Publications and Research

Document Type

Article

Publication Date

Spring 5-25-2019

Abstract

Streaming APIs are becoming more pervasive in mainstream Object-Oriented programming languages. For example, the Stream API introduced in Java 8 allows for functional-like, MapReduce-style operations in processing both finite and infinite data structures. However, using this API efficiently involves subtle considerations like determining when it is best for stream operations to run in parallel, when running operations in parallel can be less efficient, and when it is safe to run in parallel due to possible lambda expression side-effects. In this paper, we present an automated refactoring approach that assists developers in writing efficient stream code in a semantics-preserving fashion. The approach, based on a novel data ordering and typestate analysis, consists of preconditions for automatically determining when it is safe and possibly advantageous to convert sequential streams to parallel and unorder or de-parallelize already parallel streams. The approach was implemented as a plug-in to the Eclipse IDE, uses the WALA and SAFE analysis frameworks, and was evaluated on 11 Java projects consisting of ∼642K lines of code. We found that 57 of 157 candidate streams (36.31%) were refactorable, and an average speedup of 3.49 on performance tests was observed. The results indicate that the approach is useful in optimizing stream code to their full potential.

Share

COinS
 
 

To view the content in your browser, please download Adobe Reader or, alternately,
you may Download the file to your hard drive.

NOTE: The latest versions of Adobe Reader do not support viewing PDF files within Firefox on Mac OS and if you are using a modern (Intel) Mac, there is no official plugin for viewing PDF files within the browser window.