Finish Them!: Pricing Algorithms for Human Computation

Given a batch of human computation tasks, a commonly ignored aspect is how the price (i.e., the reward paid to human workers) of these tasks must be set or varied in order to meet latency or cost constraints. Often, the price is set up-front and not modified, leading to either a much higher monetary cost than needed (if the price is set too high), or to a much larger latency than expected (if the price is set too low). Leveraging a pricing model from prior work, we develop algorithms to optimally set and then vary price over time in order to meet a (a) user-specified deadline while minimizing total monetary cost (b) user-specified monetary budget constraint while minimizing total elapsed time. We leverage techniques from decision theory (specifically, Markov Decision Processes) for both these problems, and demonstrate that our techniques lead to upto 30\% reduction in cost over schemes proposed in prior work. Furthermore, we develop techniques to speed-up the computation, enabling users to leverage the price setting algorithms on-the-fly

10381 Summary and Abstracts Collection -- Robust Query Processing

Dagstuhl seminar 10381 on robust query processing (held 19.09.10 - 24.09.10) brought together a diverse set of researchers and practitioners with a broad range of expertise for the purpose of fostering discussion and collaboration regarding causes, opportunities, and solutions for achieving robust query processing. The seminar strove to build a unified view across the loosely-coupled system components responsible for the various stages of database query processing. Participants were chosen for their experience with database query processing and, where possible, their prior work in academic research or in product development towards robustness in database query processing. In order to pave the way to motivate, measure, and protect future advances in robust query processing, seminar 10381 focused on developing tests for measuring the robustness of query processing. In these proceedings, we first review the seminar topics, goals, and results, then present abstracts or notes of some of the seminar break-out sessions. We also include, as an appendix, the robust query processing reading list that was collected and distributed to participants before the seminar began, as well as summaries of a few of those papers that were contributed by some participants

Minimizing database repros using language grammars

Database engines and database-centric applications have become complex software systems. Ensuring bug-free database services is therefore a very difficult task. Whenever possible, bugs that are uncovered during testing are associated with a repro, or se-quence of steps that deterministically reproduce the problem. Un-fortunately, due to factors such as automated test generation, re-pros are generally too long and complex. This issue prevents de-velopers reacting quickly to new bugs, since usually a long man-ual “repro-minimization ” phase occurs before the actual debugging takes place. In this paper we present a fully automated technique to minimize database repros that leverages underlying language grammars and thus is significantly more focused than previous ap-proaches. Our approach has been successfully used in two com-mercial database products to isolate and simplify bugs during early development stages. We show that our technique consistently re-sults in repros that are as concise or simpler and obtained much faster than alternative ones carefully constructed manually. 1