37 citations · 69 across the 8 of their papers we have counts for
9 papers
OpTime: Statically Reducing the Execution Time of Microbenchmark Suites Using Stability Metrics
Nils Japke, Martin Grambow, Christoph Laaber +1
Performance regressions have a tremendous impact on the quality of software. One way to catch regressions before they reach production is executing performance tests before deploym…
The Early Microbenchmark Catches the Bug -- Studying Performance Issues Using Micro- and Application Benchmarks
Nils Japke, Christoph Witzko, Martin Grambow +1
An application's performance regressions can be detected by both application or microbenchmarks. While application benchmarks stress the system under test by sending synthetic but…
Efficiently Detecting Performance Changes in FaaS Application Releases
Martin Grambow, Tim Dockenfuß, Trever Schirmer +2
The source code of Function as a Service (FaaS) applications is constantly being refined. To detect if a source code change introduces a significant performance regression, the tra…
Application-Centric Benchmarking of Distributed FaaS Platforms using BeFaaS
Martin Grambow, Tobias Pfandzelter, David Bermbach
Due to the popularity of the FaaS programming model, there is now a wide variety of commercial and open-source FaaS systems. Hence, for comparison of different FaaS systems and the…
Using Microbenchmark Suites to Detect Application Performance Changes
Martin Grambow, Denis Kovalev, Christoph Laaber +2
Software performance changes are costly and often hard to detect pre-release. Similar to software testing frameworks, either application benchmarks or microbenchmarks can be integr…
BeFaaS: An Application-Centric Benchmarking Framework for FaaS Platforms
Martin Grambow, Tobias Pfandzelter, Luk Burchard +3
Following the increasing interest and adoption of FaaS systems, benchmarking frameworks for determining non-functional properties have also emerged. While existing (microbenchmark)…
MockFog 2.0: Automated Execution of Fog Application Experiments in the Cloud
Jonathan Hasenburg, Martin Grambow, David Bermbach
Fog computing is an emerging computing paradigm that uses processing and storage capabilities located at the edge, in the cloud, and possibly in between. Testing and benchmarking f…
FBase: A Replication Service for Data-Intensive Fog Applications
Jonathan Hasenburg, Martin Grambow, David Bermbach
The combination of edge and cloud in the fog computing paradigm enables a new breed of data-intensive applications. These applications, however, have to face a number of fog-specif…
Dockerization Impacts in Database Performance Benchmarking
Martin Grambow, Jonathan Hasenburg, Tobias Pfandzelter +1
Docker seems to be an attractive solution for cloud database benchmarking as it simplifies the setup process through pre-built images that are portable and simple to maintain. Howe…