A compiler's optimizer operates over abstract syntax trees (ASTs), continuously applying rewrite rules to replace subtrees of the AST with more efficient ones. Especially on large source repositories, even simply finding opportunities for a rewrite can be expensive, as optimizer traverses the AST naively. In this paper, we leverage the need to repeatedly find rewrites, and explore options for making the search faster through indexing and incremental view maintenance (IVM). Concretely, we consider bolt-on approaches that make use of embedded IVM systems like DBToaster, as well as two new approaches: Label-indexing and TreeToaster, an AST-specialized form of IVM. We integrate these approaches into an existing just-in-time data structure compiler and show experimentally that TreeToaster can significantly improve performance with minimal memory overheads.

Searching for parking spots generates frustration and pollution. To address these parking problems, we present PocketParker, a crowdsourcing system using smartphones to predict parking lot availability. PocketParker is an example of a subset of crowdsourcing we call pocketsourcing. Pocketsourcing applications require no explicit user input or additional infrastructure, running effectively without the phone leaving the user's pocket. PocketParker detects arrivals and departures by leveraging existing activity recognition algorithms. Detected events are used to maintain per-lot availability models and respond to queries. By estimating the number of drivers not using PocketParker, a small fraction of drivers can generate accurate predictions. Our evaluation shows that PocketParker quickly and correctly detects parking events and is robust to the presence of hidden drivers. Camera monitoring of several parking lots as 105 PocketParker users generated 10;827 events over 45 days shows that PocketParker was able to correctly predict lot availability 94% of the time.