Microsoft StreamInsight (StreamInsight, for brevity) is a platform for developing and deploying streaming applications. StreamInsight adopts a deterministic stream model that leverages a temporal algebra as the underlying basis for processing long-running continuous queries. In most streaming applications, continuous query processing demands the ability to cope with high input rates that are characterized by imperfections in event delivery (i.e., incomplete or out-of-order data). StreamInsight is architected to handle imperfections in event delivery, to generate real-time low-latency output, and to provide correctness guarantees on the resultant output.

On one hand, streaming operators are similar to their well-understood relational counterparts – with a precise algebra as the basis of their behavior. On the other hand, streaming operators are unique in their non-blocking nature, which guarantees low-latency and incremental result delivery. While our deterministic temporal algebra paves the way towards easier testing of the streaming system, one unique challenge is that as the field evolves with more customers adopting streaming solutions, the semantics, behavior, and variety of operators is constantly under churn. This paper overviews the test framework for the StreamInsight query processor and highlights the challenges in verifying the functional correctness of its operators. The paper discusses the extensibility and the reusability of the proposed streaming test infrastructure, as the research and industrial communities address new and constantly evolving challenges in stream query processing.