Computational Intelligence Applications for Software Engineering Problems
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This new volume explores the computational intelligence techniques necessary to carry out different software engineering tasks. Software undergoes various stages before deployment, such as requirements elicitation, software designing, software project planning, software coding, and software testing and maintenance. Every stage is bundled with a number of tasks or activities to be performed. Due to the large and complex nature of software, these tasks become more costly and error prone. This volume aims to help meet these challenges by presenting new research and practical applications in intelligent techniques in the field of software engineering.
Computational Intelligence Applications for Software Engineering Problems discusses techniques and presents case studies to solve engineering challenges using machine learning, deep learning, fuzzy-logic-based computation, statistical modeling, invasive weed meta-heuristic algorithms, artificial intelligence, the DevOps model, time series forecasting models, and more.
This volume will be helpful to software engineers, researchers, and faculty and advanced students working on intelligent techniques in the field of software engineering.
Table of Contents
1. A Statistical Experimentation Approach for Software Quality Management and Defect Evaluations
Alankrita Aggarwal, Kanwalvir Singh Dhindsa, and P. K. Suri
2. Open Challenges in Software Measurements Using Machine Learning Techniques
3. Empirical Software Engineering and Its Challenges
Sujit Kumar, Spandana Gowda, and Vikramaditya Dave
4. Uncertain Multi-Objective COTS Product Selection Problems for Modular Software System and Their Solutions by Genetic Algorithm
Anita R. Tailor and Jayesh M Dhodiya
5. Fuzzy-Logic-Based Computational Technique for Analyzing Software Bug Repository
Rama Ranjan Panda and Naresh Kumar Nagwani
6. Software Measurements from Machine Learning to Deep Learning
7. Time Series Forecasting Using ARIMA Models: A Systematic Literature Review of 2000s
Dr. Vidhi Vig
8. Industry Maintenance Optimization Using AI
V. Sesha Srinivas, R. S. M. Lakshmi Patibandla, V. Lakshman Narayana, and B. Tarakeswara Rao
9. Comparative Study of Invasive Weed Optimization Algorithms
Shweta Shrivastava, D.K. Mishra, and Vikas Shinde
10. An Overview of Computational Tools
Navneet Kaur, Shalini Sahay, and Shruti K Dixit
11. Enhanced Intelligence Architecture
12. Systematic Literature Review of Search-Based Software Engineering Techniques for Code Modularization/Remodularization
Divya Sharma and Dr. Ganga Sharma
13. Automation of Framework Using DevOps Model to Deliver DDE Software
Ishwarappa R. Kalbandi and Mohana
Parma Nand, PhD, is affiliated with Sharda University, Greater Noida, U. P., India. He has more than 27 years of experience both in industry and academia. He has published more than 150 papers in peer-reviewed international and national journals and conferences. He has also published number of book chapters in reputed publications. He has reviewed books for publications like Tata McGraw-Hill, Galgotias Publications etc. and papers in international journals. He had successfully completed government-funded projects and spearheaded several conferences, such as an IEEE International Conferences on Computing, Communication & Automation (ICCCA), Technovation Hackathon 2019, Technovation Hackathon 2020, International Conference on Computing, Communication, and Intelligent Systems (ICCCIS-2021), as well as conferences of IEEE student chapters. He has delivered many invited and keynote talks at international and national conferences, workshops, and seminars in India and abroad. Dr. Nand is a member of many IEEE and other organizations as well as an advisory/technical program committee member of international and national conferences. He is a reviewer for a number of international journals. He has received various awards including a best teacher award from Union Minister, a best student project guide award from Microsoft in 2015, and a best faculty award from Cognizant in 2016. Dr. Nand holds a PhD in Computer Science and Engineering from IIT Roorkee, India, and MTech and BTech degrees in Computer Science & Engineering from IIT Delhi, India.
Rakesh Nitin, PhD, is an experienced professional in the field of computer science. He is currently Head of the Computer Science & Engineering Department for BTech/MTech (CSE/IT), BTech CSE-IBM Specializations, BTech CSE-I Nurture, BCA/MCA, BSc/MSc-CS at, Sharda University, Greater Noida, U. P., India. He initiated an IoT & network lab there, which is a new technology initiative for graduate, postgraduate, and doctoral students. He is also working with various other department enhancements, research and academic initiatives, industrial interfacing, and other major developments. Dr. Nitin is a recipient of the IBM Drona Award and is a Top 10 State Award Winner. He is an active member of many professional societies and is a reviewer for several prestigious international journals. His research areas include network coding, interconnection networks and architecture, and online phantom transactions. Dr. Nitin has accorded several best paper, best student, best guided student, etc. awards. Dr. Nitin has been instrumental in various industrial interfacing projects for academic and research at his previous assignments with various organizations (Amity University, Jaypee University, Galgotias, etc.). Dr. Nithin has over 100 publications in Scopus- and SCI-indexed journals and international conferences. He is currently guiding eight PhD students at various universities and industries and has successfully guided several MTech and BTech students. He holds a PhD in Computer Science & Engineering with Network Coding as his specialization.
Arun Prakash Agrawal, PhD, is Professor in the Department of Computer Science and Engineering at Sharda University, Greater Noida, India. Prior to his current assignment he served at many academic institutions, including Amity University, Noida, India; Swinburne University of Technology, Melbourne, Australia; and Amity Global Business School, Singapore. He has several research papers to his credit in refereed journals and conferences of international repute in India and abroad, including the Journal of Neural Computing and Applications. His research interests include machine learning, software testing, artificial intelligence, and soft computing. He obtained his PhD and master’s in computer science and Engineering from Guru Gobind Singh Indraprastha University, New Delhi, India.
Vishal Jain, PhD, is Associate Professor in the Department of Computer Science and Engineering, School of Engineering and Technology, Sharda University, Greater Noida, U. P., India. Before that, he has worked for several years as Associate Professor at Bharati Vidyapeeth’s Institute of Computer Applications and Management (BVICAM), New Delhi. He has more than 14 years of experience in the academics. He has more than 400 research citation indices with Google Scholar (h-index score 10 and i-10 index 11). He has authored more than 85 research papers in reputed conferences and journals, including the Web of Science and Scopus. He has authored and edited more than 10 books with various reputed publishers. His research areas include information retrieval, semantic web, ontology engineering, data mining, ad hoc networks, and sensor networks. He received a Young Active Member Award for the year 2012-13 from the Computer Society of India and a Best Faculty Award for the year 2017 and Best Researcher Award for the year 2019 from BVICAM, New Delhi. He holds PhD (CSE), MTech (CSE), MBA (HR), MCA, MCP and CCNA.