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Serverless Testing: Tool Vendors' and Experts' Point of View
Serverless architecture is an emerging design style for cloud-based software systems. Testing serverless applications plays an important role in software quality assurance. However, currently, there is no consensus on how to test and debug such systems properly. Moreover, the current lack of mature tooling is a central challenge. We designed and conducted three interviews among two tools vendor leaders in the serverless domain (Epsagon and Thundra) and one expert in the field (Yan Cui), investigating the good and bad practices and several open issues. The current status of testing and debugging in serverless-based applications depicted by the experts helped us to highlight issues and challenges that need to be deeply investigated.
Valentina Lenarduzzi
,
Annibale Panichella
Botsing, a Search-based Crash Reproduction Framework for Java
Approaches for automatic crash reproduction aim to generate test cases that reproduce crashes starting from the crash stack traces. These tests help developers during their debugging practices. One of the most promising techniques in this research field leverages search-based software testing techniques for generating crash reproducing test cases. In this paper, we introduce Botsing, an open-source search-based crash reproduction framework for Java. Botsing implements state-of-the-art and novel approaches for crash reproduction. The well-documented architecture of Botsing makes it an easy-to-extend framework, and can hence be used for implementing new approaches to improve crash reproduction. We have applied Botsing to a wide range of crashes collected from open source systems. Furthermore, we conducted a qualitative assessment of the crash-reproducing test cases with our industrial partners. In both cases, Botsing could reproduce a notable amount of the given stack traces.
Pouria Derakhshanfar
,
Xavier Devroey
,
Annibale Panichella
,
Andy Zaidman
,
Arie van Deursen
Code
Project
Video
Search-Based Crash Reproduction and Its Impact on Debugging
Mozhan Soltani
,
Annibale Panichella
,
Arie van Deursen
Preprint
PDF
Code
Dataset
Project
Single-objective versus Multi-Objectivized Optimization for Evolutionary Crash Reproduction
Mozhan Soltani
,
Pouria Derakhshanfar
,
Annibale Panichella
,
Xavier Devroey
,
Andy Zaidman
,
Arie van Deursen
Preprint
Guided Genetic Algorithm for Automated Crash Reproduction
Mozhan Soltani
,
Annibale Panichella
,
Arie van Deursen
Code
Project
Parameterizing and Assembling IR-based Solutions for Software Engineering Tasks using Genetic Algorithms
Annibale Panichella
,
Bogdan Dit
,
Rocco Oliveto
,
Massimiliano di Penta
,
Denys Poshyvanyk
,
Andrea De Lucia
The impact of test case summaries on bug fixing performance: An empirical investigation
Sebastiano Panichella
,
Annibale Panichella
,
Moritz Beller
,
Andy Zaidman
,
Harald C. Gall
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