Towards Dependability Testing of MapReduce Systems

MapReduce systems have been widely used by several applications, from search tools to financial and commercial systems. There is considerable enthusiasm around these systems due to their simplicity and scalability. However, there is a lack of a testing approach, and a framework to ensure they are dependable. The goal of this PhD is to propose a complete dependability testing solution for MapReduce systems. This solution is a model-based approach for generating representative fault cases, and a testing framework to control their execution automatically. Initial experiments demonstrate promising results with HadoopTest framework coordinating fault cases across distributed MapReduce components and identifying faulty systems.