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The need for performance metrics and comparison

Since we released AW 1.0, and more generally for every release of any AOP / interceptor framework (AspectJ, JBoss AOP, Spring AOP, cglib etc), a question is always raised: "what is the performance cost of such an approach ?", "how much do I loose per method invocation when an advice / interceptor is applied ?".

This is indeed an issue that needs to be carefully addressed, and that in fact has affected the design of every mature enough framework.

We are probably all scared by the cost of the java.lang.reflect despite its relative power, and usually, even before starting to evaluate semantics robustness and ease of use in general - we start doing some hello world bench.

We have started AWbench for that purpose. Offering a single place to measure the relative performance of AOP / interceptor framework, and even measure it by your own.

More than providing performance comparison, AWbench is a good place to figure out the semantics differences and ease of use of each framework. A simple "line of count" metrics could be provided as well (source + external file like xml + Ant glue).

Introducing AWbench


AWbench is a micro benchmark suite, which aims at staying simple. The test application is very simple, and AWbench is mainly the glue around the test application that applies one or more very simple advice / interceptor of the framework of your choice.

AWbench comes with an Ant script that allows you to run it on you own box, and provide some improvement if you know some for a particular framework.

What (what are the AOP constructs benched)

So far, AWbench includes method execution pointcuts, since call side pointcuts are not supported by proxy based framework (Spring AOP, Cglib, dynAOP etc).

The awbench.method.Execution class is the test application, and contains one method per construct to bench. An important fact is that bytecode based AOP may provide much better performance for before advice and after advice, as well as much better performance when it comes to accessing contextual information.
Indeed, proxy based frameworks are very likely to use reflection to give the user access to intercepted method parameters at runtime from within an advice, while bytecode based AOP may use more advanced constructs to provide access at the speed of a statically compiled access.

The current scope is thus:

For method execution pointcut


Contextual information access





before advice



before advice

static information (method signature etc)


before advice

contextual information accessed reflectively

Likely to use of casting and unboxing of primitives

before advice

contextual information accessed with explicit framework capabilities

Only supported by AspectJ and AspectWerkz 2.x




after advice



after returning advice

return value


after throwing advice

exception instance





before + after advice






around advice


AspectJ and AspetWerkz 2.x provides specific optimizations (thisJoinPointStaticPart vs thisJoinPoint)

around advice

non optimizezd





2 around advice

contextual information


By accessing contextual information we means:

  • accessing a method parameter using its real type (i.e. boxing and unboxing might be needed)
  • accessing a the advised instance using its real type (i.e. casting might be needed)

A pseudo code block is thus likely to be:

Which AOP and Proxy frameworks are benched?

The following are included in AWbench:

Bytecode based frameworks

Proxy based frameworks



Spring AOP (1.1.1)

Cglib proxy (2.0.2)

Moreover, AWbench includes AspectWerkz extensible AOP container that allow to run any Aspect / Interceptor framework within the AspectWerkz 2.x runtime:

AspectWerkz extensible AOP container running




AOP Alliance

Spring AOP


AWbench is extensible. Refer to Contributing to add a framework.

How (general rules)

Full blown AOP




Proxy based AOP, interceptor frameworks

Spring AOP

Cglib proxy

AspectWerkz extensible AOP container

Spring AOP within the AspectWerkz extensible AOP container

What's next ?

Running awbench by your own


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