![]() ![]() Once you have narrowed your focus to particular areas of your code you start to get down to the method level. There’s nothing wrong in my opinion with gathering some basic data in this way, as long as the compromises in accuracy are understood. A benefit is that stopwatches are simple to use and can provide quick results. Be aware that many conditions could affect your measurements and their accuracy. Sometimes the use of a simple stopwatch will be a starting point to gather general timing data. NET, at the code level, there are a number of techniques which may work. NET Memory Management: For Better Code, Performance, and Scalability” by Konrad Kokosa.īaselining is the process of establishing current performance under typical conditions for your code. If you do want to learn more about profiling your code, I learned a lot from reading “ Pro. I may one day come back to these broader areas but for now, I’ll assume that you have some idea of the code paths you want to improve. Sometimes good guesses can be made but whenever possible it best to be scientific in your endeavours and back up theories with actual data. Also, they are vast topics of their own which I feel would distract from my focus on the language and framework features.įor real-world scenarios, you’ll likely need to use such techniques to first narrow down places the places where you should spend time optimising. I’ve decided to skip past these higher level techniques for now, partly because they are areas I’m not fully confident in, certainly to a level where I am able to provide good guidance on them. All of these may be necessary in order to target the services which should be optimised and at the code level, the classes and methods which should be your sights. In my experience, performance work is very much an iterative process or measuring, making small changes and measuring again to check the effect of the change.Īrguably, there are other places that I could have started in this series, perhaps with profiling, tracing or metrics gathering. ![]() This is critical in order for us to validate that our changes are having the impact we desire and most importantly, not making our performance worse. The reason that I’ve started with benchmarking is that before we can and should start optimising code, we should first understand our current position. In this post, I want to focus on benchmarking existing code and establishing baselines. In my previous post, I introduced this series in which I’ll share my experiences while learning about the new performance features in C# and the. ![]()
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