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ICSE 2022
Sun 8 - Fri 27 May 2022
Mon 9 May 2022 13:00 - 13:30 at MET room - Metamorphic Relations Chair(s): Alastair F. Donaldson

Deep Learning (DL) components are increasing their presence in mission and safety-critical systems, such as autonomous vehicles. The verification process of such systems needs to be rigorous, for which automated solutions are paramount. To allow test automation, test oracles are necessary. In the context of DL systems, metamorphic test oracles have found to be effective. However, such oracles require the execution of multiple tests, which makes testing more expensive. Metamorphic relation composition can reduce the cost of metamorphic testing. However, its effectiveness has found mixed answers. This paper reports the preliminary results of our study on measuring the cost-effectiveness of composite metamorphic relations for testing DL systems. To this end, we empirically evaluate the cost-effectiveness of composite metamorphic relations within a DL model for object classification. Our results suggest that composite metamorphic relations reduce the failure revealing capability when compared to their component metamorphic relations.

Mon 9 May

Displayed time zone: Eastern Time (US & Canada) change

13:00 - 14:00
Metamorphic RelationsMET at MET room
Chair(s): Alastair F. Donaldson Imperial College London
On the Cost-Effectiveness of Composite Metamorphic Relations for Testing Deep Learning Systems
Aitor Arrieta Mondragon University
Automated Generation of Metamorphic Relations for Query-Based Systems
Sergio Segura Universidad de Sevilla, Juan C. Alonso Universidad de Sevilla, Alberto Martin-Lopez Universidad de Sevilla, Amador Durán University of Seville, Javier Troya Universidad de Málaga, Spain, Antonio Ruiz-Cortés University of Seville

Information for Participants
Mon 9 May 2022 13:00 - 14:00 at MET room - Metamorphic Relations Chair(s): Alastair F. Donaldson
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