A Journey Towards Bio-inspired Techniques in Software Engineering (Intelligent Systems Reference Library, 185)

✍ Scribed by Singh

• Publisher: Springer
• Year: 2020
• Tongue: English
• Leaves: 214
• Edition: 1st ed. 2020
• Category: Library

✦ Synopsis

This book covers a range of basic and advanced topics in software engineering. The field has undergone several phases of change and improvement since its invention, and there is significant ongoing research in software development, addressing aspects such as analysis, design, testing and maintenance. Rather than focusing on a single aspect of software engineering, this book provides a systematic overview of recent techniques, including requirement gathering in the form of story points in agile software, and bio-inspired techniques for estimating the effort, cost, and time required for software development. As such it is a valuable resource for new researchers interested in advances in software engineering ― particularly in the area of bio-inspired techniques.

✦ Table of Contents

Preface
Contents
1 SMDICFBA: Software Model for Distributed Incremental Closeness Factor Based Algorithms
1.1 Introduction
1.2 Literature Review
1.2.1 Closeness Factor Based Algorithm (CFBA)
1.3 Proposed Software Models for Distributed Incremental Closeness Factor Based Algorithms (SMDICFBAs)
1.3.1 Performance Evaluation of Proposed SMDICFBA
1.4 Conclusive Summary
References
2 A Novel Method for Fault Tolerance Intelligence Advisor System (FT-IAS) for Mission Critical Operations
2.1 Introduction
2.2 Implementation
2.2.1 Fault Tolerance Intelligence Advisor System (FT-IAS)
2.3 Algorithm
2.3.1 Proposed Algorithm: (Fault Tolerance Intelligence Advisor System During LEB Firing)
2.4 Simulation and Results
2.5 Conclusion and Future Work
References
3 Type-2 Fuzzy Controller (T2FC) Based Motion Planning of Differential-Drive Pioneer P3-DX Wheeled Robot in V-REP Software Platform
3.1 Introduction
3.2 Type-2 Fuzzy Controller (T2FC) for Steering Angle Control
3.3 Computer Simulation Results
3.4 Conclusion and Future Work
References
4 An Object-Oriented Software Complexity Metric for Cohesion
4.1 Introduction
4.2 Review of Literature
4.3 CohM—A Cohesion Complexity Metric
4.4 CohMmetric Calibration
4.5 Theoretical Validation of CohM
4.6 Conclusion
References
5 Engineering Full Stack IoT Systems with Distributed Processing Architecture—Software Engineering Challenges, Architectures and Tools
5.1 Introduction
5.2 Full Stack Development of IoT Applications
5.3 Requirements and Challenges of IoT Systems
5.4 Software Engineering Challenges of Developing Full Stack IoT Applications
5.5 Microservices Architectural Patterns for Distributed IoT System
5.5.1 Scale Cube
5.5.2 Event—Driven Architecture
5.5.3 Hexagonal Architecture
5.6 Tools for Microservices Implementation
5.6.1 Docker Containers for Service Deployment
5.6.2 Tools for Service Provisioning
5.7 Case Study: Smart Nutrition Monitoring System Based on Microservices Architecture
5.8 Conclusion
References
6 Chaos-Based Modified Morphological Genetic Algorithm for Effort Estimation in Agile Software Development
6.1 Introduction
6.2 Related Work
6.3 CMGA Process
6.3.1 Basic Principles of MNN
6.3.2 Basic Principles of DEP
6.4 Proposed Evolutionary DEP(CMGA) Process
6.4.1 Population Initialization by Chaotic Opposition (PICO) Based Learning Method
6.4.2 Evolutionary Learning Process
6.5 Evaluation Criteria
6.6 Simulations and Results
6.6.1 Zia Dataset
6.7 Conclusion and Future Work
References
7 PerbDroid: Effective Malware Detection Model Developed Using Machine Learning Classification Techniques
7.1 Introduction
7.2 Related Work
7.2.1 Research Questions
7.3 Data Set Description
7.4 Feature Selection Approaches
7.4.1 Chi-Squared Test
7.4.2 OneR Feature Evaluation
7.4.3 Gain Ratio Feature Evaluation
7.4.4 Information Gain Feature Evaluation
7.4.5 Logistic Regression Analysis
7.4.6 Principal Component Analysis (PCA)
7.5 Machine Learning Classifiers
7.6 Proposed Detection Framework
7.7 Parameters Used for Evaluation
7.8 Setup to Perform Experiment
7.9 Outcomes
7.9.1 Feature Ranking Approaches
7.9.2 Machine Learning Classifier
7.9.3 Comparison of Results
7.9.4 Evaluation of PerbDroid Using Detection Framework
7.9.5 Experimental Finding
7.9.6 Conclusion and Future Work
References
8 A Study on Application of Soft Computing Techniques for Software Effort Estimation
8.1 Introduction
8.2 Software Size Metrics
8.2.1 Lines Of Code (LOC)
8.2.2 Function Point Analysis (FPA)
8.2.3 Use Case Points (UCP)
8.2.4 Story Points
8.3 Effort Estimation Techniques
8.3.1 Expert-Based Estimation
8.3.2 Algorithmic-Based Estimation
8.3.3 Soft Computing Techniques
8.4 Effort Estimation Influencing Factors
8.5 Experimental Design
8.5.1 Evaluation Criteria
8.5.2 Datasets
8.5.3 Model Design
8.6 Conclusion
References
9 White Box Testing Using Genetic Algorithm—An Extensive Study
9.1 Introduction
9.2 Basic Concepts
9.2.1 Software Testing
9.3 Black Box Testing
9.4 White Box Testing
9.4.1 Coverage Based Testing
9.4.2 Fault Based Testing
9.5 Path Testing
9.5.1 Control Flow Graph (CFG)
9.5.2 Linearly Independent Path
9.5.3 Cyclomatic Complexity (CC)
9.6 Mutation Testing
9.7 Evolutionary Algorithms for Software Testing
9.7.1 Genetic Algorithm (GA) for Software Testing
9.8 Related Work
9.8.1 Test Case Generation and Optimization for Path Testing Using GA
9.8.2 Test Data Generation for Mutation Testing Using GA
9.9 Conclusion
References
10 Detection of Web Service Anti-patterns Using Machine Learning Framework
10.1 Introduction
10.2 Literature Survey
10.3 Research Background
10.3.1 Web Service Definition Language (WSDL)
10.3.2 Experimental Dataset
10.3.3 Source Code Metrics
10.3.4 Aggregation Measures
10.3.5 Proposed Framework for Feature Selection
10.3.6 Data Balancing Techniques
10.3.7 Classifier Algorithms
10.4 Proposed Methodology
10.5 Results and Comparative Analysis
10.5.1 Results
10.5.2 Comparative Analysis
10.6 Conclusion
References