https://ogma.newcastle.edu.au/vital/access/ /manager/Index en-au 5 https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:39297 Mon 20 Nov 2023 15:59:35 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:43530 =4 is even more challenging. Inspired by the success of automated algorithm configuration and automated algorithm selection in solving combinatorial optimization problems, in this paper, we investigate the efficacy of automated algorithm configuration and automated algorithm selection for the CCAG problem, and propose a novel, automated CCAG approach called AutoCCAG. Extensive experiments on public benchmarks show that AutoCCAG can find much smaller-sized CCAs than current state-of-the-art approaches, indicating the effectiveness of AutoCCAG. More encouragingly, to our best knowledge, our paper reports the first results for CCAG with a high coverage strength (i.e., 5-way CCAG) on public benchmarks. Our results demonstrate that AutoCCAG can bring considerable benefits in testing highly configurable software systems.]]> Mon 20 Nov 2023 14:26:03 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:40338 Fri 08 Jul 2022 10:19:33 AEST ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:39690 Fri 02 Sep 2022 08:42:46 AEST ]]>