Tue 6 Nov 2018 14:15 - 14:37 at Horizons 5 - Software Analysis I Chair(s): Sebastian Elbaum

Data structure selection and tuning is laborious but can vastly improve an application's performance and memory footprint. Some data structures share a common interface and enjoy multiple implementations. We call them Darwinian Data Structures (DDS), since we can subject their implementations to survival of the fittest. We introduce ARTEMIS a multi-objective, cloud-based search-based optimisation framework that automatically finds optimal, tuned DDS modulo a test suite, then changes an application to use that DDS. ARTEMIS achieves substantial performance improvements for \emph{every} project in $5$ Java projects from DaCapo benchmark, $8$ popular projects and $30$ uniformly sampled projects from GitHub. For execution time, CPU usage, and memory consumption, ARTEMIS finds at least one solution that improves \emph{all} measures for $86%$ ($37/43$) of the projects. The median improvement across the best solutions is $4.8%$, $10.1%$, $5.1%$ for runtime, memory and CPU usage.

These aggregate results understate ARTEMIS's potential impact. Some of the benchmarks it improves are libraries or utility functions. Two examples are gson, a ubiquitous Java serialization framework, and xalan, Apache's XML transformation tool. ARTEMIS improves gson by $16.5$%, $1%$ and $2.2%$ for memory, runtime, and CPU; ARTEMIS improves xalan's memory consumption by $23.5$%. \emph{Every} client of these projects will benefit from these performance improvements.

Tue 6 Nov

13:30 - 15:00: Research Papers - Software Analysis I at Horizons 5
Chair(s): Sebastian ElbaumUniversity of Nebraska-Lincoln, USA
fse-2018-Journal-First13:30 - 13:52
Ganesha UpadhyayaFuturewei Technologies, Hridesh RajanIowa State University
fse-2018-research-papers13:52 - 14:15
Santanu Kumar DashUniversity College London, UK, Miltiadis AllamanisMicrosoft Research, Cambridge, Earl T. Barr
fse-2018-research-papers14:15 - 14:37
Michail BasiosUniversity College London, Lingbo LiUniversity College London, UK, Fan WuUniversity College London, UK, Leslie KanthanUniversity College London, UK, Earl T. Barr
DOI Pre-print
fse-2018-research-papers14:37 - 15:00
Yue LiAarhus University, Denmark, Tian TanAarhus University, Denmark, Anders MøllerAarhus University, Yannis SmaragdakisUniversity of Athens