Eliminating abstraction overhead of Java stream pipelines using ahead-of-time program optimization

Java 8 introduced streams that allow developers to work with collections of data using functional-style operations. Compared to processing the data with traditional imperative language mechanisms, stream pipelines requires extra heap objects and virtual method calls, which results in significant run-time overheads. We investigate how to mitigate these overheads to enable processing data in the declarative style without sacrificing performance. We argue that ahead-of-time transformation is a suitable approach to optimization of stream pipelines, and we present a static analysis that is designed to guide such transformations. Experimental results show a significant performance gain, and that the technique works for realistic stream pipelines. For 10 of 11 micro-benchmarks, the optimizer is able to produce bytecode that is as effective as hand-written imperative-style code. Additionally, 77% of 6879 stream pipelines found in real-world Java programs are optimized successfully.