software modeling and digital twins are transforming the way software engineers design, operate, and maintain complex systems. In this column, we highlight cutting-edge research presented at the ACM/IEEE 27th Internat...
详细信息
software modeling and digital twins are transforming the way software engineers design, operate, and maintain complex systems. In this column, we highlight cutting-edge research presented at the ACM/IEEE 27th internationalconference on Model-Driven engineering Languages and Systems (MODELS 2024) and the 1st internationalconference on engineering Digital Twins (EDTconf 2024). The selected papers tackle critical challenges in improving system understanding, enhancing stakeholder communication, streamlining design and development processes, optimizing lifecycles, and enabling seamless integration of complex systems.
The proceedings contain 19 papers. The special focus in this conference is on Hybrid Artificial Intelligence and Enterprise Modelling for Intelligent Information Systems. The topics include: A Linked Data Based Advanc...
ISBN:
(纸本)9783031349843
The proceedings contain 19 papers. The special focus in this conference is on Hybrid Artificial Intelligence and Enterprise Modelling for Intelligent Information Systems. The topics include: A Linked Data Based Advanced Credit Rationale;interactive Machine Learning of knowledge Graph-Based Explainable Process Analysis;a Weighted knowledge Graph for Representing the Results of a Systematic Literature Review;knowledgeengineering Formalizing DECENT Meta Model;using knowledge Graphs for Record Linkage: Challenges and Opportunities;employing knowledge Graphs for Capturing Semantic Aspects of Robotic Process Automation;Regulation-Friendly Privacy-Preserving Blockchain Based on zk-SNARK;blockchain Governance Design a Computer Science Perspective;The MEV Saga: Can Regulation Illuminate the Dark Forest?;enriching Enterprise Architecture Models with Healthcare Domain knowledge;supporting Reuse of Business Process Models by Semantic Annotation;position Paper - Hybrid Artificial Intelligence for Realizing a Leadership Assistant for Platform-Based Leadership Consulting;developing a Maturity Assessment Tool to Enable the Management of Artificial Intelligence for Organizations;mapping Time-Series Data on Process Patterns to Generate Synthetic Data;Towards Crisis Response and Intervention Using knowledge Graphs - CRISP Case Study;The RAI Way: A Technical Analysis and Design Method for Building Enterprise Semantic Layers;Towards Recommendations for knowledge-Graph-Based Requirements Management in Construction: A Report on the EU DigiChecks Project.
To assess in a constructively aligned way those programming competences that are relevant for the professional practice of future software developers, an assessment format would be suitable where students actively pro...
详细信息
ISBN:
(纸本)9798350378986;9798350378979
To assess in a constructively aligned way those programming competences that are relevant for the professional practice of future software developers, an assessment format would be suitable where students actively program, within the integrated development environment (IDE) that they are individually used to, and with unrestricted access for researching in the web. A format that accommodates these needs well is "Bring Your Own Device, Open Book, Open Web", where students work on their own devices against given git repositories, with full access on knowledge bases and the internet. In this work, we share experiences and suggest well established practices for executing this exam type. As well, we discuss how the ready availability of large language models impacts this assessment type.
The proceedings contain 20 papers. The topics discussed include: methods of entering the paint in basketball games and their relevance to subsequent play;enhancing sales system efficiency through process mining;flippe...
ISBN:
(纸本)9798350308716
The proceedings contain 20 papers. The topics discussed include: methods of entering the paint in basketball games and their relevance to subsequent play;enhancing sales system efficiency through process mining;flipped classroom based on active learning in digital communications course for science in technical education on new normal;enhancing organizational efficiency and effectiveness: a process mining approach;optimizing purchase-to-pay processes through process mining and data analysis;development of a web-based student curriculum guide and portfolio;forecasting condominium prices in Bangkok through machine learning techniques;pilot flight data processing system for airline management;on the modeling and simulation of a new sir epidemic model with saturated incidence;and exploring medical resource efficiency: a process mining analysis of hospital bed, MRI, and CT-Scan allocation in healthcare systems.
In recent years, numerous Machine Learning (ML) models, including Deep Learning (DL) and classic ML models, have been developed to detect software vulnerabilities. However, there is a notable lack of comprehensive and...
详细信息
In recent years, numerous Machine Learning (ML) models, including Deep Learning (DL) and classic ML models, have been developed to detect software vulnerabilities. However, there is a notable lack of comprehensive and systematic surveys that summarize, classify, and analyze the applications of these ML models in software vulnerability detection. This absence may lead to critical research areas being overlooked or underrepresented, resulting in a skewed understanding of the current state of the art in software vulnerability detection. To close this gap, we propose a comprehensive and systematic literature review that characterizes the different properties of ML-based software vulnerability detection systems using six major Research Questions (RQs). Using a custom web scraper, our systematic approach involves extracting a set of studies from four widely used online digital libraries: ACM Digital Library, IEEE Xplore, ScienceDirect, and Google Scholar. We manually analyzed the extracted studies to filter out irrelevant work unrelated to software vulnerability detection, followed by creating taxonomies and addressing RQs. Our analysis indicates a significant upward trend in applying ML techniques for software vulnerability detection over the past few years, with many studies published in recent years. Prominent conference venues include the internationalconference on softwareengineering (ICSE), the international Symposium on software Reliability engineering (ISSRE), the Mining software Repositories (MSR) conference, and the ACM internationalconference on the Foundations of softwareengineering (FSE), whereas Information and software Technology (IST), Computers & Security (C&S), and Journal of Systems and software (JSS) are the leading journal venues. Our results reveal that 39.1% of the subject studies use hybrid sources, whereas 37.6% of the subject studies utilize benchmark data for software vulnerability detection. Code-based data are the most commonly used data t
The proceedings contain 28 papers. The topics discussed include: inter-cluster redistribution of requests with redundancy depending on their criticality to delays;removal of complex image distortions via solving integ...
The proceedings contain 28 papers. The topics discussed include: inter-cluster redistribution of requests with redundancy depending on their criticality to delays;removal of complex image distortions via solving integral equations using the ‘spectral method’;logic graphs: complete, semantic-oriented and easy to learn visualization method for OWL DL language;two-phase model of information interaction in a heterogeneous internet of things network at the last mile;skin lesion analysis using ensemble of CNN with dermoscopic images and metadata;replication of requests when dividing cluster nodes between threads of different criticality to delays in queues;the effectiveness of using bell inequality test for information retrieval in Arabic texts;and intellectual method of program interactions visualization in Unix-like systems for information security purposes.
Modern software systems are constantly evolving and therefore subject to change. Model-based knowledge about software systems improves traceability, supports software evolution processes, and helps in quality predicti...
详细信息
ISBN:
(纸本)9798350366266;9798350366259
Modern software systems are constantly evolving and therefore subject to change. Model-based knowledge about software systems improves traceability, supports software evolution processes, and helps in quality prediction. Model transformation is often used to make heterogeneous model-based knowledge usable for model-consuming processes such as quality prediction. The goal of this work is to automate model-driven knowledge transformation and rule-based knowledge refinement to support model-consuming processes. Therefore, a model-driven composition and refinement approach is introduced that links model-generating processes such as reverse engineering with model-consuming processes such as quality prediction. The approach is realized in the form of a metamodel-independent framework that can be adapted to different target metamodels. The refinement rules of our approach are formulated using a high-level programming language. Besides the metamodel-independent framework, we present a concrete instantiation of the framework for a software architecture model for quality prediction. To demonstrate the approach, the instantiation of the framework is applied to six case studies. The results indicate that we can perform a lossless composition of input information into output models. Furthermore, the demonstration shows that the metamodel-independent framework enables knowledge refinement, achieving an F-score of 1.0 by enforcing eight specific refinement rules.
To prepare students for the future workforce, it is important to provide them with knowledge and guidance about professional softwareengineering practices. One critical element of workplace practices is learning on t...
详细信息
ISBN:
(纸本)9798350378986;9798350378979
To prepare students for the future workforce, it is important to provide them with knowledge and guidance about professional softwareengineering practices. One critical element of workplace practices is learning on the job. There are few studies of how software engineers learn on the job and little focus within the literature on how this understanding can help train students. In this paper, we present a qualitative interview-based field study of workplace learning among professional software engineers. We conducted in-depth interviews with ten software engineers and analyzed the data using thematic analysis based on the learning ecologies framework. In our findings, we identify and discuss professionals' motivation and reasons for learning, the different resources they use to learn, the challenges they face in their learning, and their views on the relationship between formal education and on the job learning. We draw implications of the findings for teaching and learning, and future research.
In softwareengineering, precise requirement specifications are crucial, often derived from natural language documents prone to ambiguity and inconsistency. This can lead to critical omissions, necessitating costly ma...
详细信息
The proceedings contain 21 papers. The topics discussed include: classification of handball shot through image analysis;a DNN-based accurate masking using significant feature sets;development of an R-shiny-based shoot...
ISBN:
(纸本)9781665482738
The proceedings contain 21 papers. The topics discussed include: classification of handball shot through image analysis;a DNN-based accurate masking using significant feature sets;development of an R-shiny-based shooting area visualization application for use in basketball;a statistical model for estimating statistical contingency fuel;blockchain-based data owner rating in medical record data sharing using Ethereum;human speech production using 3-dimensional glottal accelerometric signals;a study of the accuracy of the software site survey to find the appropriate location to install the access point for indoor positioning;a comparative study of machine learning approaches for predicting close-price cryptocurrency;technical aspects of metaverse development for batik SMEs exhibitions;the impact of knowledge management activities on employee performance in Vietnamese banks;ULAT information management system: a web-based visualization of weather and lightning observations in the Philippines;development of an obstacle avoidance system for autonomous material handling vehicles;and improving efficiency of international flight operations with process mining.
暂无评论