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The Grid promise is starting to materialize today: large- scale multi-site infrastructures have grown to assist the work of scientists from all around the world. This tremendous growth can be sustained and continued only through a higher quality of the middleware, in terms of deployability and of correct functionality. A potential solution to this problem is the adoption of industry practices regarding middleware building and testing. However, it is unclear what good build-and-test environments for grid middleware should look like, and how to use them efficiently. In this work we address both these problems. First, we study the characteristics of the NMI build-and-test environment, which handles millions of testing tasks annually, for major Grid middleware such as Condor, Globus, VDT, and gLite. Through the analysis of a system-wide trace covering the past two years we find the main characteristics of the workload, as well as the performance of the system under load. Second, we propose mechanisms for more efficient test management and operation, and for resource provisioning and evaluation. Notably, we propose a generic test optimization technique that reduces the test time by 95%, while achieving 93% of the maximum accuracy, under real conditions.