Software Engineering and Management: Theory and Applications

This book reports state-of-the-art results in Software Engineering Research, Management & Applications in both printed and electronic form. Studies in Computation Intelligence (SCI) has grown into the most comprehensive computational intelligence research forum available in the world.

This book published original papers on both theory and practice that address foundations, state-of-the-art problems and solutions, and crucial challenges.

Presents recent research in Software Engineering and Management Provides theory and applications Written by experts in the field

Inhalt

Preventing Variadic Function Attacks Through Argument Width Counting.- A Model Based Approach for Designing and Validating ABAC Policies.- A Method for Word Extraction of Language Specific Phrases for Lyric Data of Different Languages in the Same Song and Its Application to Decoding Cultural Nuances in Dynamic Equivalence A Case Study of Let It Go from Frozen.- A Preliminary Study on Self Contained Libraries in the NPM Ecosystem.- Data Guard Android Application to Monitor Security Threat in Background Data Transmission.- Extracting Educational Code Examples from Python Textbooks.- Quantifying Conversational Nuances Using Visual Analog Scale and Clustering.- The Discovery of Aesthetic Notions of the Four Seasons in Sandaishu, the Three Imperial Anthologies of Waka Poetry Using Approximate Inverse Model Explanations (AIME).- Illustration or Illusion? Reassessing the Use of Machine Learning in Phishing Email Detection.- Integrated Search Method based on Municipal Attributes and Issue Similarities for MaaS Precedents.- Discovering different parties, factions, and close politicians using a word importance derivation method for parliamentary proceedings data.- Detection of Cyber Attacks on Cloud Based Microservices with Distributed Features.- Analyzing ChatGPT Assistance in Programming.- Mapping Cyberattack Patterns and Detection An Azure Sentinel Approach.- Marketing Insight Discovery using Approximate Inverse Model Explanations (AIME) Explanatory Derivation of Response Estimates to Campaigns for Marketing Data.