Software Engineering Research, Management and Applications

This edited book presents scientific results of the 20th IEEE/ACIS International Conference on Software Engineering Research, Management, and Applications (SERA2022) held on May 25, 2022, in Las Vegas, USA. The aim of this conference was to bring together researchers and scientists, businessmen and entrepreneurs, teachers, engineers, computer users and students to discuss the numerous fields of computer science and to share their experiences and exchange new ideas and information in a meaningful way. Research results about all aspects (theory, applications and tools) of computer and information science and to discuss the practical challenges encountered along the way and the solutions adopted to solve them.

The conference organizers selected the best papers from those papers accepted for presentation at the conference.  The papers were chosen based on review scores submitted by members of the program committee and underwent further rigorous rounds of review.From this second round of review, 12 of the conference’s most promising papers are then published in this Springer (SCI) book and not the conference proceedings. We impatiently await the important contributions that we know these authors will bring to the field of computer and information science.

Examining the Factors that Influence Customers’ Intention to Use Smartwatches in Malaysia Using UTAUT2 Model.- Generating Adversarial Robust Defensive CAPTCHA (GARD-CAPTCHA) in Convolutional Neural Networks.- A Deep Learning Approach for Lantana Camara Weed Detection and Localization in the Natural Environment.- Modeling Concretizations in Software Design.- A Practical Style Guide and Templates Repository for Writing Effective Use Cases.- Label Correction of Sound Data with Label Noise Using Self Organizing Map.- Evaluation Method of Enterprise Cybersecurity.- A Multi-model Multi-task Learning System for Hurricane Genesis Prediction.- Development of Autonomous Driving Adaptive Simulation System Using Deep Learning Process Model.- An OCL Implementation for Model-Driven Engineering of C++.- Improving Students’ Readiness Toward the Labor Market Through Customized Learning.- Assessing Software Fault Risk with Machine Learning.