good way to achieve both of these (with interfaces used for the dependencies). writing tests next, against the interfaces, before the code is written, often highlights design choices which are un-modular.
i don't know whether your app is UI-intensive; that can make it more difficult to be modular. it's still usually worth the effort, but if not then assume that it will be thrown away before long and follow the iceberg principle, that 90% of the work is not tied to the UI and so easier to keep modular.
finally, i recommend "the pragmatic programmer" by andrew hunt and dave thomas as full of tips. my personal favourite is DRY -- "don't repeat yourself" -- any code which says the same thing twice smells.
iterate small
iterate often
test between iterations
get a simple working product out asap so the client can give input.
Basically assume stuff WILL get thrown out, so code appropriately, and don't get far enough into something that having it be thrown out costs a lot of time.
G'day,
Looking through the other answers here I notice that everyone is mentioning what to do for your next project.
One thing that seems to be missing though is having a washup to find out why the spec. was out of sync. with the actual requirements needed by the customer.
I'm just worried that if you don't do this, no matter what approach you are taking to implementing your next project, if you've still got that mismatch between actual requirements and the spec. for your next project then you'll once again be in the same situation.
It might be something as simple as bad communication or maybe customer requirement creep.
But at least if you know the cause and you can try and help minimise the chances of it happening again.
Not knocking what other answers are saying and there's some great stuff there, but please learn from what happened so that you're not condemned to repeat it.
HTH
cheers,
Sometimes a rewrite is the best solution!
If you are writing software for a camera, you could assume that the next version will also do video, or stereo video or 3d laser scanning and include all hooks for all this functionality, or you could write such a versatile extensible astronaut architecture that it could cope with the next camera including jet engines - but it will cost so much in money, resources and performance that you might have been better off not doing it.
A complete rewrite for new functionality in a new role isn't always a bad idea.
Like csunwold said, modularizing your code is very important. Write it so that if one piece falls prone to errors, it doesn't muck up the rest of the system. This way, you can debug a single buggy section while being able to safely rely on the rest.
Beyond this, documentation is key. If your code is neatly and clearly annotated, reworking it in the future will be infinitely easier for you or whoever happens to be debugging.
Using source control can be helpful too. If you find a piece of code doesn't work properly, there's always the opportunity to revert back to a past robust iteration.
Although it doesn't directly apply to your example, when writing code I try to keep an eye out for ways in which I can see the software evolving in the future.
Basically I try to anticipate where the software will go, but critically, I resist the temptation to implement any of the things I can imagine happening. All I am after is trying to make the APIs and interfaces support possible futures without implementing those features yet, in the hope that these 'possible scenarios' help me come up with a better and more future-proof interface.
Doesn't always work ofcourse.
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A couple of years ago the media was rife with all sorts of articles on
how the idea of code reuse was a simple way to improve productivity
and code quality.
From the blogs and sites I check on a regular basis it seems as though
the idea of "code reuse" has gone out of fashion. Perhaps the 'code
reuse' advocates have all joined the SOA crowd instead? :-)
Interestingly enough, when you search for 'code reuse' in Google the
second result is titled:
"Internal Code Reuse Considered Dangerous"!
To me the idea of code reuse is just common sense, after all look at
the success of the apache commons project!
What I want to know is:
Do you or your company try and reuse code?
If so how and at what level, i.e. low level api, components or
shared business logic? How do you or your company reuse code?
Does it work?
Discuss?
I am fully aware that there are many open source libs available and that anyone who has used .NET or the Java has reused code in some form. That is common sense!
I was referring more to code reuse within an organizations rather than across a community via a shared lib etc.
I originally asked;
Do you or your company try and reuse code?
If so how and at what level, i.e. low level api, components or shared business logic? How do you or your company reuse code?
From where I sit I see very few example of companies trying to reuse code internally?
If you have a piece of code which could potentially be shared across a medium size organization how would you go about informing other members of the company that this lib/api/etc existed and could be of benefit?
The title of the article you are referring to is misleading, and is actually a very good read. Code reuse is very beneficial, but there are downsides with everything. Basically, if I remember correctly, the gist of the article is that you are sealing the code in a black box and not revisiting it, so as the original developers leave you lose the knowledge. While I see the point, I don't necessarily agree with it - at least not to a "sky is falling" regard.
We actually group code reuse into more than just reusable classes, we look at the entire enterprise. Things that are more like framework enhancement or address cross-cutting concerns are put into a development framework that all of our applications use (think things like pre- and post-validation, logging, etc.). We also have business logic that is applicable to more than one application, so those sort of things get moved to a BAL core that is accessible anywhere.
I think that the important thing is not to promote things for reuse if they are not going to really be reused. They should be well documented, so that new developers can have a resource to help them come up to speed, as well. Chances are, if the knowledge isn't shared, the code will eventually be reinvented somewhere else and will lead to duplication if you are not rigorous in documentation and knowledge sharing.
We reuse code - in fact, our developers specifically write code that can be reused in other projects. This has paid off quite nicely - we're able to start new projects quickly, and we iteratively harden our core libraries.
But one can't just write code and expect it to be re-used; code reuse requires communication among team members and other users so people know what code is available, and how to use it.
The following things are needed for code reuse to work effectively:
The code or library itself
Demand for the code across multiple projects or efforts
Communication of the code's features/capabilities
Instructions on how to use the code
A commitment to maintaining and improving the code over time
Code reuse is essential. I find that it also forces me to generalize as much as possible, also making code more adaptable to varying situations. Ideally, almost every lower level library you write should be able to adapt to a new set of requirements for a different application.
I think code reuse is being done through open source projects for the most part. Anything that can be reused or extended is being done via libraries. Java has an amazing number of open source libraries available for doing a large number of things. Compare that to C++, and how early on everything would have to be implemented from scratch using MFC or the Win32 API.
We reuse code.
On a small scale we try to avoid code duplication as much as posible. And we have a complete library with a lot of frequently used code.
Normally code is developed for one application. And if it is generic enough, it is promoted to the library. This works excelent.
The idea of code reuse is no longer a novel idea...hence the apparent lack of interest. But it is still very much a good idea. The entire .NET framework and the Java API are good examples of code reuse in action.
We have grown accustomed to developing OO libraries of code for our projects and reusing them in other projects. Its a part of the natural life cycle of an idea. It is hotly debated for a while and then everyone accepts and there is no reason for further discussion.
Of course we reuse code.
There are a near infinite amount of packages, libraries and shared objects available for all languages, with whole communities of developers behing them supporting and updating.
I think the lack of "media attention" is due to the fact that everyone is doing it, so it's no longer worth writing about. I don't hear as many people raising awareness of Object-Oriented Programming and Unit Testing as I used to either. Everyone is already aware of these concepts (whether they use them or not).
Level of media attention to an issue has little to do with its importance, whether we're talking software development or politics! It's important to avoid wasting development effort by reinventing (or re-maintaining!) the wheel, but this is so well-known by now that an editor probably isn't going to get excited by another article on the subject.
Rather than looking at the number of current articles and blog posts as a measure of importance (or urgency) look at the concepts and buzz-phrases that have become classics or entered the jargon (another form of reuse!) For example, Google for uses of the DRY acronym for good discussion on the many forms of redundancy that can be eliminated in software and development processes.
There's also a role for mature judgment regarding costs of reuse vs. where the benefits are achieved. Some writers advocate waiting to worry about reuse until a second or third use actually emerges, rather than spending effort to generalize bit of code the first time it is written.
My personal view, based on the practise in my company:
Do you or your company try and reuse code?
Obviously, if we have another piece of code that already fits our needs we will reuse it. We don't go out of our way to use square pegs in round holes though.
If so how and at what level, i.e. low level api, components or shared business logic? How do you or your company reuse code?
At every level. It is written into our coding standards that developers should always assume their code will be reused - even if in reality that is highly unlikely. See below
If your OO model is good, your API probably reflects your business domain, so reusable classes probably equates to reusable business logic without additional effort.
For actual reuse, one key point is knowing what code is already available. We resolve this by having everything documented in a central location. We just need a little discipline to ensure that the documentation is up-to-date and searchable in a meaningful way.
Does it work?
Yes, but not because of the potential or actual reuse! In reality, beyond a few core libraries and UI components, there isn't a large amount of reuse.
In my personal opinion, the real value is in making the code reusable. In doing so, aside from a hopefully cleaner API, the code will (a) be documented sufficiently for another developer to use it without trawling the source code, and (b) it will also be replaceable. These points are a great benefit to on-going software maintenance.
Do you or your company try and reuse code? If so how and at what
level, i.e. low level api, components or shared business logic? How do
you or your company reuse code?
I used to work in a codebase with uber code reuse, but it was difficult to maintain because the reused code was unstable. It was prone to design changes and deprecation in ways that cascaded to everything using it. Before that I worked in a codebase with no code reuse where the seniors actually encouraged copying and pasting as a way to reuse even application-specific code, so I got to see the two extremities and I have to say that one isn't necessarily much better than the other when taken to the extremes.
And I used to be an uber bottom-up kind of programmer. You ask me to build something specific and I end up building generalized tools. Then using those tools, I build more complex generalized tools, then start building DIP abstractions to express the design requirements for the lower-level tools, then I build even more complex tools and repeat, and at some point I start writing code that actually does what you want me to do. And as counter-productive as that sounded, I was pretty fast at it and could ship complex products in ways that really surprised people.
Problem was the maintenance over the months, years! After I built layers and layers of these generalized libraries and reused the hell out of them, each one wanted to serve a much greater purpose than what you asked me to do. Each layer wanted to solve the world's hunger needs. So each one was very ambitious: a math library that wants to be amazing and solve the world's hunger needs. Then something built on top of the math library like a geometry library that wants to be amazing and solve the world's hunger needs. You know something's wrong when you're trying to ship a product but your mind is mulling over how well your uber-generalized geometry library works for rendering and modeling when you're supposed to be working on animation because the animation code you're working on needs a few new geometry functions.
Balancing Everyone's Needs
I found in designing these uber-generalized libraries that I had to become obsessed with the needs of every single team member, and I had to learn how raytracing worked, how fluids dynamics worked, how the mesh engine worked, how inverse kinematics worked, how character animation worked, etc. etc. etc. I had to learn how to do pretty much everyone's job on the team because I was balancing all of their specific needs in the design of these uber generalized libraries I left behind while walking a tightrope balancing act of design compromises from all the code reuse (trying to make things better for Bob working on raytracing who is using one of the libraries but without hurting John too much who is working on physics who is also using it but without complicating the design of the library too much to make them both happy).
It got to a point where I was trying to parametrize bounding boxes with policy classes so that they could be stored either as center and half-size as one person wanted or min/max extents as someone else wanted, and the implementation was getting convoluted really fast trying to frantically keep up with everyone's needs.
Design By Committee
And because each layer was trying to serve such a wide range of needs (much wider than we actually needed), they found many reasons to require design changes, sometimes by committee-requested designs (which are usually kind of gross). And then those design changes would cascade upwards and affect all the higher-level code using it, and maintenance of such code started to become a real PITA.
I think you can potentially share more code in a like-minded team. Ours wasn't like-minded at all. These are not real names but I'd have Bill here who is a high-level GUI programmer and scripter who creates nice user-end designs but questionable code with lots of hacks, but it tends to be okay for that type of code. I got Bob here who is an old timer who has been programming since the punch card era who likes to write 10,000 line functions with gotos in them and still doesn't get the point of object-oriented programming. I got Joe here who is like a mathematical wizard but writes code no one else can understand and always make suggestions which are mathematically aligned but not necessarily so efficient from a computational standpoint. Then I got Mike here who is in outer space who wants us to port the software to iPhones and thinks we should all follow Apple's conventions and engineering standards.
Trying to satisfy everyone's needs here while coming up with a decent design was, probably in retrospect, impossible. And in everyone trying to share each other's code, I think we became counter-productive. Each person was competent in an area but trying to come up with designs and standards which everyone is happy with just lead to all kinds of instability and slowed everyone down.
Trade-Offs
So these days I've found the balance is to avoid code reuse for the lowest-level things. I use a top-down approach from the mid-level, perhaps (something not too far divorced from what you asked me to do), and build some independent library there which I can still do in a short amount of time, but the library doesn't intend to produce mini-libs that try to solve the world's hunger needs. Usually such libraries are a little more narrow in purpose than the lower-level ones (ex: a physics library as opposed to a generalized geometry-intersection library).
YMMV, but if there's anything I've learned over the years in the hardest ways possible, it's that there might be a balancing act and a point where we might want to deliberately avoid code reuse in a team setting at some granular level, abandoning some generality for the lowest-level code in favor of decoupling, having malleable code we can better shape to serve more specific rather than generalized needs, and so forth -- maybe even just letting everyone have a little more freedom to do things their own way. But of course all of this is with the aim of still producing a very reusable, generalized library, but the difference is that the library might not decompose into the teeniest generalized libraries, because I found that crossing a certain threshold and trying to make too many teeny, generalized libraries starts to actually become an extremely counter-productive endeavor in the long term -- not in the short term, but in the long run and broad scheme of things.
If you have a piece of code which could potentially be shared across a
medium size organization how would you go about informing other
members of the company that this lib/api/etc existed and could be of
benefit?
I actually am more reluctant these days and find it more forgivable if colleagues do some redundant work because I would want to make sure that code does something fairly useful and non-trivial and is also really well-tested and designed before I try to share it with people and accumulate a bunch of dependencies to it. The design should have very, very few reasons to require any changes from that point onwards if I share it with the rest of the team.
Otherwise it could cause more grief than it actually saves.
I used to be so intolerant of redundancy (in code or efforts) because it appeared to translate to a product that was very buggy and explosive in memory use. But I zoomed in too much on redundancy as the key problem, when really the real problem was poor quality, hastily-written code, and a lack of solid testing. Well-tested, reliable, efficient code wouldn't suffer that problem to nearly as great of a degree even if some people duplicate, say, some math functions here and there.
One of the common sense things to look at and remember that I didn't at the time is how we don't mind some redundancy when we use a very solid third party library. Chances are that you guys use a third party library or two that has some redundant work with what your team is doing. But we don't mind in those cases because the third party library is great and well-tested. I recommend applying that same mindset to your own internal code. The goal should be to create something awesome and well-tested, not to fuss over a little bit of redundancy here and there as I mistakenly did long ago.
So these days I've shifted my intolerance towards a lack of testing instead. Instead of getting upset over redundant efforts, I find it much more productive to get upset over other people's lack of unit and integration testing! :-D
While I think code reuse is valuable, I can see where this sentiment is rooted. I've worked on a lot of projects where much extra care was taken to create re-usable code that was then never reused. Of course reuse is much preferable to duplicate code, but I have seen a lot of very extenisve object models created with the goal of using the objects across the enterprise in multiple projects (kind of the way the same service in SOA can be used in different apps) but have never seen the objects actually used more than once. Maybe I just haven't been part of organizations taking good advantage of the principle of reuse.
The two software projects I've worked on have both been long term development. One is about 10 years old, the other has been around for over 30 years, rewritten in a couple versions of Fortran along the way. Both make extensive reuse of code, but both rely very little on external tools or code libraries. DRY is a big mantra on the newer project, which is in C++ and lends itself more easily to doing that in practice.
Maybe the better question is when do we NOT reuse code these days? We are either in a state on building using someone elses observed "best practices" or prediscovered "design patterns" or just actually building on legacy code, libraries, or copying.
It seems the degree to which code A is reused to make code B is often based around how much the ideas in code A taken to code B are abstracted into design patterns/idioms/books/fleeting thoughts/actual code/libraries. The hard part is in applying all those good ideas to your actual code.
Non-technical types get overzealous about the reuse thing. They don't understand why everything can't be copy-pasted. They don't understand why the greemelfarm needs a special adapter to communicate the same information that it used to to the old system to the new system, and that, unfortunately we can't change either due to a bazillion other reasons.
I think techies have been reusing from day 1 in the same way musicians have been reusing from day 1. Its an ongoing organic evolution and sythesis that will keep ongoing.
Code reuse is an extremely important issue - where code is not reused, projects take longer and are harder for new team members to get into.
However, writing reusable code takes longer.
Personally, I try to write all my code in a reusable way, this takes longer, but it results in the fact that most of my code has become official infrastructures in my organization and that new projects based on these infrastructures take significantly less time.
The danger in reusing code, is if the reused code is not written as an infrastructure - in a general and encapsulated manner with as few as possible assumptions and as much as possible documentation and unit testing, that the code can end up doing unexpected things.
Also, if bugs are found and fixed, or features added, these changes are rarely returned to the source code, resulting in different versions of the reused code, that no one knows of or understands.
The solution is:
1. To design and write the code with not only one project in mind, but to think of future requirements and try to make the design flexible enough to cover them with minimal code change.
2. To enclose the code within libraries that are to be used as-is and not modified within using projects.
3. To allow users to view and modify the code of of the library withing its solution (not within the using project's solution).
4. To design future projects to be based on the existing infrastructures, making changes to the infrastructures as necessary.
5. To charge maintaining the infrastructure to all projects, thus keeping the infrastructure funded.
Maven has solved code reuse. I'm completely serious.