Performance evaluation of list iteration methods in Java: an empirical study
DOI:
https://doi.org/10.15649/2346075X.467Keywords:
Performance evaluation; Lists; List iteration methods; List iteration time; Test methodology.Abstract
Introduction: Lists are used in various software applications including web applications, desktop applications, and Internet of
Things (IoT) applications to store different types of items (e.g.
country name, product model, and device category). Users can select one or more of these items to perform specific tasks such as
filling forms, ordering products, reading device data, etc. In some
software applications, lists store a huge number of items to be iterated over in order to know what users have selected. From a software development perspective, there are a number of methods to
iterate over list items. Materials and Methods: In this paper, five
list iteration methods: Classic For, Enhanced For, Iterator, List Iterator, and For Each have been compared experimentally with each
other with regard to their performance (execution time required to
iterate over list items). Thus, a number of experimental test scenarios have been conducted to obtain the comparison results. Results
and Discussion: The experimental results of this study have been
presented in Table 4. Conclusions: Overall performance evaluation showed that Iterator and List Iterator methods outperformed
other list iteration methods in all test scenarios. However, List Iterator outperformed Iterator when the list size was small. On the
other hand, Iterator outperformed List Iterator when the list size
was large.
References
Mingyao X, Xiongfei L. Embedded database query optimization algorithm based on particle swarm optimization. Proceedings of the 7th International Conference on Measuring Technology and Mechatronics Automation; 2015 June 13-14; Nanchang, China; IEEE; 2015. p. 429-432. https://doi.org/10.1109/ICMTMA.2015.109
Oh G, Kim S, Lee SW, Moon B. SQLite optimization with phase change memory for mobile applications. Proc. VLDB Endow. 2015; 8(12): 1454-65. https://doi.org/10.14778/2824032.2824044
Kang W, Son SH, Stankovic JA. Design, implementation, and evaluation of a QoS-aware real-time embedded database. IEEE Transactions on Computers. 2012; 61(1): 45-59. https://doi.org/10.1109/TC.2010.240
H2 Database Engine (redirect) [Internet]. H2database.com. [cited 1 October 2018]. Available from: https://www.h2database.com
HSQLDB [Internet]. Hsqldb.org. [cited 1 October 2018]. Available from: http://hsqldb.org/
Apache Derby [Internet]. Db.apache.org. [cited 1 October 2018]. Available from: https://db.apache.org/derby/
SQLite Home Page [Internet]. Sqlite.org. [cited 1 October 2018]. Available from: https://sqlite.org/index.html
Ray S, Simion B, Brown AD. Jackpine: A benchmark to evaluate spatial database performance. Proceedings of the 27th International Conference on Data Engineering; 2011 April 11-16; Hannover, Germany; IEEE; 2011. p. 1139-1150. https://doi.org/10.1109/ICDE.2011.5767929
Kabakus AT, Kara R. A performance evaluation of in-memory databases. Journal of King Saud University-Computer and Information Sciences. 2017; 29(4): 520-5. https://doi.org/10.1016/j.jksuci.2016.06.007
Song W, Tao T, Gao T. Performance optimization for flash memory database in mobile embedded system. Proceedings of the 2nd International Workshop on Education Technology and Computer Science; 2010 March 6-7; Wuhan, China; IEEE; 2010. p. 35-39. https://doi.org/10.1109/ETCS.2010.109
Olson MA. Selecting and implementing an embedded database system. Computer. 2000; 33(9): 27-34. https://doi.org/10.1109/2.868694
Li Y, Manoharan S. A performance comparison of SQL and NoSQL databases. Proceedings of the IEEE Pacific Rim Conference on Communications, Computers and Signal Processing (PACRIM); 2013 August 27-29; Victoria, BC, Canada; IEEE; 2013. p. 15-19. https://doi.org/10.1109/PACRIM.2013.6625441
Patchigolla VN, Springer J, Lutes K. Embedded database management performance. Proceedings of the 8th International Conference on Information Technology: New Generations; 2011 April 11-13; Las Vegas, NV, USA; IEEE; 2011. p. 998-1001. https://doi.org/10.1109/ITNG.2011.171
Tonghui Q, Yang Q, Limin C, Zili S, Xiaowu C, Dehua L. The design of embedded database management system for mobile computing. Proceedings of the International Conference on Computer Science and Information Processing (CSIP); 2012 August 24-26; Xi'an, Shaanxi, China; IEEE; 2012. p. 1454-1457.
Batra R. A Primer on SQL. 3rd ed. Leanpub; 2015.
Sarhan QI, Gawdan IS. Web Applications and Web Services: A Comparative Study. Science Journal of University of Zakho. 2018; 6(1): 35-41. https://doi.org/10.25271/2018.6.1.375
Sarhan QI. Internet of things: a survey of challenges and issues. International Journal of Internet of Things and Cyber-Assurance. 2018; 1(1): 40-75. https://doi.org/10.1504/IJITCA.2018.090162
Sarhan QI, Gawdan IS. Java Message Service Based Performance Comparison of Apache ActiveMQ and Apache Apollo Brokers. Science Journal of University of Zakho. 2017; 5(4): 307-12. https://doi.org/10.25271/2017.5.4.376
Downloads
Published
How to Cite
Issue
Section
Altmetrics
Downloads
License
All articles published in this scientific journal are protected by copyright. The authors retain copyright and grant the journal the right of first publication, with the work simultaneously licensed under a Creative Commons Attribution-NonCommercial 4.0 International License (CC BY-NC 4.0), which permits sharing the work with authorship recognition and without commercial purposes.
Readers may copy and distribute the material from this journal issue for non-commercial purposes in any medium, provided the original work is cited and credit is given to the authors and the journal.
Any commercial use of the material from this journal is strictly prohibited without written permission from the copyright holder.
For more information on the copyright of the journal and open access policies, please visit our website.