https://ogma.newcastle.edu.au/vital/access/ /manager/Index en-au 5 https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:43766 Wed 28 Sep 2022 15:58:55 AEST ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:50483 Wed 26 Jul 2023 18:43:34 AEST ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:42523 Wed 24 Aug 2022 12:27:38 AEST ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:43502 Wed 21 Sep 2022 10:01:20 AEST ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:31844 Log², a cost-aware logging mechanism. Given a “budget” (defined as the maximum volume of logs allowed to be output in a time interval), Log² makes the “whether to log” decision through a two-phase filtering mechanism. In the first phase, a large number of irrelevant logs are discarded efficiently. In the second phase, useful logs are cached and output while complying with logging budget. In this way, Log² keeps the useful logs and discards the less useful ones. We have implemented Log² and evaluated it on an open source system as well as a real-world online service system from Microsoft. The experimental results show that Log² can control logging overhead while preserving logging effectiveness.]]> Wed 11 Apr 2018 13:44:54 AEST ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:39899 LiDAR (Linked Incident identification with DAta-driven Representation), a deep learning based approach to incident linking. More specifically, we incorporate the textual description of incidents and structural information extracted from historical linked incidents to identify possible links among a large number of incidents. To show the effectiveness of our method, we apply our method to a real-world IcM system and find that our method outperforms other state-of-the-art methods.]]> Wed 06 Jul 2022 09:15:10 AEST ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:39871 Wed 06 Jul 2022 08:49:22 AEST ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:39861 incidental incidents. Our qualitative and quantitative analyses show that incidental incidents are significant in terms of both number and cost. Therefore, it is important to prioritize incidents by identifying incidental incidents in advance to optimize incident management efforts. In particular, we propose an approach, called DeepIP (Deep learning based Incident Prioritization), to prioritizing incidents based on a large amount of historical incident data. More specifically, we design an attention-based Convolutional Neural Network (CNN) to learn a prediction model to identify incidental incidents. We then prioritize all incidents by ranking the predicted probabilities of incidents being incidental. We evaluate the performance of DeepIP using real-world incident data. The experimental results show that DeepIP effectively prioritizes incidents by identifying incidental incidents and significantly outperforms all the compared approaches. For example, the AUC of DeepIP achieves 0.808, while that of the best compared approach is only 0.624 on average.]]> Wed 06 Jul 2022 08:36:19 AEST ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:44029 Wed 05 Oct 2022 15:19:12 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:53301 Tue 21 Nov 2023 12:04:11 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:53307 Tue 21 Nov 2023 12:02:23 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:41877 Tue 16 Aug 2022 09:42:16 AEST ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:48346 Tue 14 Mar 2023 18:46:36 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:50076 Tue 09 Jul 2024 16:01:59 AEST ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:43830 Tue 04 Oct 2022 11:25:27 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:38791 Tue 01 Feb 2022 14:23:24 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:31906 Thu 29 Mar 2018 17:34:57 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:52105 Thu 28 Sep 2023 14:58:10 AEST ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:52783 Thu 26 Oct 2023 15:14:22 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:42098 Thu 18 Aug 2022 11:43:37 AEST ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:42085 Thu 18 Aug 2022 11:24:23 AEST ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:46072 Thu 10 Nov 2022 16:29:02 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:47921 Thu 09 Feb 2023 10:35:54 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:40310 Thu 07 Jul 2022 16:57:00 AEST ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:31614 Sat 24 Mar 2018 08:45:10 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:31616 Sat 24 Mar 2018 08:45:09 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:31726 Sat 24 Mar 2018 08:43:31 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:31728 Sat 24 Mar 2018 08:43:31 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:31843 Sat 24 Mar 2018 08:43:16 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:31799 Sat 24 Mar 2018 08:42:48 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:31793 Sat 24 Mar 2018 08:42:47 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:30525 Mon 13 Aug 2018 12:55:21 AEST ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:46971 Mon 12 Dec 2022 16:19:24 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:36059 Mon 03 Feb 2020 12:34:07 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:36058 Mon 03 Feb 2020 12:34:07 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:54947 Fri 22 Mar 2024 15:21:30 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:42143 Fri 19 Aug 2022 13:39:06 AEST ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:53212 Fri 17 Nov 2023 12:05:41 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:39739 Fri 17 Jun 2022 18:27:13 AEST ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:39729 Fri 17 Jun 2022 17:52:05 AEST ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:54836 Fri 15 Mar 2024 11:52:33 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:35051 Fri 14 Jun 2019 12:45:40 AEST ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:48883 Fri 14 Apr 2023 10:50:46 AEST ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:47307 Fri 13 Jan 2023 10:59:48 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:47303 Fri 13 Jan 2023 10:52:30 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:42783 Fri 02 Sep 2022 13:34:27 AEST ]]>