The Westermo test system performance data set

TL;DR

This paper introduces the Westermo test system performance data set, a comprehensive collection of performance metrics from cyber-physical systems, aimed at advancing anomaly detection research and improving trust in nightly testing processes.

Contribution

It provides a publicly available, anonymized data set of performance metrics from industrial test systems to facilitate research in anomaly detection and sustainable software engineering.

Findings

Data set has been used in hackathons and student projects.

Enables research on anomaly detection using various methods.

Supports development of automated abnormal state detection.

Abstract

There is a growing body of knowledge in the computer science, software engineering, software testing and software test automation disciplines. However, a challenge for researchers is to evaluate their research findings, ideas and tools due to lack of realistic data. This paper presents the Westermo test system performance data set. More than twenty performance metrics such as CPU and memory usage sampled twice per minute for a month on nineteen test systems driving nightly testing of cyber-physical systems has been anonymized and released. The industrial motivation is to spur work on anomaly detection in seasonal data such that one may increase trust in nightly testing. One could ask: If the test system is in an abnormal state - can we trust the test results? How could one automate the detection of abnormal states? The data set has previously been used by students and in hackathons. By releasing it we hope to simplify experiments on anomaly detection based on rules, thresholds, statistics, machine learning or artificial intelligence, perhaps while incorporating seasonality. We also hope that the data set could lead to findings in sustainable software engineering.