Category Archives: Software Development

Appearance on .NET Rocks! Podcast

Carl and Richard put together a great podcast. .NET Rocks! has existed for years now and it’s amazing how many episodes they’ve published.

A couple of weeks ago, I had the privilege of recording their latest episode with them, #1041. We talked about a ton of interesting things like the importance of memory management, precise measurement, using the correct tools, not being afraid of the debugger, a little bit about Microsoft culture, and even LEGO!

Here is their description:

Carl and Richard talk to Ben Watson about his work around writing high performance .NET code. Ben talks about how the Bing team decided to use .NET code internally, which seems like an obvious choice for a Microsoft group, but it isn’t really – when milliseconds count, does .NET makes sense? Ben says it does, and he’s done the work to prove it. Ben’s book “Writing High Performance .NET Code” focuses not only on coding techniques, but also the larger practice of having a deep understanding of how .NET works, and the processes that take place to turn .NET code into machine code. The conversation also digs deeply into the need for performance measurement, especially Event Tracing for Windows. .NET can be fast when you do it right!

Give a listen. Subscribe in iTunes or listen on the web. Let me know what you think!


Check out my latest book, the essential, in-depth guide to performance for all .NET developers:

Writing High-Performance.NET Code by Ben Watson. Available now in print and as an eBook at:

Digging Into .NET Object Allocation Fundamentals

[Note: this article also appeared on CodeProject]

Introduction

While understanding garbage collection fundamentals is vital to working with .NET, it is also important to understand how object allocation works. It shows you just how simple and performant it is, especially compared to the potentially blocking nature of native heap allocations. In a large, native, multi-threaded application, heap allocations can be major performance bottleneck which requires you to perform all sorts of custom heap management techniques. It’s also harder to measure when this is happening because many of those details are hidden behind the OS’s allocation APIs. More importantly, understanding this will give you clues to how you can mess up and make object allocation far less efficient.

In this article, I want to go through an example taken from Chapter 2 of Writing High-Performance .NET Code and then take it further with some additional examples that weren’t covered in the book.

Viewing Object Allocation in a Debugger

Let’s start with a simple object definition: completely empty.

class MyObject 
{
}

static void Main(string[] args)
{
    var x = new MyObject();
}

In order to examine what happens during allocation, we need to use a “real” debugger, like Windbg. Don’t be afraid of this. If you need a quick primer on how to get started, look at the free sample chapter on this page, which will get you up and running in no time. It’s not nearly as bad you think.

Build the above program in Release mode for x86 (you can do x64 if you’d like, but the samples below are x86).

In Windbg, follow these steps to start and debug the program:

  1. Ctrl+E to execute a program. Navigate to and open the built executable file.
  2. Run command: sxe ld clrjit (this tells the debugger to break on loading any assembly with clrjit in the name, which you need loaded before the next steps)
  3. Run command: g (continues execution)
  4. When it breaks, run command: .loadby sos clr (loads .NET debugging tools)
  5. Run command: !bpmd ObjectAllocationFundamentals Program.Main (Sets a breakpoint at the beginning of a method. The first argument is the name of the assembly. The second is the name of the method, including the class it is in.)
  6. Run command: g

Execution will break at the beginning of the Main method, right before new() is called. Open the Disassembly window to see the code.

Here is the Main method’s code, annotated for clarity:

; Copy method table pointer for the class into
; ecx as argument to new()
; You can use !dumpmt to examine this value.
mov ecx,006f3864h
; Call new
call 006e2100 
; Copy return value (address of object) into a register
mov edi,eax

Note that the actual addresses will be different each time you execute the program. Step over (F10, or toolbar) a few times until call 006e2100 (or your equivalent) is highlighted. Then Step Into that (F11). Now you will see the primary allocation mechanism in .NET. It’s extremely simple. Essentially, at the end of the current gen0 segment, there is a reserved bit of space which I will call the allocation buffer. If the allocation we’re attempting can fit in there, we can update a couple of values and return immediately without more complicated work.

If I were to outline this in pseudocode, it would look like this:

if (object fits in current allocation buffer)
{
   Increment a pointer, return address;
}
else
{
   call JIT_New to do more complicated work in CLR
}

The actual assembly looks like this:

; Set eax to value 0x0c, the size of the object to
; allocate, which comes from the method table
006e2100 8b4104          mov     eax,dword ptr [ecx+4] ds:002b:006f3868=0000000c
; Put allocation buffer information into edx
006e2103 648b15300e0000  mov     edx,dword ptr fs:[0E30h]
; edx+40 contains the address of the next available byte
; for allocation. Add that value to the desired size.
006e210a 034240          add     eax,dword ptr [edx+40h]
; Compare the intended allocation against the
; end of the allocation buffer.
006e210d 3b4244          cmp     eax,dword ptr [edx+44h]
; If we spill over the allocation buffer,
; jump to the slow path
006e2110 7709            ja      006e211b
; update the pointer to the next free
; byte (0x0c bytes past old value)
006e2112 894240          mov     dword ptr [edx+40h],eax
; Subtract the object size from the pointer to
; get to the start of the new obj
006e2115 2b4104          sub     eax,dword ptr [ecx+4]
; Put the method table pointer into the
; first 4 bytes of the object.
; eax now points to new object
006e2118 8908            mov     dword ptr [eax],ecx
; Return to caller
006e211a c3              ret
; Slow Path - call into CLR method
006e211b e914145f71      jmp     clr!JIT_New (71cd3534)

In the fast path, there are only 9 instructions, including the return. That’s incredibly efficient, especially compared to something like malloc. Yes, that complexity is traded for time at the end of object lifetime, but so far, this is looking pretty good!

What happens in the slow path? The short answer is a lot. The following could all happen:

  • A free slot somewhere in gen0 needs to be located
  • A gen0 GC is triggered
  • A full GC is triggered
  • A new memory segment needs to be allocated from the operating system and assigned to the GC heap
  • Objects with finalizers need extra bookkeeping
  • Possibly more…

Another thing to notice is the size of the object: 0x0c (12 decimal) bytes. As covered elsewhere, this is the minimum size for an object in a 32-bit process, even if there are no fields.

Now let’s do the same experiment with an object that has a single int field.

class MyObjectWithInt { int x; }

Follow the same steps as above to get into the allocation code.

The first line of the allocator on my run is:

00882100 8b4104          mov     eax,dword ptr [ecx+4] ds:002b:00893874=0000000c

The only interesting thing is that the size of the object (0x0c) is exactly the same as before. The new int field fit into the minimum size. You can see this by examining the object with the !DumpObject command (or the abbreviated version: !do). To get the address of the object after it has been allocated, step over instructions until you get to the ret instruction. The address of the object is now in the eax register, so open up the Registers view and see the value. On my computer, it has a value of 2372770. Now execute the command: !do 2372770

You should see similar output to this:

0:000> !do 2372770
Name:        ConsoleApplication1.MyObjectWithInt
MethodTable: 00893870
EEClass:     008913dc
Size:        12(0xc) bytes
File:        D:\Ben\My Documents\Visual Studio 2013\Projects\ConsoleApplication1\ConsoleApplication1\bin\Release\ConsoleApplication1.exe
Fields:
      MT    Field   Offset                 Type VT     Attr    Value Name
70f63b04  4000001        4         System.Int32  1 instance        0 x

This is curious. The field is at offset 4 (and an int has a length of 4), so that only accounts for 8 bytes (range 0-7). Offset 0 (i.e., the object’s address) contains the method table pointer, so where are the other 4 bytes? This is the sync block and they are actually at offset -4 bytes, before the object’s address. These are the 12 bytes.

Try it with a long.

class MyObjectWithLong { long x; }

The first line of the allocator is now:

00f22100 8b4104          mov     eax,dword ptr [ecx+4] ds:002b:00f33874=00000010

Showing a size of 0x10 (decimal 16 bytes), which we would expect now. 12 byte minimum object size, but 4 already in the overhead, so an extra 4 bytes for the 8 byte long. And an examination of the allocated object shows an object size of 16 bytes as well.

0:000> !do 2932770
Name:        ConsoleApplication1.MyObjectWithLong
MethodTable: 00f33870
EEClass:     00f313dc
Size:        16(0x10) bytes
File:        D:\Ben\My Documents\Visual Studio 2013\Projects\ConsoleApplication1\ConsoleApplication1\bin\Release\ConsoleApplication1.exe
Fields:
      MT    Field   Offset                 Type VT     Attr    Value Name
70f5b524  4000002        4         System.Int64  1 instance 0 x

If you put an object reference into the test class, you’ll see the same thing as you did with the int.

Finalizers

Now let’s make it more interesting. What happens if the object has a finalizer? You may have heard that objects with finalizers have more overhead during GC. This is true–they will survive longer, require more CPU cycles, and generally cause things to be less efficient. But do finalizers also affect object allocation?

Recall that our Main method above looked like this:

mov ecx,006f3864h
call 006e2100 
mov edi,eax

If the object has a finalizer, however, it looks like this:

mov     ecx,119386Ch
call    clr!JIT_New (71cd3534)
mov     esi,eax

We’ve lost our nifty allocation helper! We have to now jump directly to JIT_New. Allocating an object that has a finalizer is a LOT slower than a normal object. More internal CLR structures need to be modified to track this object’s lifetime. The cost isn’t just at the end of object lifetime.

How much slower is it? In my own testing, it appears to be about 8-10x worse than the fast path of allocating a normal object. If you allocate a lot of objects, this difference is considerable. For this, and other reasons, just don’t add a finalizer unless it really is required.

Calling the Constructor

If you are particularly eagle-eyed, you may have noticed that there was no call to a constructor to initialize the object once allocated. The allocator is changing some pointers, returning you an object, and there is no further function call on that object. This is because memory that belongs to a class field is always pre-initialized to 0 for you and these objects had no further initialization requirements. Let’s see what happens if we change to the following definition:

class MyObjectWithInt { int x = 13; }

Now the Main function looks like this:

mov     ecx,0A43834h
; Allocate memory
call    00a32100
; Copy object address to esi
mov     esi,eax
; Set object + 4 to value 0x0D (13 decimal)
mov     dword ptr [esi+4],0Dh

The field initialization was inlined into the caller!

Note that this code is exactly equivalent:

class MyObjectWithInt { int x; public MyObjectWithInt() { this.x = 13; } }

But what if we do this?

class MyObjectWithInt 
{ 
    int x; 

    [MethodImpl(MethodImplOptions.NoInlining)]  
    public MyObjectWithInt() 
    { 
        this.x = 13; 
    } 
}

This explicitly disables inlining for the object constructor. There are other ways of preventing inlining, but this is the most direct.

Now we can see the call to the constructor happening after the memory allocation:

mov     ecx,0F43834h
call    00f32100
mov     esi,eax
mov     ecx,esi
call    dword ptr ds:[0F43854h]

Exercise for the Reader

Can you get the allocator shown above to jump to the slow path? How big does the allocation request have to be to trigger this? (Hint: Try allocating arrays of various sizes.) Can you figure this out by examining the registers and other values from the running code?

Summary

You can see that in most cases, allocation of objects in .NET is extremely fast and efficient, requiring no calls into the CLR and no complicated algorithms in the simple case. Avoid finalizers unless absolutely needed. Not only are they less efficient during cleanup in a garbage collection, but they are slower to allocate as well.

Play around with the sample code in the debugger to get a feel for this yourself. If you wish to learn more about .NET memory handling, especially garbage collection, take a look at the book Writing High-Performance .NET Code.


Check out my latest book, the essential, in-depth guide to performance for all .NET developers:

Writing High-Performance.NET Code by Ben Watson. Available now in print and as an eBook at:

5 More Attributes of Highly Effective Programmers

Nearly 7 years ago, I wrote a little article called The Top 5 Attributes of Highly Effective Programmers that got some good feedback and has proven popular over time.

One matures as a developer, of course. I wrote that last article quite closer to the beginning of my career. Over the last few years, especially at Microsoft, I’ve had the opportunity to witness a much wider range of behaviors. I’ve been able to develop a much better sense of what differentiates the novice from the truly effective developer.

The difference in skills can be truly staggering if you’re not used to seeing it. A new programmer, or one who has not learned much from experience, can often be an order of magnitude or more less productive than a good, experienced developer. You don’t want to spend very long at the bottom of this kind of ranking. Some of this is just experience, but in many cases it’s just a mindset–there are plenty of “experienced” developers who haven’t actually learned to improve. It’s true in many professions, but especially so in programming–you can’t plateau. You have to keep learning. The world changes, programming changes, and what was true 10 years ago is laughably outdated.

The attributes I listed in the previous article are still applicable. They are still valuable, but there is more. Note that I am not claiming in this article that I’ve mastered these. I still aspire to meet higher standards in each of these areas. Remember that it is not hypocrisy to espouse good ideas, even while struggling to live up to them. These are standards to live up to, not descriptions of any one person I know (though I do know plenty of people who are solid in at least one of these areas).

Sense of Ownership

Ownership means a lot of things, but mainly that you don’t wait for problems to find you. It means that if you see a problem, you assume it’s your job to either fix it or find someone else who can, and then to make sure it happens. It means not ignoring emails because, hey, not my problem! It means taking issues seriously and making sure they are dealt with. Someone with a sense of ownership would never sweep a problem under the rug or blithely hope that someone else will deal with it.

You could equate ownership with responsibility, but I think it goes beyond that. “Responsibility” often takes on the hue of a burden or delegation of an unwelcome task, while “ownership” implies that you are invested in the outcome.

Ownership often means stepping outside of your comfort zone. You may think you’re not the best person to deal with something, but if no one else is doing it, than you absolutely are. Just step up, own the problem, and get it done.

Ownership does not mean that you do all the work–that would be draining, debilitating, and ultimately impossible. It does not mean that you specify bounds for your responsibility and forbid others to encroach. It especially does not mean code ownership in the sense that only you are allowed to change your code.

Ownership is a mentality that defies strict hierarchies of control in favor of a more egalitarian opportunism.

Closely related to the idea of ownership is taking responsibility for your mistakes. This means you don’t try to excuse yourself, shift blame, or minimize the issue unnecessarily. If there’s a problem you caused, be straight about it, explain what happened, what you’re going to do to prevent it, and move on.

Together, these ideas on ownership will gain you a reputation as someone who wants the best for the team or product. You want to be that person.

Remember, if you are ever having the thought, Someone ought to…–stop! That someone is you.

Data-Driven

A good developer does not make assumptions. Experience is good, yes, but data is better. Far, far better. Knowing how to measure things is far more important than being able to change them. If you make changes without measuring, then you’re just a random-coding monkey, just guessing that you’re doing something useful. Especially when it comes to performance, building a system to automatically measure performance is actually more important than the actual changes to performance. This is because if you don’t have that system, you will spend far more time doing manual measurement than actual development. See the section on Automation below.

Measurement can be simple. For some bugs, the measurement is merely, does the bug repro or not? For performance tuning of data center server applications, it will likely be orders of magnitude more complicated and involve systems dedicated to measurement.

Determining the right amount of data to make a decision is not always easy. You do have to balance this with expediency, and you don’t want to hold good ideas hostage to more measurement than necessary. However, there is very little you should that do completely blind with no data at all. As a developer, your every action should be independently justifiable.

The mantra of performance optimization is Measure, Measure, Measure. This should be the mantra of all software development. Are things improving or not? Faster or not? How much? Are customers happier or not? Can tasks be completed easier? Are we saving more money? Does it use less memory? Is our capacity larger? Is the UI more responsive? How much, exactly?

The degree to which you measure the answer to those questions is in large part dependent on how important it is to your bottom line.

My day job involves working on an application that runs on thousands of servers, powering a large part of Bing. With something like this, even seemingly small decisions can have a drastic effect in the end. If I make something a bit more inefficient, it could translate into us needing to buy more machines. Great, now my little coding change that I didn’t adequately measure is costing the company hundreds of thousands of extra dollars per year. Oops.

Even for smaller applications, this can be a big deal. For example, making a change that causes the UI to be 20% more sluggish in some cases may not be noticed if you don’t have adequate measurement in place, but if it leads to a bad review by someone who noticed it, and there are adequate competitors, that one decision could be a major loss of revenue.

Solid Tests

Notice that I don’t say “tests”, unqualified. Good tests, solid, repeatable tests. Those are the only ones worth having.

If you see a code change that doesn’t have accompanying test changes, don’t be afraid to ask the question, “Where are the tests?” The answer might be that existing tests cover the change, or that tests at a larger scope, or in a different change will cover it, but the point is to ask the question, and make sure there is a satisfactory answer. “Manual test” is a valid response sometimes, but this should be very rare, and justifiable.

I cannot say how many times I’ve been saved due to the hundreds of unit tests that exercise my code, especially when I’m attempting a big internal refactor, usually for performance reasons.

As important as good tests are, it’s also important to get rid of bad tests. Don’t waste resources on things that aren’t helpful. Insist on a clean, reliable test suite. I’m not sure which is worse: no tests, or tests you can’t rely on. Eventually, unreliable tests become the same as having no tests at all.

Automation

An effective developer is always trying to put themselves out of a job. Seriously. There is more work than you can possibly fit in the time allotted. Automate the heck out of the stuff that annoys you, trips you up, is repetitive, is frequent, is error-prone. Once you can break down a process into something so deterministic that you could write a script for someone else to follow and get the same result, then make sure that someone else is a program.

This is more than just simple maintenance scripts for server management. This is ANY part of your job. Collecting data? Get it automatically ingested into the systems that need it. Generating reports? If you’ve generated the same report more than twice, don’t do it a third time. Your build system requires more than a single step? What’s wrong with you?

You have to free yourself up for more interesting, more creative work. You’re a highly paid programmer. Act like it.

Example: One of my jobs in the last year has been to run regular performance profiling, analyze the results, and send them to my team, making suggestions for future focus. This involved a bunch of steps:

  1. Log onto a random machine in the datacenter.
  2. Start a 120-second CPU profile.
  3. Wait for 120-seconds plus a few minutes for processing, symbol resolution, etc.
  4. Compress file, copy to my machine
  5. Analyze file–group, filter, and sort data according to various rules.
    1. Look for a bunch of standard things that I always report on
  6. Do the same thing for a 900-second memory/exception/thread/etc. profile.

This took about an hour each time, sometimes more.

I realized that every single part of this could happen automatically. I a wrote a service that gets deployed to every datacenter machine. A couple of times per day it checks to see whether we need a profile, whether the machine is in a good state to profile, etc.. It then runs the profiler, collects the data, and even analyzes the data automatically (See Chapter 8 of Writing High-Performance .NET Code for a hint about how I did this). This all gets uploaded to a file server and the analysis gets displayed on a web-site. No intervention whatsoever. Not only do I not have to do this work myself anymore, but others are empowered to look at the data for themselves, and we can easily add more analysis components over time.

Unafraid of Communication

The final thing I want to talk about is communication. This has been a challenge for me. I definitely have the personality type that really likes to disappear into a cave and pound on a keyboard for a few days, to emerge at the end with some magical piece of code. I would delete Outlook from my computer if I could.

This kind of attitude might serve you well for a while, but it’s ultimately limiting.

As you get more senior, communication becomes key. Effective communication skills are one of the things you can use to distinguish yourself to advance your career.

Effective communication can begin with a simple acknowledgement of someone’s issue, or an explanation that you’re working on something, with a follow-up to everyone involved at regular points. Nobody likes to be kept in the dark, especially for burning issues. For time-critical issues, a “next update in XX hours” can be vital.

Effective communication also means being able to say what you’re working on and why it’s cool.

Eventually, it means a lot more–being able to present complicated ideas to many other people in a simple, understandable, logical way.

Good communication skills enable you to be able to move beyond implementing software all by yourself to helping teams as a whole do better software. You can have a much wider impact by helping and teaching others. This is good for your team, your company, and your career.

Do you have a good engineering culture?

I assume one big prerequisite to all of these attributes: You must have a solid engineering environment to operate in. If management gives short shrift to employee happiness, sound software engineering principles, or the workplace is otherwise toxic, than perhaps you need to focus on changing that first.

If your leaders are so short-sighted that they can’t stand the thought of you automating your work instead of just getting the job done, that’s a problem.

If bringing up problems or admitting fault to a mistake is a career-limiting move, then you need to get out soon. That’s a team that will eventually implode under the weight of cumulative failure that no one wants to address.

Don’t settle for this kind of workplace. Either work to change it or find some place better.

 


Check out my latest book, the essential, in-depth guide to performance for all .NET developers:

Writing High-Performance.NET Code by Ben Watson. Available now in print and as an eBook at:

Article about Class Design and General .NET Coding

I modified Chapter 5 from Writing High-Performance .NET Code and posted it as an article at CodeProject. Take a look and tell me what you think!


Check out my latest book, the essential, in-depth guide to performance for all .NET developers:

Writing High-Performance.NET Code by Ben Watson. Available now in print and as an eBook at:

Announcing Writing High-Performance .NET Code

This blog has been silent for far too long. That’s because I’ve been heads-down on a side project for the last 10 months. I’d like to announce my latest technical book:

Writing High-Performance .NET Code

Cover-Tall-2000x2828

If you write managed code, you want this book. If you have friends who write managed code, they want this, even if they don’t know it yet.

Do you want your .NET code to have the absolute best performance it can? This book demystifies the CLR, teaching you how and why to write code with optimum performance. Learn critical lessons from a person who helped design and build one of the largest high-performance .NET systems in the world.

This book does not just teach you how the CLR works—it teaches you exactly what you need to do now to obtain the best performance today. It will expertly guide you through the nuts and bolts of extreme performance optimization in .NET, complete with in-depth examinations of CLR functionality, free tool recommendations and tutorials, useful anecdotes, and step-by-step guides to measure and improve performance.

Among the topics you will learn are how to:

  • Choose what to measure and why
  • Use many amazing tools, freely available, to solve problems quickly
  • Understand the .NET garbage collector and its effect on your application
  • Use effective coding patterns that lead to optimal garbage collection performance
  • Diagnose common GC-related issues
  • Reduce costs of JITting
  • Use multiple threads sanely and effectively, avoiding synchronization problems
  • Know which .NET features and APIs to use and which to avoid
  • Use code generation to avoid performance problems
  • Measure everything and expose hidden performance issues
  • Instrument your program with performance counters and ETW events
  • Use the latest and greatest .NET features
  • Ensure your code can run on mobile devices without problems
  • Build a performance-minded team

…and much more.

See http://www.writinghighperf.net for up-to-date information about the book. You can also like the Facebook page or subscribe to this blog to see updates.

The book is currently available via Amazon and Kobo. Barnes and Noble is pending. More retailers and formats will follow. See the Buy page to check for current availability.

I will also be posting some blog entries with topics inspired by the book, but weren’t quite a good fit.


Check out my latest book, the essential, in-depth guide to performance for all .NET developers:

Writing High-Performance.NET Code by Ben Watson. Available now in print and as an eBook at:

Keep API Usage Simple

One lesson that I’m appreciating more every week is that old acronym, K.I.S.S. – Keep It Simple, Stupid. Simple code is best. The highest cost of most software is maintenance—and you don’t want maintenance to include a lot of “how the heck does this work?”

This simplicity does not apply to just your own code. Most API frameworks provide multiple ways of doing things, but if you don’t need it, don’t use it.

For example, I’ve been working a lot with the Task Parallel Library, and it’s great – it really is an awesome way of doing asynchronous programming. However, when you get to continuations, there are so many options, it can quickly make your code a bewildering mix of usage patterns, if you’re not careful.

You can have continuations called only when the task fails, or is canceled, or only when it succeeds, or only when it does not succeed. You can chain continuations, cancel them, and there are all sorts of scheduling options, and much more.

This API is powerful, and I’m grateful it’s all there, but when you need to have a large team work on a single code base, it’s helpful necessary to enforce some simplifying constraints. One thing we’ve done, specifically with the Task Parallel Library, is to require everyone to use just one of the many possible patterns. This way, no matter what part of the code we’re looking at, we can understand exactly how Tasks work. It takes the guesswork out, and reduces maintenance costs. This kind of thing is especially critical for complex areas of the code – i.e., asynchronous programming.

Takeaway: you don’t have to use every possible API feature or pattern—just pick one and enforce consistency and simplicity.


Check out my latest book, the essential, in-depth guide to performance for all .NET developers:

Writing High-Performance.NET Code by Ben Watson. Available now in print and as an eBook at:

Activator.CreateInstance: Slow vs. Less-Slow

In the system I’m working on, there is a lot of runtime type resolution, e.g., lines like this:

var obj = Activator.CreateInstance(type, param1, param2, param3)

The params are arguments to the constructor of the type. The type itself is ultimately given through some configuration or otherwise-dynamic means.

Since we do a lot of this (many times per second), we’d like to ensure that instance creation is as fast as it can be. The method given above is not fast.

When this overload of CreateInstance is called, .Net has to do a lot of work to make sure it works: find the right constructor, verify that all the argument types match up, etc. This can be painfully slow, especially when, in a closed system, you can do a lot of offline validation to ensure that types are correctly specified.

Fortunately, Activator has another overload that is quite a bit faster, if you can use it.

Activator.CreateInstance(type)

This will call the default constructor of the type. However, we still have the problem of passing in those arguments. There are a few ways we could do this, but one of the simplest is to ensure that all the types you’re doing this for implement a common initialization interface, as in this sample program:

interface IPerson
{
    void Initialize(string name, DateTime dob, int weight);
}

class Employee : IPerson
{
    public Employee()
    {
    }

    public Employee(string name, DateTime dob, int weight)
    {
        Initialize(name, dob, weight);
    }

    public Employee(string name, DateTime dob)
        : this(name, dob, -1)
    {
    }

    public void Initialize(string name, DateTime dob, int weight)
    {
        this.name = name;
        this.dob = dob;
        this.weight = weight;
    }

    private string name;
    private DateTime dob;
    private int weight;
}

class Program
{
    static void Main(string[] args)
    {
        const int iterations = 1000000;

        Console.WriteLine("Timing Activator.CreateInstance(type, params)...");
        var employees = new IPerson[iterations];

        var stopwatch = Stopwatch.StartNew();

        for (int i = 0; i < iterations; ++i)
        {
            employees[i] = Activator.CreateInstance(typeof(Employee), 
                "Bob", DateTime.Now, 220) as IPerson;
        }

        stopwatch.Stop();

        Console.WriteLine("Total time: {0} for {1:N0} employees", 
            stopwatch.Elapsed.ToString(), iterations);
        Console.WriteLine();

        Console.WriteLine("Timing Activator.CreateInstance(type) + Initialization...");
        
        var employees2 = new IPerson[iterations];

        var stopwatch2 = Stopwatch.StartNew();            

        for (int i = 0; i < iterations; ++i)
        {
            employees2[i] = Activator.CreateInstance(typeof(Employee)) as IPerson;
            employees2[i].Initialize("Bob", DateTime.Now, 220);
        }

        stopwatch2.Stop();

        Console.WriteLine("Total time: {0} for {1:N0} employees", 
            stopwatch2.Elapsed.ToString(), iterations);
    }
}

What do you think the time difference in the two approaches is?

Timing Activator.CreateInstance(type, params)…

Total time: 00:00:05.4765664 for 1,000,000 employees

Timing Activator.CreateInstance(type) + Initialization…

Total time: 00:00:01.6007687 for 1,000,000 employees

About 3.5x faster. Pretty good. In practice, the improvement will vary. In some of our own timing experiments, we actually saw a much better speedup.

Like this tip? Check out my book, C # 4.0 How-To, where you’ll finds hundreds of great tips like this one.


Check out my latest book, the essential, in-depth guide to performance for all .NET developers:

Writing High-Performance.NET Code by Ben Watson. Available now in print and as an eBook at:

Another C# 4.0 How-To Book Give-away

In celebration of the beginning of the school year here in the USA, I’m going to give away a few more copies of my book C# 4.0 How-To .

If you’ve ever wanted a step-by-step guide with practicable code examples for hundreds of tasks in C#, .Net, and Windows, then this is the book for you. So far, I’m very pleased with the reviews its gotten (if you already have the book and haven’t left a review, why not? Smile)

Just leave a comment on this post, and I’ll choose two people at random. You must be in the US or Canada.

Also, for twitter users, if you retweet a link to this post using the hashtag #cs4howto, I’ll include you in the drawing as well.

The more comments and #cs4howto re-tweets there are, the more books I’ll give away!


Check out my latest book, the essential, in-depth guide to performance for all .NET developers:

Writing High-Performance.NET Code by Ben Watson. Available now in print and as an eBook at:

Measure Amount of Data to Serialize with a Null Stream

If you’ve got to serialize some data, especially in a binary format, it’s common to output the length of the data. This is useful for versioning, random access, knowing when you’re done reading the records, among other reasons.

Therefore, you need to know the size of the data you’re going to serialize. There are a few ways to do this:

  1. Measure the position you’re at, write the data, measure the new position, subtract, and that’s your length.
  2. If you want to write the length first (which is usually better), you can write a dummy value, such as 0, then writing the data, then backing up in the stream, and writing the real value.
  3. If you can’t back up the stream (very possible in some situations, or undesirable in others), you can measure the amount of data before you write. However, now you have to maintain that code in addition to the actual serialization.
  4. My solution presented here, avoids having to maintain separate code by writing the data to a null stream which does not write any data, but keeps track of how much data was “written.”
class NullStream : System.IO.Stream
{
    public override bool CanRead { get { return false; } }
 
    public override bool CanSeek { get { return false; } }
 
    public override bool CanWrite {get { return true; } }
 
    public override void Flush() { /*do nothing*/ }
 
    public override long Length { get { return Position; } }
 
    private long _position = 0;
    public override long Position 
    { 
        get 
        {
            return _position;
        }
        set
        {
            _position = value;
        }
    }
 
    public override int Read(byte[] buffer, int offset, int count)
    {
        throw new InvalidOperationException();
    }
 
    public override void Write(byte[] buffer, int offset, int count)
    {
        Position += count;
    }
 
    public override long Seek(long offset, System.IO.SeekOrigin origin)
    {
        throw new InvalidOperationException();
    }
 
    public override void SetLength(long value)
    {
        throw new InvalidOperationException();
    }
}

You can use it like this:

long GetDataSize()
{
    using (NullStream stream = new NullStream())
    {
        if (SaveData(stream))
        {
            return stream.Position;
        }
    }
    return 0;
}

There is a downside to something like this: you’re still essentially doing a lot of the work of serialization. Sure, you’re not writing out the bytes anywhere, but if, say, you need to encode a string as bytes before writing to the stream, that’s still going to happen.

Still, this technique made sense in my case, maybe it will work for you.


Check out my latest book, the essential, in-depth guide to performance for all .NET developers:

Writing High-Performance.NET Code by Ben Watson. Available now in print and as an eBook at:

Get a Free, Autographed Copy of C# 4.0 How-To!

To celebrate how well C# 4.0 How-To is doing, I’m going to give away two free copies of the book!

Here’s how it’s going to work:

1. Leave a comment on this post describing a project you’d like to build with C# 4.

2. I’ll pick two people from those comments at random.

(Make sure you enter your e-mail address where asked—it won’t be published to the blog, but I need it to contact you.)

I’ll leave the comments open for a while and I’ll update this post with the closing date.

Feel free to share a link to this blog post, tweet it, etc. If I get a lot of responses I may give away more.

Thanks to all those have already bought it!

UPDATE 18 May: I am going to close comments on Saturday morning (22 May) and pick the winners then. Thanks for commenting!

UPDATE 22 May: Comments are closed.


Check out my latest book, the essential, in-depth guide to performance for all .NET developers:

Writing High-Performance.NET Code by Ben Watson. Available now in print and as an eBook at: