The increasing complexity of available infrastructures with specific features (caches, hyperthreading, dual core, etc.) or with complex architectures (hierarchical, parallel, distributed, etc.) makes models either extremely difficult to build or intractable. Hence, it raises the question: how to validate algorithms if a realistic analytic analysis is not possible any longer? As for some other sciences (physics, chemistry, biology, etc.), the answer partly falls in experimental validation. Nevertheless, experiment in computer science is a difficult subject that opens many questions: what an experiment is able to validate? What is a "good experiments"? How to build an experimental environment that allows for "good experiments"? etc. In this paper we will provide some hints on this subject and show how some tools can help in performing "good experiments". More precisely we will focus on three main experimental methodologies, namely real-scale experiments (with an emphasis on PlanetLab and Grid'5000), Emulation (with an emphasis on Wrekavoc: http://wrekavoc.gforge.inria.fr) and simulation (with an emphasis on SimGRID and Grid-Sim). We will provide a comparison of these tools and methodologies from a quantitative but also qualitative point of view.