BIBLIOS

Document type
Journal articles

Document subtype
Full paper

Title
Improving energy-efficiency by recommending Java collections

Participants in the publication
Wellington Oliveira (Author)
FACULDADE DE CIÊNCIAS DA UNIVERSIDADE DE LISBOA
Dep. Informática
LASIGE
Renato Oliveira (Author)
UNIVERSIDADE FEDERAL DE PERNAMBUCO
Fernando Castor (Author)
UNIVERSIDADE DE UTRECHT
Gustavo Pinto (Author)
UNIVERSIDADE FEDERAL DO PARÁ
João Paulo Fernandes (Author)
UNIVERSIDADE DO PORTO

Summary
Over the last years, increasing attention has been given to creating energy-efficient software systems. However, developers still lack the knowledge and the tools to support them in that task. In this work, we explore our vision that non-specialists can build software that consumes less energy by alternating diversely-designed pieces of software without increasing the development complexity. To support our vision, we propose an approach for energy-aware development that combines the construction of application-independent energy profiles of Java collections and static analysis to produce an estimate of in which ways and how intensively a system employs these collections. We implement this approach in a tool named CT+ that works with both desktop and mobile Java systems and is capable of analyzing 39 different collection implementations of lists, maps, and sets. We applied CT+ to seventeen software systems: two mobile-based, twelve desktop-based, and three that can run in both environments. Our evaluation infrastructure involved a high-end server, two notebooks, three smartphones, and a tablet. Overall, 2295 recommendations were applied, achieving up to 16.34% reduction in energy consumption, usually changing a single line of code per recommendation. Even for a real-world, mature system such as Tomcat, CT+ could achieve a 4.12% reduction in energy consumption. Our results indicate that some widely used collections, e.g., ArrayList, HashMap, and Hashtable, are not energy- efficient and sometimes should be avoided when energy consumption is a major concern.


Institution
UNIVERSIDADE FEDERAL DE PERNAMBUCO

Where published
Empirical Software Engineering

Publication Identifiers
ISSN - 1382-3256

Publisher
Springer Science and Business Media LLC


Document Identifiers
DOI - https://doi.org/10.1007/s10664-021-09950-y
URL - http://dx.doi.org/10.1007/s10664-021-09950-y

Rankings
Web Of Science Q2 (2020) - 2.522 - COMPUTER SCIENCE, SOFTWARE ENGINEERING - SCIE