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检索条件"任意字段=Knowledge-Based Software Engineering Conference"

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software requirements engineering maturity model (SREMM) in offshore software development outsourcing 17

Software requirements engineering maturity model (SREMM) in ...

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17th International conference on Frontiers of Information Technology, FIT 2019

作者： Shafiq, Muhammad Zhang, Qinghua Akbar, Muhammad Azeem School of Computer Science and Technology Chongqing University of Posts and Telecommunications Chongqing China School of Big Data and Software Engineering Chongqing University Chongqing China

ISBN: (纸本)9781728166254

Presently, a number of software development firms are being adopted offshore software development outsourcing (OSDO) mostly due to the noteworthy profits in the shape of good return on investment. However, many challenges related to OSDO are complicated especially interrelated to requirements engineering (RE) process. It is observed that RE contributes an important part in the successful execution of OSDO projects. The development of 'software Requirements engineering Maturity Model (SREMM) in the context of OSDO' is the main focus of this research that can assist RE experts to assess and measure their RE process readiness prior to implementation RE activities in the domain of OSDO. The SREMM is based on already published literature about RE, an industrial questionnaire survey with RE experts, and the knowledge about the factors that can influence the employment of RE activities in an OSDO environment. © 2019 IEEE.

关键词： Requirements engineering

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Interaction of Spatial Computing In Augmented Reality

Interaction of Spatial Computing In Augmented Reality

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International conference on Advanced Computing and Communication Systems (ICACCS)

作者： S. Balakrishnan M.Syed Shahul Hameed K Venkatesan G Aswin Sri Krishna College of Engg. and Technology Coimbatore Tamilnadu India University of Technology and Applied Sciences - SUR PO BOX: 484 PC 411 SUR The Sultanate of Oman St. Josephs college of engineering Full stack software developer zealbots in chadura Tech Tiruchirapalli Tamilnadu India

In the above certain years, the technology of spatial computing has recognized the environment growth of simulated reality by user interaction and extensive knowledge which assist the 3D canvas used space for user interfaces. Spatial computing is widely compatible with XR which is an Extended Reality. This acts itself as an umbrella phase for Augmented Reality (AR), Mixed Reality (MR) and Virtual Reality (VR). Moreover, we are looking into the deep concepts of AR in spatial computing. Augmented reality is a new medium of laminating and merging digital contents towards the real world. This medium provides individual assets connecting the physical-virtual world with steady control and enhances the overall environment reality of user's information. These are obtained based on mobile devices, projection devices and mounted displays that help in augmenting the information over real-life. In advance, AR is part of spatial augmented reality which is an assistive technology tool used for determining the completion time of task, speed range and quality of interactive computation. This paper delivers the effectiveness of Augmented Reality (AR) with possible combination of technologies and applications from a user's point of view.

关键词： Three-dimensional displays Spatial augmented reality Glass User interfaces Tools Internet X reality

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Attaining competences in software quality oriented design based on cyclic learning

Attaining competences in software quality oriented design ba...

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Frontiers in Education (FIE) conference

作者： Camelia Şerban Virginia Niculescu Andreea Vescan Faculty of Mathematics and Computer Science Babes-Bolyai University Cluj-Napoca România

ISBN: (数字)9781728189611

ISBN: (纸本)9781728189628

This Research to Practice Full Paper delineates the impact of using cyclic learning to obtain competences in software quality oriented design. Nowadays, the need for quality in the software systems has become more and more a concern for many researchers and industry practitioners. Developing students' appropriate competencies and skills in writing quality programs must be an important objective of any software engineering related course from the Computer Science Curricula. In order to attain this goal, the paper presents a new strategy for reflecting software quality models into software engineering related courses based on cyclic learning. The method is based on an educational strategy that integrates the cyclic learning approach and induces to the students the awareness regarding the importance of developing quality software. We focus on a set of software quality characteristics described by the ISO25010 quality model for which we analyze the level of knowledge attained by the students during the entire bachelor cycle of studies. The study is directed by a detailed analysis of three courses: Advanced Programming Methods, Parallel and Distributed Programming, and software Systems Verification and Validation, which were chosen in order to master the analysis complexity, but at the same time to assure coverage of as many quality attributes as possible. The investigation includes qualitative and quantitative analysis, directed by the objective of establishing the efficiency and effectiveness of the approach. The results obtained confirm both students' awareness regarding the importance of learning software quality attributes, and the efficiency of using cyclic learning in teaching this subject. We also outline several insights and advantages, and we conclude by showing that the proposed strategy fulfilled the expected objectives.

关键词： software software quality Taxonomy Programming Education software systems software engineering

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Improving Machine Learning-based Code Smell Detection via Hyper-Parameter Optimization

Improving Machine Learning-Based Code Smell Detection via Hy...

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Asia-Pacific conference on software engineering

作者： Lei Shen Wangshu Liu Xiang Chen Qing Gu Xuejun Liu School of Computer Science and Technology Nanjing Tech University Nanjing China State Key Laboratory for Novel Software Technology Nanjing University Nanjing China

ISBN: (数字)9781728195537

ISBN: (纸本)9781728195544

Unlike code errors, the presence of code smell often does not affect the behavior of the software system, but it will cause quality problems in terms of readability, understandability, and efficiency. To improve the software quality and reduce the maintenance costs, the developers need to detect code smells rapidly and make corresponding code refactoring. In code smell detection, recently, machine learning-based methods become more prevalent and can overcome the shortcomings of the heuristic-based methods, which mainly rely on manually designed rules. However, to our best knowledge, there is little research to analyze whether using hyper-parameter optimization can improve the performance of machine learning-based methods. In this study, we mainly focus on two classical code smells (i.e., Data Class and Feature Envy). First, we consider four optimizers for hyper-parameter optimization, and six commonly used classifiers for machine-learning-based methods. Second, we use AUC as the performance measure to evaluate the performance of constructed models. based on final empirical results, we find that (1) Using hyper-parameter optimization can significantly improve the performance of code smell detection. (2) Differential evolution (DE) optimizer can achieve better performance than the other three optimizers when using the random forest classifier. (3) We can further improve the performance of code smell detection when performing parameter optimization on the DE optimizer.

关键词： Learning systems software quality Maintenance engineering software systems Optimization Random forests software engineering

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MBSE-Compliant Product Lifecycle Model Management 14

MBSE-Compliant Product Lifecycle Model Management

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14th Annual conference System of Systems engineering (SoSE)

作者： Wang, Chengen Shanghai Jiao Tong Univ Sch Mech Engn Shanghai Peoples R China

ISBN: (纸本)9781728104577

Systematically managing product models and their derivative data becomes a rudimentary and essential requirement for manufacturing companies to cost-effectively develop and operate complex product systems. It is recognized that conventional product data management techniques are deficient in information integration across disciplinary boundaries and product lifecycle stages. Increasing complexity in product developments demands all related aspects be dealt in accordance with systems engineering methodologies. In compliance with the prevailing model-based systems engineering (MBSE) methodology, this paper proposes to extend conventional product data management to product lifecycle model management (PLMM), which shift emphasis from data managements to model managements throughout a whole product lifecycle. This paper first presents a MBSE-compliant PLMM architecture that outlines the related methodology, modeling techniques, processes, knowledge management, etc. Then, this paper describes basic compositions of a generic PLMM software platform that materializes the PLMM approaches. Subsequently, this paper reports a joint PLMM research initiative in China. It is anticipated that manufacturing companies will benefit much from implementations of PLMM techniques.

关键词： complex product system of systems product lifecycle model management (PLMM) PLMM architecture PLMM software platform

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Emerging Structures in Information Systems: A SOS Approach 7

Emerging Structures in Information Systems: A SOS Approach

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ICSE Joint conference on IEEE/ACM 7th International Workshop on software engineering for Systems-of-Systems / 13th Workshop on Distributed software Development, software Ecosystems and Systems-of-Systems (SESoS-WDES)

作者： Salvaneschi, Paolo Univ Bergamo Dep Management Informat & Prod Engn Salvaneschi & Partners Bergamo Italy

ISBN: (纸本)9781728134390

Large industrial information systems are composed of many applications, custom-developed or COTS. Each application supports a specific business activity, and business processes are typically implemented by a distributed network of applications that evolves and grows over time. Usually, different development teams or vendors are responsible for the evolution process, each working on only part of the whole system. As a result, the organization suffers from knowledge fragmentation leading to an information system that easily evolves into a chaotic structure. In this paper, we present an experience report of developing and using SoS models of an industrial information system. based on the insight that information systems are, by all means, systems of systems (SoS), we suggest that this view may mitigate the above stated problems. We model the information system at the SoS level of abstraction. The model appears highly complex and unmanageable. The reason is that the SoS is not designed by an external entity (a system architect) but is the result of a growing process. We research if structures are emerging from the behavior-driven evolution and detect business clusters - sets of applications/systems implementing the processes of a business area. We classify the business clusters according to their shapes and apply the concepts of cohesion/coupling to them, deriving cluster measures. We discuss some possible uses of the clusters and describe how different stakeholders really used them and have benefited from the model. As these structures are at an intermediate level of abstraction between single applications/systems and the whole information system, they help addressing the issue of knowledge fragmentation.

关键词： Information System System of Systems Emergent engineering

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The Computer Vision-based Tolerancing Callout Detection Model 16

The Computer Vision-based Tolerancing Callout Detection Mode...

引用

16th CIRP conference on Computer Aided Tolerancing, CIRP CAT 2020

作者： Deng, Xin Li, Tukun Xu, Yuanping Cao, Yanlong Kong, Chao Zhang, Errui School of Software Engineering Chengdu University of Information Technology Chengdu China EPSRC Future Advanced Metrology Hub Centre for Precision Technologies School of Computing and Engineering University of Huddersfield HuddersfieldHD1 3DH United Kingdom Shandong Industrial Technology Research Institute Zhejiang University Shandong277500 China College of Engineering and Computer Science Australia National University CanberraACT2600 Australia

Tolerancing symbols play an important role in mechanical product drawings, and they directly determine the functions, mating properties, interchangeability and working life of geometrical products. A symbolic tolerancing callout containing a set of symbols represents a set of pre-ordered operations with attributes. It includes an amount of knowledge from the drawing and standard documents, which is often reconstructed manually by engineers. Thus, at the same time, a symbolic tolerancing callout makes it difficult for the end-user to understand and interpret these callouts manually. To this end, this study puts forward a tolerancing callout detection model via the use of off-the-shelf costumer-grade cameras on current mobile devices for extracting and recognizing tolerancing callout blocks and symbols in them intelligently. This model has four core components: image preprocessing, callout location and extraction, symbol and character segmentation, and deep learning-based symbol recognition. The image preprocessing component is developed to remove the interferences on the target technical drawings through the corresponding morphological methods. This study proposes a novel solution on callout block locations and extractions in callout intensive scenarios since the callout locations and extractions can directly affect the accuracy of symbol and character recognitions. Then, Huff Transform and improved projection methods have been devised to symbol and character segmentations. Finally, this study constructed a convolutional neural network (CNN) to train a symbol recognition model. The experimental results show that the proposed model gains applicability on intelligent callout extractions and the corresponding symbol recognitions. © 2020 The Authors. Published by Elsevier B.V.

关键词： Extraction

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Designing a Multi-disciplinary Group Project for Computer Science and engineering Students 10

Designing a Multi-disciplinary Group Project for Computer Sc...

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10th IEEE Global engineering Education conference (EDUCON)

作者： Kheng Leong Tan Goh, Wooi Boon Nanyang Technol Univ Sch Comp Sci & Engn Singapore Singapore

ISBN: (纸本)9781538695067

This paper describes the design of a group-based project that combines both the hardware and software disciplines of our Computer Science (CS) and Computer engineering (CE) undergraduates. The goals for the multi-disciplinary design project (MDP) are to provide our 3rd year undergraduates with the opportunities to apply the theoretical knowledge acquired from their early years to solving a practical problem, foster a continuous improvement mindset, and experience the benefits and challenges of working collaboratively in a large team. This requires the formulation of a suitably complex problem that can integrate the skill sets from both the CE and CS programmes. It also requires suitable assessment strategies that can evaluate the students at the individual level, at the group level and at the inter-group level. This paper shares our pedagogical considerations in designing the project module, our experience gleaned from conducting the module over the last five years and some results of a recent online survey conducted to gather students' feedback on their experience of MDP.

关键词： multi-disciplinary collaborative group-based design

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Reverse engineered design automation: Applying knowledge based engineering techniques to a case of automotive fixtures design configuration 22

Reverse engineered design automation: Applying knowledge bas...

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22nd International conference on engineering Design, ICED 2019

作者： Johansson, Christian Blekinge Institute of Technology Mechanical Engineering Sweden

In the production of automotive body components, fixtures are an important part of the ongoing work on geometrical assurance. The fixture is uniquely defined for each component, and the design and configuration of these are time-consuming and takes a lot of effort. The objective with this paper is to explore the use of a design automation approach and application to semi-automate the configuration process of the fixture product. The paper presents an approach to automate the configuration of the fixtures in a flexible way, by reverse engineering the configuration of the fixture product from a generic blueprint that represents the expected outcome of the process, using a knowledge-based engineering approach applied to a computer aided design (CAD) environment. A reverse-engineered design automation toolbox for a CAD-software is developed. The toolbox is developed to lead a user through the configuration process, in the way that the experts want it done, end-to-end, making use of some unconventional solutions from a design automation perspective. © 2019 Design Society. All rights reserved.

关键词： Computer aided design

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Zero-Day Malware Classification Using Deep Features with Support Vector Machines

Zero-Day Malware Classification Using Deep Features with Sup...

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IEEE International conference on Intelligent Computing and Information Systems (ICICIS)

作者： Rania El-Sayed Amir El-Ghamry Tarek Gaber Aboul Ella Hassanien Scientific Research Group Computer Engineering Cairo University Cairo Egypt Faculty of Computers and Information Mansoura University Mansoura Egypt Scientific Research Group Cairo Egypt Faculty of Computers & Informatics Suez Canal University Ismailia Egypt School of Science Engineering and Environment University of Salford UK Scientific Research Group Faculty of Computer and AI Cairo University Cairo Egypt

ISBN: (纸本)9781665411592

IoT devices are increasingly used every day. However, their limited resources cause them to be vulnerable to any malware, malicious software that causes harm to any device without the user’s knowledge. Malwares are called zero-day attacks, a serious threat to internet security since they exploit zero-day vulnerabilities with unknown nature, making them difficult to detect. To solve this problem, the structure of these malware need to be known and analyzed, therefore a small dataset of different types of malware including zero-day attack, is live-captured from network traffic to form 1000 PCAP files representing malware and normal behavior that is used as a source for traffic analysis and malware classification. Most traditional malware detection systems proposed in the literature use signature-based methods, so these systems cannot detect unknown malware types. This paper aims to introduce novel IoT image-based malware traffic analysis approaches (i.e., anomaly detection) using machine and deep learning techniques that can detect unknown malware. To achieve better analysis, PCAP files are represented as RGB images, then the supervised machine or deep learning algorithm is carefully selected to achieve the best results. In this paper, seven supervised learning algorithms with different s and levels of complexity are tested and compared with analysis to have the best one selected. The seven s are divided into two categories: Two-Layer CNN, Four-Layer CNN, VGG16, and under the category of CNN classifiers and Logistic Regression, Support Vector Machine, and K-Nearest Neighbours under the category of Ordinary Classifiers. Experimental results show that the highest performance reached is 94% with the SVM classifier on MobileNetv2 features due to its fast and stable training with fewer resources compared to the other models.

关键词： Support vector machines Deep learning Training Computational modeling Supervised learning Internet security Telecommunication traffic

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