The book constitutes proceedings of the 12th Industry Symposium held in conjunction with the 18th edition of the International Conference on Distributed Computing and Intelligent Technology (ICDCIT 2022). The focus of the industry symposium is on Mobile Application Development: Practice and Experience. This book focuses on software engineering research and practice supporting any aspects of mobile application development. The book discusses findings in the areas of mobile application analysis, models for generating these applications, testing, debugging & repair, localization & globalization,…mehr
The book constitutes proceedings of the 12th Industry Symposium held in conjunction with the 18th edition of the International Conference on Distributed Computing and Intelligent Technology (ICDCIT 2022). The focus of the industry symposium is on Mobile Application Development: Practice and Experience. This book focuses on software engineering research and practice supporting any aspects of mobile application development. The book discusses findings in the areas of mobile application analysis, models for generating these applications, testing, debugging & repair, localization & globalization, app review analytics, app store mining, app beyond smartphones and tablets, app deployment, maintenance, and reliability of apps, industrial case studies of automated software engineering for mobile apps, etc. Papers included in the book describe new or improved ways to handle these aspects or address them in a more unified manner, discussing benefits, limitations, and costs of provided solutions. The volume will be useful for master, research students as well as industry professionals.
Jagannath Singh is an Associate Professor in the School of Computer Engineering at Kalinga Institute of Industrial Technology, Bhubaneswar, India. He received his Ph.D. and M.Tech. degrees from the National Institute of Technology (NIT) Rourkela, India, in 2016 and 2012, respectively. He has published several research articles in reputed conferences and journals. His research interest includes software engineering, artificial neural networks, and machine learning. He is guiding three full-time Ph.D. students. Debasish Das has over 17 years of experience in product engineering, software systems, cyber security, industrial IoT & quality management focusing on research & innovation, strategy, leadership & management. He has worked in interdisciplinary fields of design, architecture, performance engineering, application security, QA & automation along with business development & consulting. He's a founding member of TCS Video Engineering & Analytics Lab. As an enterprise architect, he is currently working as a core member of TCS Enterprise Vulnerability Management CoE. Debasish completed his M.Tech from BITS Pilani. His research area focuses on emerging cyber security paradigms e.g. malware resiliency, cyber risk, and intelligent vulnerability remediation systems. He also focuses on video engineering R&D for next-gen ecosystems using 5G, edge computing, and industrial IoT. Over the years, he has filed multiple patents, developed innovative platforms, organized tech events, and won multiple innovation awards for his research works which have been published in journals of national and international repute. Lov Kumar is an assistant professor in the Department of Computer Science and Information Systems, BITS Pilani, Hyderabad. He received his Ph.D. in Computer Science and Engineering from the National Institute of Technology (NIT) Rourkela. His current research interests are in the area of mining software repositories, machine learning, text analysis, testing of AI systems, software analytics, and social media analytics. He has delivered over 25 invited talks and published over 50 refereed publications in international conferences and journals, and two book chapters. Aneesh Krishna is an associate professor with the School of Electrical Engineering, Computing, and Mathematical Sciences, Curtin University, Australia. He holds a Ph.D. in computer science from the University of Wollongong, Australia. He was a lecturer in software engineering at the School of Computer Science and Software Engineering, University of Wollongong, Australia. His research interests include AI for software engineering, model-driven development/evolution, requirements engineering, agent systems, formal methods, data mining, computer vision, machine learning, bioinformatics, and renewable energy systems. He has published more than 130 articles in reputed journals and international conferences. His research is (or has been) funded by theAustralian Research Council (ARC), and various Australian government agencies (like NSW State Emergency Service) as well as companies such as Woodside Energy, Amristar Solutions, and Autism West Incorporated.
Inhaltsangabe
Chapter 1: A survey on Mobile Application Development Models.- Chapter 2: Mobile Technology for Smart Agriculture Deployment case for Pearl Millet disease detection.- Chapter 3: Energy Consumption Based Profiling of Android Apps.- Chapter 4: Impact of Covid-19 on IT Business.- Chapter 5: ANNDroid_A framework for Android malware detection using feature selection techniques and machine learning algorithms.
Chapter 1: A survey on Mobile Application Development Models.- Chapter 2: Mobile Technology for Smart Agriculture Deployment case for Pearl Millet disease detection.- Chapter 3: Energy Consumption Based Profiling of Android Apps.- Chapter 4: Impact of Covid-19 on IT Business.- Chapter 5: ANNDroid_A framework for Android malware detection using feature selection techniques and machine learning algorithms.
Chapter 1: A survey on Mobile Application Development Models.- Chapter 2: Mobile Technology for Smart Agriculture Deployment case for Pearl Millet disease detection.- Chapter 3: Energy Consumption Based Profiling of Android Apps.- Chapter 4: Impact of Covid-19 on IT Business.- Chapter 5: ANNDroid_A framework for Android malware detection using feature selection techniques and machine learning algorithms.
Chapter 1: A survey on Mobile Application Development Models.- Chapter 2: Mobile Technology for Smart Agriculture Deployment case for Pearl Millet disease detection.- Chapter 3: Energy Consumption Based Profiling of Android Apps.- Chapter 4: Impact of Covid-19 on IT Business.- Chapter 5: ANNDroid_A framework for Android malware detection using feature selection techniques and machine learning algorithms.
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