Paper Info
Title
Analytics-Driven Load Testing: An Industrial Experience Report on Load Testing of Large-Scale Systems.
Abstract
Assessing how large-scale software systems behave under load is essential because many problems cannot be uncovered without executing tests of large volumes of concurrent requests. Load-related problems can directly affect the customer- perceived quality of systems and often cost companies millions of dollars. Load testing is the standard approach for assessing how a system behaves under load. However, designing, executing and analyzing a load test can be very difficult due to the scale of the test (e.g., simulating millions of users and analyzing terabytes of data). Over the past decade, we have tackled many load testing challenges in an industrial setting. In this paper, we document the challenges that we encountered and the lessons that we learned as we addressed these challenges. We provide general guidelines for conducting load tests using an analytics-driven approach. We also discuss open research challenges that require attention from the research community. We believe that our experience can be beneficial to practitioners and researchers who are interested in the area of load testing.
Year
DOI
Venue
2017
10.1109/ICSE-SEIP.2017.26
ICSE-SEIP
Keywords
Field
DocType
load testing, test analysis, performance testing, mining software repositories
System integration testing,Systems engineering,Load testing,Computer science,Software performance testing,White-box testing,Real-time computing,Software reliability testing,Acceptance testing,Test strategy,Cloud testing
Conference
ISBN
Citations 
PageRank 
978-1-5386-2718-1
4
0.41
References 
Authors
32
7
Name
Order
Citations
PageRank
Tse-Hsun Chen123319.10
Mark D. Syer21348.12
Weiyi Shang356638.03
Zhen Ming Jiang478040.11
Ahmed E. Hassan55959287.68
Mohamed N. Nasser61165.13
Parminder Flora741619.50