Modern science is relying on software more than ever. The behavior and outcomes of this software shape the scientific and public discourse on important topics like climate change, economic growth, or the spread of inf...
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ISBN:
(纸本)9798350395129;9798350395112
Modern science is relying on software more than ever. The behavior and outcomes of this software shape the scientific and public discourse on important topics like climate change, economic growth, or the spread of infections. Most researchers creating software for scientific purposes are not trained in softwareengineering. As a consequence, research software is often developed ad hoc without following stringent processes. With this paper, we want to characterize research software as a new application domain that needs attention from the Requirements engineering community. We conducted an exploratory study based on 8 interviews with 12 researchers who develop software. We describe how researchers elicit, document, and analyze requirements for research software and what processes they follow. From this, we derive specific challenges and describe a vision of Requirements engineering for research software.
The ongoing digitization of processes in all domains of everyday life driven by IT systems shows great potential for process automation, analysis, and optimization. In the last decade process mining has advanced to an...
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ISBN:
(数字)9783031641824
ISBN:
(纸本)9783031641817;9783031641824
The ongoing digitization of processes in all domains of everyday life driven by IT systems shows great potential for process automation, analysis, and optimization. In the last decade process mining has advanced to an important and mature discipline of computerscience research and has been widely adopted in industry. More recently,-acknowledging the huge potential of digital trace data to study processes-process science has been introduced as an interdisciplinary field studying how processes unfold over time. This paper discusses the potential that arises when using digital trace data not only in the context of highly automated processes but also to investigate human-centered (work) processes and elaborates on associated challenges. Examples range from the semi-automated storage and production processes in a smart factory to healthcare processes to process analysts performing process mining tasks and software engineers reading software artifacts like source code and process models.
The method of identifying and predicting software flaws or problems in software systems involves using historical data. software fault prediction is a crucial topic of research in the field of softwareengineering bec...
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To mitigate the challenges posed by data uncertainty in Full-Self Driving (FSD) systems. This paper proposes a novel feature extraction learning model called Adaptive Region of Interest Optimized Pyramid Network (ARO)...
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We are entering a new era in which software systems are becoming more and more complex and larger. So, the composition of such systems is becoming infeasible by manual means. To address this challenge, self-organising...
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ISBN:
(纸本)9783031646256;9783031646263
We are entering a new era in which software systems are becoming more and more complex and larger. So, the composition of such systems is becoming infeasible by manual means. To address this challenge, self-organising software models represent a promising direction since they allow the (bottom-up) emergence of complex computational structures from simple rules. In this paper, we propose an abstract machine, called the composition machine, which allows the definition and the execution of such models. Unlike typical abstract machines, our proposal does not compute individual programs but enables the emergence of multiple programs at once. We particularly present the machine's semantics and demonstrate its operation with well-known rules from the realm of Boolean logic and elementary cellular automata.
The definition and understanding of UX data and its possibilities for analysis and production of insights play a key role in software teams' adoption of UX practices. Information Visualization (InfoVis) offers app...
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ISBN:
(纸本)9783031592348;9783031592355
The definition and understanding of UX data and its possibilities for analysis and production of insights play a key role in software teams' adoption of UX practices. Information Visualization (InfoVis) offers approaches to assist the design of visualizations that users could better explore. Besides, it provides principles to support the analysis of information that emerged from data. This paper introduces a doctoral research project that uses Design science Research (DSR) as a general methodology to guide successive research cycles involving investigations in the grey literature and exploratory studies to build a framework. This doctoral research aims to develop a framework for assisting software teams in creating, configuring, and using visual representations to organize, extract, and communicate information embedded within UX data.
This paper addresses classical simulations in the assessment of quantum computing performance. It emphasises the significance of these simulations in understanding quantum systems and exploring the potential of quantu...
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ISBN:
(纸本)9783031492686;9783031492693
This paper addresses classical simulations in the assessment of quantum computing performance. It emphasises the significance of these simulations in understanding quantum systems and exploring the potential of quantum algorithms. The challenges posed by the exponential growth of quantum states and the limitations of full-state simulations are addressed. Various approximation techniques and encoding methods are pointed out to enable simulations of larger quantum systems, and advanced simulation strategies tailored to specific goals are also discussed. This work focuses on the feasibility of classical simulation in decision processes regarding the development of software solutions, extending the assessment beyond high-performance computing systems to include standard hardware. This opportunity can foster the adoption of classical simulations of quantum algorithms to a wider range of users.
With the rise of the library ecosystem (such as NPM for JavaScript and PyPI for Python), a developer has access to a multitude of library packages that they can adopt as dependencies into their application. Prior work...
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A University-Enterprise Deep Integration-Oriented Talent Training Approach (UED-IOTTA) was designed to improve the post-competency and employment prospects of softwareengineering graduates from colleges and universit...
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ISBN:
(纸本)9798350378986;9798350378979
A University-Enterprise Deep Integration-Oriented Talent Training Approach (UED-IOTTA) was designed to improve the post-competency and employment prospects of softwareengineering graduates from colleges and universities. This approach is tightly aligned with the demand for talent in enterprises and the development of talent in academic institutions on a variety of dimensions, including employment requirements, professional ethics, and occupational skills. Building on this paradigm, a specific implementation strategy has been developed. This implementation strategy's key components include establishing industry-specific training classes known as UED-IOTTA classes, providing softwareengineering vocational training, putting industry-academic collaboration supervision techniques into practice, developing progressive pedagogy, and defining particular university-enterprise partnership strategies. Empirical results indicate the noteworthy influence of this customized talent training approach on improving the caliber of talent advancement in the field of softwareengineering.
The rapid expansion of Artificial Intelligence has driven a surge in the development of Machine Learning (ML) pipelines, essential for constructing and maintaining ML models. Despite the growing recognition of the imp...
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ISBN:
(纸本)9783031783852;9783031783869
The rapid expansion of Artificial Intelligence has driven a surge in the development of Machine Learning (ML) pipelines, essential for constructing and maintaining ML models. Despite the growing recognition of the importance of high-quality ML pipelines, there is limited actionable guidance on improving pipelines quality at the implementation level. The Object-Oriented (OO) paradigm and software design principles have been used in softwareengineering to enhance software system quality. In this context, this work explores the coverage of existing ML pipelines in relation to OO concepts and software design principles. Our findings reveal a limited use of OO mechanisms and minimal adherence to software design principles. Specifically, issues such as poor code organization and deficient levels of coupling and cohesion were observed. Our results can shed some light on the development of strategies to overcome these deficiencies for improving ML pipelines quality.
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