The integration of artificial intelligence (AI) into softwareengineering education presents a unique opportunity to enhance the learning experience and equip students with cutting-edge skills. In this paper, we explo...
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The goal of this paper is to deliver the overview of the current state of the art, provide experience report on developing quantum software tools, and outline the perspective for developing quantum programming tools s...
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ISBN:
(纸本)9798400707551
The goal of this paper is to deliver the overview of the current state of the art, provide experience report on developing quantum software tools, and outline the perspective for developing quantum programming tools supporting symbolic programming for the needs of quantum computing technologies. The main focus of this paper is on quantum computing technologies, as they can in the most direct way benefit from developing tools enabling the symbolic manipulation of quantum circuits and providing software tools for creating, optimizing, and testing quantum programs. We deliver a short survey of the most popular approaches in the field of quantum software development, pointing their strengths and weaknesses. This helps to formulate a list of desirable characteristics which should be included in quantum computing frameworks. Next, we describe a software architecture and its preliminary implementation supporting the development of quantum programs using symbolic approach, encouraging the functional programming paradigm, and, at the same, time enabling the integration with high-performance and cloud computing. The described software consists of several packages developed to address different needs, but nevertheless sharing common design concepts. We also outline how the presented approach could be used in tasks in quantum softwareengineering: quantum software testing and quantum circuit construction.
software deployment misconfiguration often happens and has been one of the major causes of deployment failures that give rise to service interruptions. However, there is currently no existing approach to automatically...
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ISBN:
(数字)9798400712487
ISBN:
(纸本)9798400712487
software deployment misconfiguration often happens and has been one of the major causes of deployment failures that give rise to service interruptions. However, there is currently no existing approach to automatically repairing deployment failures. We propose DeployFix, which automatically repairs software deployment failures via constraint solving in the dynamic-changing deployment environments. DeployFix first defines DeployIR as a unified intermediate representation to achieve the translation of heterogeneous specifications from different schedulers with different syntaxes. By reducing the root-cause analysis of deployment failures to the conflict resolution in propositional logic, DeployFix uses off-the-shelf constraint solvers to achieve automatic localization and diagnosis of conflicting constraints, which are the root causes of deployment failures. DeployFix finally resolves the conflicting constraints and generates repaired deployment configurations in terms of practical requirements. We evaluate DeployFix in both simulation and production environments with tens of thousands of nodes at Alibaba, on which tens of thousands of applications are running guided by hundreds of thousands of deployment constraints. Experimental results demonstrate that DeployFix outperforms the state of the art and it correctly repairs the deployment failures in minutes, even in a large production data center.
Formal methods were historically implemented in regions, which include device layout, hardware/software code sign, and verification to automate complex architecture layouts for embedded computing systems. This paper g...
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The massive growth of mobile and IoT devices demands geographically distributed computing systems for optimal performance, privacy, and scalability. However, existing edge-to-cloud serverless platforms lack location a...
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ISBN:
(纸本)9798331528690;9798331528706
The massive growth of mobile and IoT devices demands geographically distributed computing systems for optimal performance, privacy, and scalability. However, existing edge-to-cloud serverless platforms lack location awareness, resulting in inefficient network usage and increased latency. In this paper, we propose GeoFaaS, a novel edge-to-cloud Function-as-a-Service (FaaS) platform that leverages real-time client location information for transparent request execution on the nearest available FaaS node. If needed, GeoFaaS transparently offloads requests to the cloud when edge resources are overloaded, thus, ensuring consistent execution without user intervention. GeoFaaS has a modular and decentralized architecture: building on the single-node FaaS system tinyFaaS, GeoFaaS works as a stand-alone edge-to-cloud FaaS platform but can also integrate and act as a routing layer for existing FaaS services, e.g., in the cloud. To evaluate our approach, we implemented an open-source proof-of-concept prototype and studied performance and fault-tolerance behavior in experiments.
When developing aeroderivative gas turbines at Siemens Energy, engine models are subject to complex simulation campaigns for finite element analysis carried out by a legacy simulation tool. This paper presents results...
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ISBN:
(纸本)9798350300376
When developing aeroderivative gas turbines at Siemens Energy, engine models are subject to complex simulation campaigns for finite element analysis carried out by a legacy simulation tool. This paper presents results of a multi-year software modernization project to provide a software-as-a-service (SaaS) framework that enables the distributed and automated execution of simulation jobs over a hybrid cloud platform containing both private cloud and public cloud nodes. Our framework allows to significantly reduce the net time required for completing complex simulation campaigns, thus increasing the effectiveness of engineers. The performance of our framework is evaluated in various cloud configurations with complex simulation campaigns performed in the context of a real simulation task.
The "satellite data acquisition and ground processing" mode is difficult to meet the characteristics of detection and recognition in high real-time tasks such as target tracking and disaster detection caused...
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This research paper delves into the domain of Speech Emotion Recognition (SER) within softwareengineering, employing Deep Learning techniques for emotion analysis. The study critically evaluates two prevalent methodo...
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With this flood of multimedia data, protecting it is an absolute necessity. This paper describes a complete method for securing images that combines encryption and watermarking. A technique of the sort suggested furth...
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Although quantum computing has been attracting increasing attention, hardware restrictions are tight in current implementations. Intensive design exploration is therefore essential to match requirements, such as the p...
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ISBN:
(纸本)9798400706349
Although quantum computing has been attracting increasing attention, hardware restrictions are tight in current implementations. Intensive design exploration is therefore essential to match requirements, such as the problem scale and acceptable error rate, with potential designs to combine quantum computing and classical computing. The design decision made in this way is often fragile as it is sensitive to the problem scale as well as still evolving quantum services. We need continuous design decision, or adaptation and evolution, given changes in requirements or environments. In this paper, we present a framework for model-based engineering to support the continuous adaptation and evolution of quantum-classical hybrid systems. Modeling in our framework involves not only potential designs, but also rationale or evidence of design decision, which often requires simulation and experiments. This focus allows for tracing and analyzing whether the past decision is still valid or not, or whether there is uncertainty and we need further simulation and experiments. The usage of the framework is demonstrated with an example problem from steel manufacturing.
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