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| artificial intelligence in software engineering: Artificial Intelligence Methods For Software Engineering Meir Kalech, Rui Abreu, Mark Last, 2021-06-15 Software is an integral part of our lives today. Modern software systems are highly complex and often pose new challenges in different aspects of Software Engineering (SE).Artificial Intelligence (AI) is a growing field in computer science that has been proven effective in applying and developing AI techniques to address various SE challenges.This unique compendium covers applications of state-of-the-art AI techniques to the key areas of SE (design, development, debugging, testing, etc).All the materials presented are up-to-date. This reference text will benefit researchers, academics, professionals, and postgraduate students in AI, machine learning and software engineering.Related Link(s) |
| artificial intelligence in software engineering: Artificial Intelligence Methods for Software Engineering Meir Kalech, Rui Abreu, Mark Last, 2021 |
| artificial intelligence in software engineering: 2014 International Conference on Artificial Intelligence and Software Engineering(AISE2014) S. K. Chen, Altair Engineering Inc., California, USA, Y. H. Chang, Chihlee Institute of Technology, Taiwan, 2014-02-06 2014 International Conference on Artificial Intelligence and Software Engineering(AISE2014) aims to provide a forum for accessing to the most up-to-date and authoritative knowledge from both Artificial Intelligence and Software Engineering. AISE2014 features unique mixed topics of AI Algorithms, Data Mining, Knowledge-based Systems, Software Process and so on. The goal of this conference is to bring researchers, engineers, and students to the areas of Artificial Intelligence and Software Engineering to share experiences and original research contributions on those topics. Researchers and practitioners are invited to submit their contributions to AISE2014. |
| artificial intelligence in software engineering: Artificial Intelligence and Software Engineering Derek Partridge, 2013-04-11 Managers, business owners, computer literate individuals, software developers, students, and researchers--all are looking for an understanding of artificial intelligence (AI) and what might be in the future. In this literate yet easy-to-read discussion, Derek Partridge explains what artificial intelligence can and cannot do, and what it holds for applications such as banking, financial services, and expert systems of all kinds. Topics include: the strengths and weaknesses of software development and engineering; machine learning and its promises and problems; expert systems and success stories; and practical software through artificial intelligence. |
| artificial intelligence in software engineering: Advances in Machine Learning Applications in Software Engineering Zhang, Du, Tsai, Jeffery J.P., 2006-10-31 This book provides analysis, characterization and refinement of software engineering data in terms of machine learning methods. It depicts applications of several machine learning approaches in software systems development and deployment, and the use of machine learning methods to establish predictive models for software quality while offering readers suggestions by proposing future work in this emerging research field--Provided by publisher. |
| artificial intelligence in software engineering: Readings in Artificial Intelligence and Software Engineering Charles Rich, Richard C. Waters, 2014-06-28 Readings in Artificial Intelligence and Software Engineering covers the main techniques and application of artificial intelligence and software engineering. The ultimate goal of artificial intelligence applied to software engineering is automatic programming. Automatic programming would allow a user to simply say what is wanted and have a program produced completely automatically. This book is organized into 11 parts encompassing 34 chapters that specifically tackle the topics of deductive synthesis, program transformations, program verification, and programming tutors. The opening parts provide an introduction to the key ideas to the deductive approach, namely the correspondence between theorems and specifications and between constructive proofs and programs. These parts also describes automatic theorem provers whose development has be designed for the programming domain. The subsequent parts present generalized program transformation systems, the problems involved in using natural language input, the features of very high level languages, and the advantages of the programming by example system. Other parts explore the intelligent assistant approach and the significance and relation of programming knowledge in other programming system. The concluding parts focus on the features of the domain knowledge system and the artificial intelligence programming. Software engineers and designers and computer programmers, as well as researchers in the field of artificial intelligence will find this book invaluable. |
| artificial intelligence in software engineering: Machine Learning Applications In Software Engineering Du Zhang, Jeffrey J P Tsai, 2005-02-21 Machine learning deals with the issue of how to build computer programs that improve their performance at some tasks through experience. Machine learning algorithms have proven to be of great practical value in a variety of application domains. Not surprisingly, the field of software engineering turns out to be a fertile ground where many software development and maintenance tasks could be formulated as learning problems and approached in terms of learning algorithms. This book deals with the subject of machine learning applications in software engineering. It provides an overview of machine learning, summarizes the state-of-the-practice in this niche area, gives a classification of the existing work, and offers some application guidelines. Also included in the book is a collection of previously published papers in this research area. |
| artificial intelligence in software engineering: Artificial Intelligence Applications for Improved Software Engineering Development: New Prospects Meziane, Farid, Vadera, Sunil, 2009-07-31 This book provides an overview of useful techniques in artificial intelligence for future software development along with critical assessment for further advancement--Provided by publisher. |
| artificial intelligence in software engineering: Software Engineering: Artificial Intelligence, Compliance, and Security Brian D'Andrade, 2021-02-16 Information security is important in every aspect of daily life. This book examines four areas where risks are present: artificial intelligence (AI), the internet of things (IoT), government and malware. The authors channel their experience and research into an accessible body of knowledge for consideration by professionals.AI is introduced as a tool for healthcare, security and innovation. The advantages of using AI in new industries are highlighted in the context of recent developments in mechanical engineering, and a survey of AI software risks is presented focusing on well-publicized failures and US FDA regulatory guidelines.The risks associated with the billions of devices that form the IoT grow with the availability of such devices in consumer products, healthcare, energy infrastructure and transportation. The risks, software engineering risk mitigation methods and standards promoting a level of care for the manufacture of IoT devices are examined because of their importance for software developers.Strategic insights for software developers looking to do business with the US federal government are presented, considering threats to both public and private sectors as well as governmental priorities from recent executive and legislative branch actions.Finally, an analysis of malicious software that infects numerous computer systems each day and causes millions of dollars in damages every year is presented. Malicious software, or malware, is software designed with hostile intent, but the damage may be mitigated with static and dynamic analyses, which are processes for studying how malware operates and analyzing potential impacts. |
| artificial intelligence in software engineering: Engineering Artificial Intelligence Software Derek Partridge, 1992 This book explains the reality of exploiting the promise of A1 in software systems. It presents the realities, the problems, the current state of the art, and future directions. It includes an examination of the problems that engineering A1 software involves, and a consideration of the alternative routes to solution of these problems. |
| artificial intelligence in software engineering: Artificial Intelligence Methods In Software Testing Mark Last, Abraham Kandel, Horst Bunke, 2004-06-03 An inadequate infrastructure for software testing is causing major losses to the world economy. The characteristics of software quality problems are quite similar to other tasks successfully tackled by artificial intelligence techniques. The aims of this book are to present state-of-the-art applications of artificial intelligence and data mining methods to quality assurance of complex software systems, and to encourage further research in this important and challenging area. |
| artificial intelligence in software engineering: Artificial Intelligence, Computer and Software Engineering Advances Miguel Botto-Tobar, Henry Cruz, Angela Díaz Cadena, 2021-04-20 This book constitutes the proceedings of the XV Multidisciplinary International Congress on Science and Technology (CIT 2020), held in Quito, Ecuador, on 26–30 October 2020, proudly organized by Universidad de las Fuerzas Armadas ESPE in collaboration with GDEON. CIT is an international event with a multidisciplinary approach that promotes the dissemination of advances in Science and Technology research through the presentation of keynote conferences. In CIT, theoretical, technical, or application works that are research products are presented to discuss and debate ideas, experiences, and challenges. Presenting high-quality, peer-reviewed papers, the book discusses the following topics: Artificial Intelligence Computational Modeling Data Communications Defense Engineering Innovation, Technology, and Society Managing Technology & Sustained Innovation, and Business Development Modern Vehicle Technology Security and Cryptography Software Engineering |
| artificial intelligence in software engineering: Artificial Intelligence Derek Partridge, 1986 |
| artificial intelligence in software engineering: Artificial Intelligence, Computer and Software Engineering Advances Miguel Botto-Tobar, Henry Cruz, Angela Díaz Cadena, 2021-04-20 This book constitutes the proceedings of the XV Multidisciplinary International Congress on Science and Technology (CIT 2020), held in Quito, Ecuador, on 26–30 October 2020, proudly organized by Universidad de las Fuerzas Armadas ESPE in collaboration with GDEON. CIT is an international event with a multidisciplinary approach that promotes the dissemination of advances in Science and Technology research through the presentation of keynote conferences. In CIT, theoretical, technical, or application works that are research products are presented to discuss and debate ideas, experiences, and challenges. Presenting high-quality, peer-reviewed papers, the book discusses the following topics: Artificial Intelligence Computational Modeling Data Communications Defense Engineering Innovation, Technology, and Society Managing Technology & Sustained Innovation, and Business Development Modern Vehicle Technology Security and Cryptography Software Engineering |
| artificial intelligence in software engineering: Artificial Intelligence and Software Engineering , 1998 |
| artificial intelligence in software engineering: Machine Learning Design Patterns Valliappa Lakshmanan, Sara Robinson, Michael Munn, 2020-10-15 The design patterns in this book capture best practices and solutions to recurring problems in machine learning. The authors, three Google engineers, catalog proven methods to help data scientists tackle common problems throughout the ML process. These design patterns codify the experience of hundreds of experts into straightforward, approachable advice. In this book, you will find detailed explanations of 30 patterns for data and problem representation, operationalization, repeatability, reproducibility, flexibility, explainability, and fairness. Each pattern includes a description of the problem, a variety of potential solutions, and recommendations for choosing the best technique for your situation. You'll learn how to: Identify and mitigate common challenges when training, evaluating, and deploying ML models Represent data for different ML model types, including embeddings, feature crosses, and more Choose the right model type for specific problems Build a robust training loop that uses checkpoints, distribution strategy, and hyperparameter tuning Deploy scalable ML systems that you can retrain and update to reflect new data Interpret model predictions for stakeholders and ensure models are treating users fairly |
| artificial intelligence in software engineering: Artificial Intelligence Methods for Optimization of the Software Testing Process Sahar Tahvili, Leo Hatvani, 2022-07-21 Artificial Intelligence Methods for Optimization of the Software Testing Process: With Practical Examples and Exercises presents different AI-based solutions for overcoming the uncertainty found in many initial testing problems. The concept of intelligent decision making is presented as a multi-criteria, multi-objective undertaking. The book provides guidelines on how to manage diverse types of uncertainty with intelligent decision-making that can help subject matter experts in many industries improve various processes in a more efficient way. As the number of required test cases for testing a product can be large (in industry more than 10,000 test cases are usually created). Executing all these test cases without any particular order can impact the results of the test execution, hence this book fills the need for a comprehensive resource on the topics on the how's, what's and whys. To learn more about Elsevier's Series, Uncertainty, Computational Techniques and Decision Intelligence, please visit this link: https://www.elsevier.com/books-and-journals/book-series/uncertainty-computational-techniques-and-decision-intelligence - Presents one of the first empirical studies in the field, contrasting theoretical assumptions on innovations in a real industrial environment with a large set of use cases from developed and developing testing processes at various large industries - Explores specific comparative methodologies, focusing on developed and developing AI-based solutions - Serves as a guideline for conducting industrial research in the artificial intelligence and software testing domain - Explains all proposed solutions through real industrial case studies |
| artificial intelligence in software engineering: Inductive Logic Programming Francesco Bergadano, Daniele Gunetti, 1996 Although Inductive Logic Programming (ILP) is generally thought of as a research area at the intersection of machine learning and computational logic, Bergadano and Gunetti propose that most of the research in ILP has in fact come from machine learning, particularly in the evolution of inductive reasoning from pattern recognition, through initial approaches to symbolic machine learning, to recent techniques for learning relational concepts. In this book they provide an extended, up-to-date survey of ILP, emphasizing methods and systems suitable for software engineering applications, including inductive program development, testing, and maintenance. Inductive Logic Programming includes a definition of the basic ILP problem and its variations (incremental, with queries, for multiple predicates and predicate invention capabilities), a description of bottom-up operators and techniques (such as least general generalization, inverse resolution, and inverse implication), an analysis of top-down methods (mainly MIS and FOIL-like systems), and a survey of methods and languages for specifying inductive bias. Logic Programming series |
| artificial intelligence in software engineering: Software Engineering: Evolution and Emerging Technologies K. Zieliński, T. Szmuc, 2005-09-27 The capability to design quality software and implement modern information systems is at the core of economic growth in the 21st century. Nevertheless, exploiting this potential is only possible when adequate human resources are available and when modern software engineering methods and tools are used. The recent years have witnessed rapid evolution of software engineering methodologies, including the creation of new platforms and tools which aim to shorten the software design process, raise its quality and cut down its costs. This evolution is made possible through ever-increasing knowledge of software design strategies as well as through improvements in system design and code testing procedures. At the same time, the need for broad access to high-performance and high-throughput computing resources necessitates the creation of large-scale, interactive information systems, capable of processing millions of transactions per seconds. These systems, in turn, call for new, innovative distributed software design and implementation technologies. The purpose of this book is to review and analyze emerging software engineering technologies, focusing on the evolution of design and implementation platforms as well as on novel computer systems related to the development of modern information services. |
| artificial intelligence in software engineering: Handbook on Artificial Intelligence-Empowered Applied Software Engineering Maria Virvou, George A. Tsihrintzis, Nikolaos G. Bourbakis, Lakhmi C. Jain, 2022-09-03 This book provides a structured overview of artificial intelligence-empowered applied software engineering. Evolving technological advancements in big data, smartphone and mobile software applications, the Internet of Things and a vast range of application areas in all sorts of human activities and professions lead current research towards the efficient incorporation of artificial intelligence enhancements into software and the empowerment of software with artificial intelligence. This book at hand, devoted to Novel Methodologies to Engineering Smart Software Systems Novel Methodologies to Engineering Smart Software Systems, constitutes the first volume of a two-volume Handbook on Artificial Intelligence-empowered Applied Software Engineering. Topics include very significant advances in (i) Artificial Intelligence-Assisted Software Development and (ii) Software Engineering Tools to develop Artificial Intelligence Applications, as well as a detailed Survey of Recent Relevant Literature. Professors, researchers, scientists, engineers and students in artificial intelligence, software engineering and computer science-related disciplines are expected to benefit from it, along with interested readers from other disciplines. |
| artificial intelligence in software engineering: Computational Intelligence Techniques and Their Applications to Software Engineering Problems Ankita Bansal, Abha Jain, Sarika Jain, Vishal Jain, Ankur Choudhary, 2020-09-27 Computational Intelligence Techniques and Their Applications to Software Engineering Problems focuses on computational intelligence approaches as applicable in varied areas of software engineering such as software requirement prioritization, cost estimation, reliability assessment, defect prediction, maintainability and quality prediction, size estimation, vulnerability prediction, test case selection and prioritization, and much more. The concepts of expert systems, case-based reasoning, fuzzy logic, genetic algorithms, swarm computing, and rough sets are introduced with their applications in software engineering. The field of knowledge discovery is explored using neural networks and data mining techniques by determining the underlying and hidden patterns in software data sets. Aimed at graduate students and researchers in computer science engineering, software engineering, information technology, this book: Covers various aspects of in-depth solutions of software engineering problems using computational intelligence techniques Discusses the latest evolutionary approaches to preliminary theory of different solve optimization problems under software engineering domain Covers heuristic as well as meta-heuristic algorithms designed to provide better and optimized solutions Illustrates applications including software requirement prioritization, software cost estimation, reliability assessment, software defect prediction, and more Highlights swarm intelligence-based optimization solutions for software testing and reliability problems |
| artificial intelligence in software engineering: Human-Centered AI Ben Shneiderman, 2022 The remarkable progress in algorithms for machine and deep learning have opened the doors to new opportunities, and some dark possibilities. However, a bright future awaits those who build on their working methods by including HCAI strategies of design and testing. As many technology companies and thought leaders have argued, the goal is not to replace people, but to empower them by making design choices that give humans control over technology. In Human-Centered AI, Professor Ben Shneiderman offers an optimistic realist's guide to how artificial intelligence can be used to augment and enhance humans' lives. This project bridges the gap between ethical considerations and practical realities to offer a road map for successful, reliable systems. Digital cameras, communications services, and navigation apps are just the beginning. Shneiderman shows how future applications will support health and wellness, improve education, accelerate business, and connect people in reliable, safe, and trustworthy ways that respect human values, rights, justice, and dignity. |
| artificial intelligence in software engineering: Data Democracy Feras A. Batarseh, Ruixin Yang, 2020-01-28 This book provides a manifesto to data democracy. After reading the chapters of this book, you are informed and suitably warned! You are already part of the data republic, and you (and all of us) need to ensure that our data fall in the right hands. Everything you click, buy, swipe, try, sell, drive, or fly is a data point. But who owns the data? At this point, not you! You do not even have access to most of it. The next best empire of our planet is one who owns and controls the world's best dataset. If you consume or create data, if you are a citizen of the data republic (willingly or grudgingly), and if you are interested in making a decision or finding the truth through data-driven analysis, this book is for you. A group of experts, academics, data science researchers, and industry practitioners gathered to write this manifesto about data democracy. - The future of the data republic, life within a data democracy, and our digital freedoms. - An in-depth analysis of open science, open data, open source software, and their future challenges. - A comprehensive review of data democracy's implications within domains such as: healthcare, space exploration, earth sciences, business, and psychology. - The democratization of Artificial Intelligence (AI), and data issues such as: bias, imbalance, context, and knowledge extraction. - A systematic review of AI methods applied to software engineering problems. |
| artificial intelligence in software engineering: Advances in Artificial Intelligence in Software Engineering Tuncer L. Oren, 1990 |
| artificial intelligence in software engineering: Software Engineering Perspectives and Application in Intelligent Systems Radek Silhavy, Roman Senkerik, Zuzana Kominkova Oplatkova, Petr Silhavy, Zdenka Prokopova, 2016-04-26 The volume Software Engineering Perspectives and Application in Intelligent Systems presents new approaches and methods to real-world problems, and in particular, exploratory research that describes novel approaches in the field of Software Engineering. Particular emphasis is laid on modern trends in selected fields of interest. New algorithms or methods in a variety of fields are also presented. The 5th Computer Science On-line Conference (CSOC 2016) is intended to provide an international forum for discussions on the latest research results in all areas related to Computer Science. The addressed topics are the theoretical aspects and applications of Computer Science, Artificial Intelligences, Cybernetics, Automation Control Theory and Software Engineering. |
| artificial intelligence in software engineering: Artificial Intelligence and Expert Systems for Engineers C.S. Krishnamoorthy, S. Rajeev, 2018-04-24 This book provides a comprehensive presentation of artificial intelligence (AI) methodologies and tools valuable for solving a wide spectrum of engineering problems. What's more, it offers these AI tools on an accompanying disk with easy-to-use software. Artificial Intelligence and Expert Systems for Engineers details the AI-based methodologies known as: Knowledge-Based Expert Systems (KBES); Design Synthesis; Design Critiquing; and Case-Based Reasoning. KBES are the most popular AI-based tools and have been successfully applied to planning, diagnosis, classification, monitoring, and design problems. Case studies are provided with problems in engineering design for better understanding of the problem-solving models using the four methodologies in an integrated software environment. Throughout the book, examples are given so that students and engineers can acquire skills in the use of AI-based methodologies for application to practical problems ranging from diagnosis to planning, design, and construction and manufacturing in various disciplines of engineering. Artificial Intelligence and Expert Systems for Engineers is a must-have reference for students, teachers, research scholars, and professionals working in the area of civil engineering design in particular and engineering design in general. |
| artificial intelligence in software engineering: Applications of Artificial Intelligence in Process Systems Engineering Jingzheng Ren, Weifeng Shen, Yi Man, Lichun Dong, 2021-06-05 Applications of Artificial Intelligence in Process Systems Engineering offers a broad perspective on the issues related to artificial intelligence technologies and their applications in chemical and process engineering. The book comprehensively introduces the methodology and applications of AI technologies in process systems engineering, making it an indispensable reference for researchers and students. As chemical processes and systems are usually non-linear and complex, thus making it challenging to apply AI methods and technologies, this book is an ideal resource on emerging areas such as cloud computing, big data, the industrial Internet of Things and deep learning. With process systems engineering's potential to become one of the driving forces for the development of AI technologies, this book covers all the right bases. - Explains the concept of machine learning, deep learning and state-of-the-art intelligent algorithms - Discusses AI-based applications in process modeling and simulation, process integration and optimization, process control, and fault detection and diagnosis - Gives direction to future development trends of AI technologies in chemical and process engineering |
| artificial intelligence in software engineering: Intelligent Algorithms in Software Engineering Radek Silhavy, 2020-08-08 This book gathers the refereed proceedings of the Intelligent Algorithms in Software Engineering Section of the 9th Computer Science On-line Conference 2020 (CSOC 2020), held on-line in April 2020. Software engineering research and its applications to intelligent algorithms have now assumed an essential role in computer science research. In this book, modern research methods, together with applications of machine and statistical learning in software engineering research, are presented. |
| artificial intelligence in software engineering: Deep Learning for Coders with fastai and PyTorch Jeremy Howard, Sylvain Gugger, 2020-06-29 Deep learning is often viewed as the exclusive domain of math PhDs and big tech companies. But as this hands-on guide demonstrates, programmers comfortable with Python can achieve impressive results in deep learning with little math background, small amounts of data, and minimal code. How? With fastai, the first library to provide a consistent interface to the most frequently used deep learning applications. Authors Jeremy Howard and Sylvain Gugger, the creators of fastai, show you how to train a model on a wide range of tasks using fastai and PyTorch. You’ll also dive progressively further into deep learning theory to gain a complete understanding of the algorithms behind the scenes. Train models in computer vision, natural language processing, tabular data, and collaborative filtering Learn the latest deep learning techniques that matter most in practice Improve accuracy, speed, and reliability by understanding how deep learning models work Discover how to turn your models into web applications Implement deep learning algorithms from scratch Consider the ethical implications of your work Gain insight from the foreword by PyTorch cofounder, Soumith Chintala |
| artificial intelligence in software engineering: Systems Engineering and Artificial Intelligence William F. Lawless, Ranjeev Mittu, Donald A. Sofge, Thomas Shortell, Thomas A. McDermott, 2021-11-02 This book provides a broad overview of the benefits from a Systems Engineering design philosophy in architecting complex systems composed of artificial intelligence (AI), machine learning (ML) and humans situated in chaotic environments. The major topics include emergence, verification and validation of systems using AI/ML and human systems integration to develop robust and effective human-machine teams—where the machines may have varying degrees of autonomy due to the sophistication of their embedded AI/ML. The chapters not only describe what has been learned, but also raise questions that must be answered to further advance the general Science of Autonomy. The science of how humans and machines operate as a team requires insights from, among others, disciplines such as the social sciences, national and international jurisprudence, ethics and policy, and sociology and psychology. The social sciences inform how context is constructed, how trust is affected when humans and machines depend upon each other and how human-machine teams need a shared language of explanation. National and international jurisprudence determine legal responsibilities of non-trivial human-machine failures, ethical standards shape global policy, and sociology provides a basis for understanding team norms across cultures. Insights from psychology may help us to understand the negative impact on humans if AI/ML based machines begin to outperform their human teammates and consequently diminish their value or importance. This book invites professionals and the curious alike to witness a new frontier open as the Science of Autonomy emerges. |
| artificial intelligence in software engineering: Software Engineering Application in Informatics Radek Silhavy, Petr Silhavy, Zdenka Prokopova, 2021-11-16 This book constitutes the first part of refereed proceedings of the 5th Computational Methods in Systems and Software 2021 (CoMeSySo 2021). The CoMeSySo 2021 Conference is breaking the barriers, being held online. CoMeSySo 2021 intends to provide an international forum for the discussion of the latest high-quality research results. The software engineering, computer science, and artificial intelligence are crucial topics for the research within an intelligent systems problem domain. |
| artificial intelligence in software engineering: Artificial intelligence & software engineering Derek Partridge, 1988 |
| artificial intelligence in software engineering: Exploring Artificial Intelligence Howard E. Shrobe, 2014-05-12 Exploring Artificial Intelligence: Survey Talks from the National Conference on Artificial Intelligence provides information pertinent to the distinct subareas of artificial intelligence research. This book discusses developments in machine learning techniques. Organized into six parts encompassing 16 chapters, this book begins with an overview of intelligent tutoring systems, which describes how to guide a student to learn new concepts. This text then links closely with one of the concerns of intelligent tutoring systems, namely how to interact through the utilization of natural language. Other chapters consider the various aspects of natural language understanding and survey the huge body of work that tries to characterize heuristic search programs. This book discusses as well how computer programs can create plans to satisfy goals. The final chapter deals with computational facilities that support. This book is a valuable resource for cognitive scientists, psychologists, domain experts, computer scientists, instructional designers, expert teachers, and research workers. |
| artificial intelligence in software engineering: Advances in Artificial Intelligence, Software and Systems Engineering Tareq Z. Ahram, 2018-06-28 This book focuses on emerging issues following the integration of artificial intelligence systems in our daily lives. It focuses on the cognitive, visual, social and analytical aspects of computing and intelligent technologies, highlighting ways to improve technology acceptance, effectiveness, and efficiency. Topics such as responsibility, integration and training are discussed throughout. The book also reports on the latest advances in systems engineering, with a focus on societal challenges and next-generation systems and applications for meeting them. It also discusses applications in smart grids and infrastructures, systems engineering education as well as defense and aerospace. The book is based on both the AHFE 2018 International Conference on Human Factors in Artificial Intelligence and Social Computing, Software and Systems Engineering, The Human Side of Service Engineering and Human Factors in Energy, July 21–25, 2018, Loews Sapphire Falls Resort at Universal Studios, Orlando, Florida, USA. |
| artificial intelligence in software engineering: Artificial Intelligence for Autonomous Networks Mazin Gilbert, 2018-09-25 Artificial Intelligence for Autonomous Networks introduces the autonomous network by juxtaposing two unique technologies and communities: Networking and AI. The book reviews the technologies behind AI and software-defined network/network function virtualization, highlighting the exciting opportunities to integrate those two worlds. Outlining the new frontiers for autonomous networks, this book highlights their impact and benefits to consumers and enterprise customers. It also explores the potential of the autonomous network for transforming network operation, cyber security, enterprise services, 5G and IoT, infrastructure monitoring and traffic optimization, and finally, customer experience and care. With contributions from leading experts, this book will provide an invaluable resource for network engineers, software engineers, artificial intelligence, and machine learning researchers. |
| artificial intelligence in software engineering: Human Factors in Global Software Engineering Rehman, Mobashar, Amin, Aamir, Gilal, Abdul Rehman, Hashmani, Manzoor Ahmed, 2019-06-28 More software engineers are likely to work in a globally distributed environment, which brings benefits that include quick and better software development, less manpower retention, scalability, and less software development cost and sharing of knowledge from the global pool of employees. However, these work environments also introduce a physical separation between team members and project leaders, which can create problems in communication and ultimately lead to the failure of the project. Human Factors in Global Software Engineering is a collection of innovative research focusing on the challenges, issues, and importance of human factors in global software engineering organizations in order to help these organizations better manage their manpower and provide an appropriate culture and technology in order to make their software development projects successful. While highlighting topics including agile software, knowledge management, and human-computer interaction, this book is ideally designed for project managers, administrators, business professionals, researchers, practitioners, students, and academicians. |
| artificial intelligence in software engineering: Handbook of Research on Applied Data Science and Artificial Intelligence in Business and Industry Chkoniya, Valentina, 2021-06-25 The contemporary world lives on the data produced at an unprecedented speed through social networks and the internet of things (IoT). Data has been called the new global currency, and its rise is transforming entire industries, providing a wealth of opportunities. Applied data science research is necessary to derive useful information from big data for the effective and efficient utilization to solve real-world problems. A broad analytical set allied with strong business logic is fundamental in today’s corporations. Organizations work to obtain competitive advantage by analyzing the data produced within and outside their organizational limits to support their decision-making processes. This book aims to provide an overview of the concepts, tools, and techniques behind the fields of data science and artificial intelligence (AI) applied to business and industries. The Handbook of Research on Applied Data Science and Artificial Intelligence in Business and Industry discusses all stages of data science to AI and their application to real problems across industries—from science and engineering to academia and commerce. This book brings together practice and science to build successful data solutions, showing how to uncover hidden patterns and leverage them to improve all aspects of business performance by making sense of data from both web and offline environments. Covering topics including applied AI, consumer behavior analytics, and machine learning, this text is essential for data scientists, IT specialists, managers, executives, software and computer engineers, researchers, practitioners, academicians, and students. |
| artificial intelligence in software engineering: Emerging Artificial Intelligence Applications in Computer Engineering Ilias G. Maglogiannis, 2007 Provides insights on how computer engineers can implement artificial intelligence (AI) in real world applications. This book presents practical applications of AI. |
| artificial intelligence in software engineering: Software Engineering Trends and Techniques in Intelligent Systems Radek Silhavy, Petr Silhavy, Zdenka Prokopova, Roman Senkerik, Zuzana Kominkova Oplatkova, 2017-04-07 This book presents new approaches and methods to solve real-world problems as well as exploratory research describing novel approaches in the field of software engineering and intelligent systems. It particularly focuses on modern trends in selected fields of interest, introducing new algorithms, methods and application of intelligent systems in software engineering. The book constitutes the refereed proceedings of the Software Engineering Trends and Techniques in Intelligent Systems Section of the 6th Computer Science On-line Conference 2017 (CSOC 2017), held in April 2017. |
| artificial intelligence in software engineering: Artificial Intelligence and Digital Systems Engineering Adedeji B. Badiru, 2021-08-11 The resurgence of artificial intelligence has been fueled by the availability of the present generation of high-performance computational tools and techniques. This book is designed to provide introductory guidance to artificial intelligence, particularly from the perspective of digital systems engineering. Artificial Intelligence and Digital Systems Engineering provides a general introduction to the origin of AI and covers the wide application areas and software and hardware interfaces. It will prove to be instrumental in helping new users expand their knowledge horizon to the growing market of AI tools, as well as showing how AI is applicable to the development of games, simulation, and consumer products, particularly using artificial neural networks. This book is for the general reader, university students, and instructors of industrial, production, civil, mechanical, and manufacturing engineering. It will also be of interest to managers of technology, projects, business, plants, and operations. |
Ways of Applying Artificial Intelligence in Software Engineering
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Artificial Intelligence techniques, which aim to create software systems that exhibit some form of human intelligence, have been employed to assist or automate
Chapter 10: The Application of Artificial Intelligence in Software ...
Many refer to that program, as the first software program. Software, since its earliest stages, aimed to help humans automate processes that require a certain level of ‘intelligence’. The process of …
Trustworthy and Synergistic Artificial Intelligence for Software ...
As illustrated in Fig. 1, this paper first describes the history and key challenges of AI for Software Engineering (AI4SE) in Sections I and II, respectively. In then describes a vision for AI4SE in …
The Role of Artificial Intelligence in Software Engineering
Nevertheless, the software engineering research and practitioner communities have fallen under the ‘AI spell’. Artificial Intelligence is about making machines intelligent, while software …
Ways of Applying Artificial Intelligence in Software …
We show the usefulness of this taxonomy by classifying 15 papers from previous editions of the RAISE workshop. Results show that the taxonomy allows classification of distinct AI …
Integrating Artificial Intelligence in Software Engineering ...
Abstract- The integration of artificial intelligence (AI) in software engineering is revolutionizing the traditional software development lifecycle. This research paper explores the multifaceted role of …
Intelligent Software Engineering: Synergy between AI and …
In our perspec-tive, we advocate the research community to step back (from just simply applying AI technologies) and explore instilling intelligence in software engineering solutions, with AI …
Synergies Between Artificial Intelligence and Software …
Jul 12, 2021 · In this chapter, we present a study of current AI trends in software engineering research, focused on the techniques more applicable to distinct aspects of the software process.
Artificial Intelligence for Software Developers - Theseus
The integration of Artificial Intelligence (AI) into software engineering practices has emerged as a pivotal area of exploration, offering new avenues for streamlining development processes and …
Artificial Intelligence and Software Engineering: Status …
The disciplines of Artificial Intelligence and Software Engineering have many commonalities. Both deal with modeling real world objects from the real world like business processes, expert …
The Impact of Artificial Intelligence on Software Development
By automating coding tasks, improving testing and enhancing project management, AI is reshaping the landscape of software engineering. This paper also addresses the challenges …
Software Engineering Using Artificial Intelligence …
Abstract: This paper surveys the application of artificial intelligence approaches to the software engineering processes. These approaches can have a major impact on reducing the time to …
Software Engineering for AI-Based Systems: A Survey
AI-based systems are software systems which include AI components. These systems learn by analyzing their environment and taking actions, aiming at having an intelligent behaviour.
Artificial Intelligence In Software Engineering: Integration …
It examines how AI can be effectively incorporated throughout the software development lifecycle, encompassing phases like requirement analysis, system design, code development, testing, …
Intelligent Software Engineering: The Significance of …
Software Development Lifecycle is the foundation of this paper, and each phase of it – Requirements Engineering, Design and Architecture, Development and Implementation, and …
Artificial Intelligence Techniques in Software Engineering …
In particular, it focuses on techniques developed (or that are being developed) in artificial intelligence that can be deployed in solving problems associated with software engineering …
Interaction between Software Engineering and Artificial …
Artificial intelligence is the field of computer science that aims to create intelligent machines. This field is defined as the study and design of intelligent agents. AI research is highly technical and …
Application of Artificial Intelligence in Software Engineering
Artificial Intelligence techniques, which aim to create software systems that exhibit some form of human intelligence, have been employed to assist or automate the activities in software …
Explainable Artificial Intelligence Techniques for Software …
Abstract— Artificial Intelligence (AI) is rapidly expanding and integrating more into daily life to automate tasks, guide decision- making, and enhance efficiency.
Artificial Intelligence in Software Requirements …
In this paper, we present the current state-of-the-art of AI in RE. We reviewed the literature published between January 2015 to December 2021 in order to understand how the state of …
Use of Artificial Intelligence in Software Development Life …
Artificial Intelligence techniques, which aim to create software systems that exhibit some form of human intelligence, have been employed to assist or automate
Chapter 10: The Application of Artificial Intelligence in …
Many refer to that program, as the first software program. Software, since its earliest stages, aimed to help humans automate processes that require a certain level of ‘intelligence’. The …
Trustworthy and Synergistic Artificial Intelligence for …
As illustrated in Fig. 1, this paper first describes the history and key challenges of AI for Software Engineering (AI4SE) in Sections I and II, respectively. In then describes a vision for AI4SE in …
