With the rise and development of microelectronics as well as the optoelectronics industry, micro photoelectric devices, like miniature cameras, pose a serious threat to the privacy and security of personal and public ...
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Digital Image Correlation (DIC) is a non-contact full field measurement method. This method utilizes computer vision and image processing techniques to measure and analyze the displacement and strain parameters of obj...
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Requirements validation is an important aspect for ensuring high quality software. Commonly used are requirements inspections, where the specification is read from different persons assuming different roles or applyin...
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ISBN:
(纸本)9798400700446
Requirements validation is an important aspect for ensuring high quality software. Commonly used are requirements inspections, where the specification is read from different persons assuming different roles or applying different reading techniques, partly accompanied by checklists. Actual defect detection with requirements inspection is costly, and defect detection rates must be considered low. Therefore, repeated validation is used or validation with multiple inspection groups - known as N-fold inspections. However, this does not only yield more defects found, but also more false positives. In this paper, we investigate how defect aggregation can be used to improve the overall quality of validation. Therefore, we conducted an experiment with 22 N-fold inspection groups consisting of four to five reviewers each. Results show that simple aggregation of all results leads to a number of false positives that can actually negatively impact the validation task, while the use of more tailored aggregation strategies can considerably improve the validation of requirements with N-fold inspections.
In multi-institutional patient data sharing scenarios, maintaining fine-grained access control while safeguarding privacy and adapting to real-world environments is crucial. Traditional attribute-based encryption (ABE...
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The growing importance of digital data security has led to increased exploration of advanced cryptographic methods, including innovative bio-inspired techniques such as DNA cryptography. In this paper, we present an e...
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Medical information extraction (IE) tasks, including named entity recognition (NER), relation extraction (RE), and event extraction (EE), are crucial for constructing medical knowledge graphs from unstructured text. H...
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The retrofit of aircraft - the design and installation of new cabins into existing planes, comes with challenges, particularly regarding access to the necessary information. Although aircraft are generally similar, ea...
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Nowadays, the vast majority of university careers declare a competency-based curriculum. However, having concrete evidence to measure learning outcomes can be a complex problem in engineering. Academics make great eff...
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Dentigerous cysts, a prevalent form of odontogenic lesions, present a significant challenge in dental diagnostics due to their often asymptomatic nature and potential for complications if left untreated. Early and acc...
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Context: The quality of software systems has always been a crucial task and has led to the establishment of various reputable software quality models. However, the automation trends in softwareengineering have challe...
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ISBN:
(纸本)9783031603273;9783031603280
Context: The quality of software systems has always been a crucial task and has led to the establishment of various reputable software quality models. However, the automation trends in softwareengineering have challenged the traditional notion of quality assurance, motivating the development of a new paradigm with advanced AI-based quality standards. Objective: The goal of this paper is to bridge the gap between theoretical frameworks and practical implementations on the aspects of software quality. Methodology: This study involved an extensive literature review of software quality models, including McCall, Boehm, Dromey, FURPS, and ISO/IEC 25010. The detailed information about quality attributes from each model was systematically synthesized and organized into datasets, data frames, and Python dictionaries. The resulting resources were then shared and made accessible through a public GitHub repository. Results: In brief, this research provides (i) a comprehensive dataset on software quality containing catalogs of quality models and attributes, (ii) a Python dictionary encapsulating the quality models and their associated characteristics for convenient empirical experimentation, (iii) the application of advanced knowledge graph techniques for the analysis and visualization of software quality parameters, and (iv) the complete construction steps and resources for download, ensuring easy integration and accessibility. Conclusion: This study builds a foundational step towards the standardization of automating software quality modeling to enhance not just quality but also efficiency for software development. For our future work, there will be a concentration on the practical utilization of the dataset in real-world software development contexts.
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