SUMMARYParallel programs present some features such as concurrency, communication and synchronization that make the test a challenging activity. Because of these characteristics, the direct application of traditional testing is not always possible and adequate testing criteria and tools are necessary. In this paper we investigate the challenges of validating message-passing parallel programs and present a set of specific testing criteria. We introduce a family of structural testing criteria based on a test model. The model captures control and data flow of the message-passing programs, by considering their sequential and parallel aspects. The criteria provide a coverage measure that can be used for evaluating the progress of the testing activity and also provide guidelines for the generation of test data. We also describe a tool, called ValiPar, which supports the application of the proposed testing criteria. Currently, ValiPar is configured for parallel virtual machine (PVM) and message-passing interface (MPI). Results of the application of the proposed criteria to MPI programs are also presented and analyzed.

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Multi-objective evolutionary algorithms (MOEAs) have been efficiently applied to Search-Based Software Engineering (SBSE) problems. However, skilled software engineers waste significant effort designing such algorithms for a particular problem, adapting them, selecting operators and configuring parameters. Hyper-heuristics can help in these tasks by dynamically selecting or creating heuristics. Despite of such advantages, we observe a lack of works regarding this subject in the SBSE field. Considering this fact, this work introduces HITO, a Hyper-heuristic for the Integration and Test Order Problem. It includes a set of well-defined steps and is based on two selection functions (Choice Function and Multi-armed Bandit) to select the best low-level heuristic (combination of mutation and crossover operators) in each mating. To perform the selection, a quality measure is proposed to assess the performance of low-level heuristics throughout the evolutionary process. HITO was implemented using NSGA-II and evaluated to solve the integration and test order problem in seven systems. The introduced hyper-heuristic obtained the best results for all systems, when compared to a traditional algorithm.

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