The Service Level Agreement monitor queries the infrastructure for the amount of resources available at a given site part of a Federated Cloud. Tools and techniques used to create the front end of a website change. The EOSC-SYNERGY Openstack Dashboard (ESOD) allows the graphical navigation to one of the available Openstack instances in Federated Clouds. Front-end web application development (client-side development) focuses on. It supports use cases in which VMs are started at different sites, but need to be reachable via the same hostname. Web application to host, search, compare and analyze benchmark results from Federated Clouds in EOSC.ĭiscover and use OpenStack Swift endpoints for storage provided by the EGI Federated Cloud Infrastructure.įedCloud client is a high-level Python package for a command-line client designed for interaction with the OpenStack services in the EGI Federated Cloud. The following table shows the location of the development repositories.Īccess toolset based on OpenID Connect to be used in HPC-like cluster environments While these new paradigms are welcome and bring many benefits that does not mean that they replace other proven systems of software development. The EOSC-Synergy Thematic Services are described in the section of EOSC for researchers. Implementation of an evaluator for the fulfilment of FAIR data quality based on the Research Data Alliance (RDA) criteria. JePL can be used with the SQAaaS or standalone. Includes JePL library, badges implementation, web service, etc…Ī library to implement Software Quality Assurance (SQA) checks using Jenkins CI/CD pipelines. Software Quality Assurance as a Service: is the EOSC-Synergy framework to ensure Quality. The c ommon Service Quality Assurance Baseline Criteria establishes the minimum viable set of quality requirements provides an initial approach to Service Quality Assurance, meant to be applied in the integration process of services which will be accessible through EOSC. The work started in the framework of the H2020 project INDIGO-DataCloud, and has been continuous evolved via an open collaboration framework. Improve the productivity of SE tasks.Minimum viable set of quality requirements that shall be covered when tackling any software development project. Identified the unique trends of impacts of DL models on SE tasks, as well asįive unique challenges that needed to be met in order to better leverage DL to ML/DL technique was selected for a specific SE problem. To improve the applicability and generalizability of research results, weĪnalyzed what ingredients in a study would facilitate an understanding of why a Identified five factors that influence their replicability and reproducibility. Observed a paucity of replicable and reproducible ML/DL-related SE studies and Our trend analysis demonstrated the mutual impacts that Systematic Literature Review (SLR) on 906 ML/DL-related SE papers publishedīetween 20. ML/DL-related SE studies, and to stimulate and enhance future collaborationsīetween SE/AI researchers and industry practitioners, we conducted a 10-year Improve the quality (especially the applicability and generalizability) of Reviews have emerged that suggest that ML/DL should be used cautiously. (ML)/Deep Learning (DL) and Software Engineering (SE). Introduction of ImageNet, has stimulated the synergy between Machine Learning Download a PDF of the paper titled Synergy between Machine/Deep Learning and Software Engineering: How Far Are We?, by Simin Wang and 6 other authors Download PDF Abstract: Since 2009, the deep learning revolution, which was triggered by the
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