Software Performance

Editors of the Special Issue

• Tse-Hsun (Peter) Chen, Concordia University, Canada (peterc@encs.concordia.ca)
• Cor-Paul Bezemer, University of Alberta (bezemer@ualberta.ca)
• André van Hoorn, University of Stuttgart, Germany (van.hoorn@informatik.uni-stuttgart.de)
• Catia Trubiani, Gran Sasso Science Institute, Italy (catia.trubiani@gssi.it)
• Weiyi Shang, Concordia University, Canada (shang@encs.concordia.ca)

Description of the Special Issue

Performance is one of the most important aspects of software quality. Performance can directly affect the user experience of large-scale systems, such as Amazon, eBay, and Google. Prior work shows that field issues that were reported in such systems were more often associated with the performance of the system, rather than functional issues. in fact performance has been recently defined as the new correctness. Performance-related issues occur widely in software systems, and are difficult to avoid during the software development processes. Performance-related issues have various effects on the system. Some lead to high resource (like CPU or memory) utilization, and some can cause high response times to user requests. These issues often cause an impact on users globally, resulting in significant financial and reputational repercussions. Famous examples of such failures include the rolling-out of the United States’ healthcare.gov system, the release of Apple’s MobileMe service, and NASDAQ’s initial public offering of shares in Facebook. In particular, Amazon estimated a 10 billion dollar cost for quality and efficiency issues of their ultra-large-scale systems.

Many recent studies have started to explore the relationship between software engineering activities and the performance of the software. The empirical findings and techniques have shown great success in addressing various issues and providing significant improvement to software performance, such as identifying performance requirements, detecting performance issues and anti-patterns, performance testing and monitoring, and software performance analysis. Therefore, improving the performance throughout the software engineering life cycle has attracted great attention in the software engineering and other research communities.

We invite the submission of high-quality papers describing original and significant work in all areas of software engineering that aim to model, monitor, analyze, and improve software performance, including but not limited to:

1. Empirical studies of software performance throughout the software engineering activities.
2. Approaches and techniques that assess and improve software performance throughout the software engineering activities.
3. Improving the sharing and analytics of software performance data to assist with the design and evaluation of such software engineering activities.
4. Leveraging data in software repositories to analyze and understand the causes of performance issues.

Submission Topics

The following list of topics aims to summarize targeted areas in more detail, whereas we also invite submissions to related topics.

• (Model-driven) Performance requirements engineering
• Software performance modeling
• (Continuous) Software performance testing
• Relationship between performance and architecture
• Tools and techniques for the collection and analysis of performance data
• Software performance (anti-)patterns
• Performance and agile methods

Submission Instructions

Papers should be submitted through the Empirical Software Engineering editorial manager website (http://www.editorialmanager.com/emse/) as follows (1) select “Research Papers” and (2) later on the Additional Information page:

Answer “Yes” to “Does this paper belong to a special issue?”

And select “Software Performance” for “Please select the issue your manuscript belongs to”.

For formatting guidelines as well as submission instructions, visit http://www.springer.com/computer/swe/journal/10664?detailsPage=pltci_2530593

EMSE encourages open science and reproducible research for this special issue. Please see our Open Science Initiative for further information.

Schedule

Submission Deadline: Friday May 14, 2021

First Review Notification: Sunday August 15, 2021