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This paper explores the main elements that influence innovation and the relationships among them. It is pointed out that innovation results from an entrepreneurial action inside an established institutional context, sustained by resources, abilities and competences and with the support of the necessary financial capital. Therefore, it is proposed that innovation is a function (just as the microeconomic production function) composed of entrepreneurship, institutions, capabilities and capital. Each one of these elements is explored individually and the relationships among them are analyzed. It is still suggested that the size of the firm is a moderator in the relationship between these elements and innovation. The study's contribution is the development of a conceptual model. Phone: +55 51 3308 3728 / Fax: +55 51 3308 3991. amsantos@ea.ufrgs.br (5) PPGA/UNB. ICC Norte Módulo 25 sub-solo. Campus Universitário Darcy Ribeiro/UNB.

Mutation testing is a program-transformation technique that injects artificial bugs to check whether the existing test suite can detect them. However, the costs of using mutation testing are usually high, hindering its use in industry. Useless mutants (equivalent and duplicated) contribute to increase costs. Previous research has focused mainly on detecting useless mutants only after they are generated and compiled. In this paper, we introduce a strategy to help developers with deriving rules to avoid the generation of useless mutants. To use our strategy, we pass as input a set of programs. For each program, we also need a passing test suite and a set of mutants. As output, our strategy yields a set of useless mutants candidates. After manually confirming that the mutants classified by our strategy as "useless" are indeed useless, we derive rules that can avoid their generation and thus decrease costs. To the best of our knowledge, we introduce 37 new rules that can avoid useless mutants right before their generation. We then implement a subset of these rules in the MUJAVA mutation testing tool. Since our rules have been derived based on artificial and small Java programs, we take our MUJAVA version embedded with our rules and execute it in industrial-scale projects. Our rules reduced the number of mutants by almost 13% on average. Our results are promising because (i) we avoid useless mutants generation; (ii) our strategy can help with identifying more rules in case we set it to use more complex Java programs; and (iii) our MUJAVA version has only a subset of the rules we derived.

Current GPU computational power enables the execution of complex and parallel algorithms, such as ray tracing techniques supported by kD-trees for 3D scene rendering in real time. This work describes in detail the study and implementation of eight different kD-tree traversal algorithms using the parallel framework NVIDIA Compute Unified Device Architecture, in order to point their pros and cons regarding performance, memory consumption, branch divergencies and scalability on multiple GPUs. In addition, two new algorithms are proposed by the authors based on this analysis, aiming to performance improvement. Both of them are capable of reaching speedup gains up to 3× when compared to recent and optimized parallel traversal implementations. As a consequence, interactive frame rates are possible for scenes with 1,408 × 768 pixels of resolution and 3.6 million primitives.