Requirements engineers have the responsibility for classifying software requirements into functional and nonfunctional variants. As software architects need quality requirements to be known to get their job done, mach...
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ISBN:
(纸本)9783031752001;9783031752018
Requirements engineers have the responsibility for classifying software requirements into functional and nonfunctional variants. As software architects need quality requirements to be known to get their job done, machine learning is employed to speed up and add consistency to the process of identifying and categorizing requirements so that effort may be spent more effectively. We experimented with the effects of different machine learning algorithms, as well as different pre-processing and feature selection techniques. It was determined that, for this application, stop words should not be removed and that performing lemmatization on words provides the most effective features for classification. Furthermore, after finalizing our choices of pre-processing techniques and algorithm to use, we proposed a modification to the Extensive Feature Selector by gathering the most distinctive words in each category and using a list of those as our main features. By using a threshold of 0.013, we obtained an F1 score of 0.787, which is an improvement on the base Enhanced Feature Selector's F1 score of 0.761 with the same number of word features.
In this work, we present GitTruck@Duck;a web-powered software visualization tool that combines hierarchical file structure with configurable software evolution and collaboration metrics on adjustable time ranges. In a...
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ISBN:
(纸本)9798350395693;9798350395686
In this work, we present GitTruck@Duck;a web-powered software visualization tool that combines hierarchical file structure with configurable software evolution and collaboration metrics on adjustable time ranges. In an automated mining process, Git Truck aggregates a system's Git history using an in-memory relational database, along with an algorithm for detecting the renaming of files over time. Users can explore the Git history in a 2D hierarchical visualization of folders and files, where they encode evolution and collaboration metrics (e.g., top contributors or last change date) on the size and color of the marks that represent files. Users can gain fine-grain control over these metrics by specifying the time ranges for inspection.
We propose a method for enhancing cybersecurity in spacecraft operations by analyzing and reducing the attack surface of flight software. We advocate for reducing complexity in the software architecture and adopting m...
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ISBN:
(纸本)9798350384529;9798350384512
We propose a method for enhancing cybersecurity in spacecraft operations by analyzing and reducing the attack surface of flight software. We advocate for reducing complexity in the software architecture and adopting more secure architectural principles to mitigate vulnerabilities and make spacecraft more resilient against cyber attacks. By utilizing a systematic approach, we scrutinize key areas, such as the real-time operating system (RTOS) and operating system abstraction layer (OSAL), and develop mitigations for issues we find. This study's findings suggest strategies for simplifying abstractions to make them more secure, addressing implementation issues, and providing supporting evidence for moving to a more resilient architectural approach.
software composition analysis (SCA) tools have been widely adopted to identify vulnerable libraries used in software applications. Such SCA tools depend on a vulnerability database to know affected libraries of each v...
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The Team Orienteering Problem with Time Windows ( TOPTW) is a typical variant of the Orienteering Problem (OP) that each node can only provide one time service in a predefined time window, its objective is to maximize...
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ISBN:
(纸本)9798350386783;9798350386776
The Team Orienteering Problem with Time Windows ( TOPTW) is a typical variant of the Orienteering Problem (OP) that each node can only provide one time service in a predefined time window, its objective is to maximize the total score of visiting nodes with a given number of paths. In this study we propose an improved ALNS(adaptive large neighborhood search) algorithm to solve the TOPTW problem, which clusters nodes according to their features to construct the initial solution, and design knowledge- based removal and repair operators to optimize solutions. To fully evaluate the proposed algorithm, some typical benchmark datasets are taken as the test instance suite and several state-of-the-art algorithms are chosen to compare with the proposed algorithm. Experimental results show our algorithm has satisfactory accuracy and far better performance.
Nowadays, the rapid spread of Artificial Intelligence (AI) in the daily lives of individuals is raising multiple challenges and issues. The latter must be timely and effectively addressed since they have a substantial...
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ISBN:
(纸本)9798400717017
Nowadays, the rapid spread of Artificial Intelligence (AI) in the daily lives of individuals is raising multiple challenges and issues. The latter must be timely and effectively addressed since they have a substantial impact on numerous domains with implications concerning the technicalities, typically faced by computerscience, and also to multiple areas of society, such as law, ethics, psychology, etc. The PhD project presented in this manuscript aims at finding new human-centered methodologies and techniques, belonging to the Human-computer Interaction (HCI) discipline, that can be applied to the design and development of AI to foster the symbiotic relationship between machines and humans. The project deals with Symbiotic Artificial Intelligence (SAI), which has the goal of supporting humans in executing their tasks without replacing them. The research aims at finding the intersection between softwareengineering (SE), HCI, and AI to create a framework supporting and providing guidance to all the parties involved in the process of creating effective SAI systems.
The proceedings contain 67 papers. The topics discussed include: leveraging feature headers to learn sparse and semantically pertinent linear models;heart rate estimation by PCA with LSTM from video-based plethysmogra...
ISBN:
(纸本)9781665491983
The proceedings contain 67 papers. The topics discussed include: leveraging feature headers to learn sparse and semantically pertinent linear models;heart rate estimation by PCA with LSTM from video-based plethysmography under periodic noise;selecting an open-source home automation system using the AHP methodology;clustering of human gene expression stimulated by bacterial infection from microarray analysis;deep learning for sex determination of the clavicle: a blind study on a Thai population;face recognition using skin color segment and modified binary particle swarm optimization;information systems in medical settings: a Covid-19 detection system using x-ray scans;job-candidate classifying and ranking system-based machine learning method;Thai paraphrasing tool for chatbot intent recognition training;python code smell detection using machine learning;a framework for bang Saen safe food avenue management system;movie recommendation system using director-based;Isarn dialect word segmentation using bi-directional gated recurrent unit with transfer learning approach;and contextual data modeling for recommender system in building and construction materials business.
The complex nature of compliance with industry regulations, along with the increasing requirements for Product Change Notifications (PCNs) and managing product complexity, poses challenges for component manufacturers ...
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ISBN:
(纸本)9783031720406;9783031720413
The complex nature of compliance with industry regulations, along with the increasing requirements for Product Change Notifications (PCNs) and managing product complexity, poses challenges for component manufacturers and machine builders in the engineering phase of product development working with up-to-date Digital Twin (DT) data. This situation leads to delays, potential compliance issues, and inefficiencies. Main reasons are the lack of interoperability PCNs, poor data quality, and the absence of direct traceability and tracking of product changes. To address these challenges, this paper proposes a solution approach that involves utilizing a Product Lifecycle Management (PLM) system and the Asset Administration Shell (AAS). Their design and mutual adjustment enhance collaboration, improve data quality, enable traceability, and finally, increase efficiency within engineering processes. The paper presents first results of a prototype implementation and outlines the next steps of the overarching research project.
One of the most crucial aspects of software development is software cost estimation. It entails calculating the amount of time and money needed to finish the software development. software cost estimation is crucial w...
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Sustainable software development is a major challenge in the softwareengineering industry. software practitioners lack practical guidance or tools for integrating social sustainability in software development process...
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ISBN:
(纸本)9798350322637
Sustainable software development is a major challenge in the softwareengineering industry. software practitioners lack practical guidance or tools for integrating social sustainability in software development processes. This study proposes stakeholder mapping and the use of sustainability personas as a framework to guide software practitioners in making decisions that support socially sustainable software development. We will evaluate the effectiveness in a randomized controlled experiment with 104 final-year undergraduate computerscience students who would select features to be included in the development of a software application. We aim to show how these interventions helps to improve software practitioners' perspective of social sustainability in software development.
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