The Research Group is Moving!

During winter term 2021/22, we move to University of Bamberg. From Oct. 15, 2021, Fabian Beck holds a full professor position on Information Visualization.

New webpage of the research group: https://www.uni-bamberg.de/vis

Publications

Publications of the research group since 2016. For earlier publications, please visit Fabian Beck's Google Scholar or DBLP profile.

Concern-driven Reporting of Software Performance Analysis Results

Type of Publication: Article in Collected Edition

Concern-driven Reporting of Software Performance Analysis Results

Author(s):
Okanović, Dušan; van Hoorn, André; Zorn, Christoph; Beck, Fabian; Ferme, Vincenzo; Walter, Jürgen
Title of Anthology:
Companion of the 2019 ACM/SPEC International Conference on Performance Engineering
pages:
1-4
Publisher:
ACM
Publication Date:
2019
Digital Object Identifier (DOI):
doi:10.1145/3302541.3313103
Fulltext:
Concern-driven Reporting of Software Performance Analysis Results (568 KB)
Citation:
Download BibTeX

Abstract

State-of-the-art approaches for reporting performance analysis results rely on charts providing insights on the performance of the system, often organized in dashboards. The insights are usually data-driven, i.e., not directly connected to the performance concern leading the users to execute the performance engineering activity, thus limiting the understandability of the provided result. A cause is that the data is presented without further explanations.

To solve this problem, we propose a concern-driven approach for reporting of performance evaluation results, shaped around a performance concern stated by a stakeholder and captured by state-of-the-art declarative performance engineering specifications. Starting from the available performance analysis, the approach automatically generates a customized performance report providing a chart- and natural-language-based answer to the concern. In this paper, we introduce the general concept of concern-driven performance analysis reporting and present a first prototype implementation of the approach. We envision that, by applying our approach, reports tailored to user concerns reduce the effort to analyze performance evaluation results.