Knowledge-Based Software Engineering: 2022: Proceedings of the 14th International Joint Conference on Knowledge-Based Software Engineering

✍ Scribed by Maria Virvou, Takuya Saruwatari, Lakhmi C. Jain

• Publisher: Springer
• Year: 2023
• Tongue: English
• Leaves: 219
• Series: Learning and Analytics in Intelligent Systems, 30
• Category: Library

✦ Synopsis

This book contains extended versions of  the works and new research results presented at the 14^th International Joint Conference on Knowledge-based Software Engineering (JCKBSE2022). JCKBSE2022 was originally planned to take place in Larnaca, Cyprus. Unfortunately, the COVID-19 pandemic forced it to be rescheduled as an online conference.

 

JCKBSE is a well-established international biennial conference that focuses on the applications of Artificial Intelligence on Software Engineering. The 14^th International Joint Conference on Knowledge-based Software Engineering (JCKBSE2022) was organized by the Department of Informatics of the University of Piraeus, Greece.

 

This book is a valuable resource for experts and researchers in the field of (knowledge-based) software engineering. It is also valuable to general readers in the fields of artificial and computational intelligence and, more generally, computer science, wishing to learn more about the exciting field of (knowledge-based) software engineering and its applications. An extensive list of bibliographic references at the end of each chapter helps readers to probe deeper into the application areas of interest to them.

✦ Table of Contents

Preface
Artificial Intelligence as Dual Use Technology
Attacks in Android Mobile User Interfaces Exposing User Privacy and Personal Data
Contents
Part I Software Development Techniques and Tools
1 Proposal of a Middleware to Support Development of IoT Firmware Analysis Tools
1.1 Introduction
1.1.1 Background
1.1.2 Contribution
1.2 Characterization of Firmware Vulnerability Detection Methods
1.2.1 Categorization of Features
1.2.2 Research on Firmware Vulnerability Analysis
1.2.3 Result
1.3 Our Approach
1.3.1 Firmware Splitting
1.3.2 Static Strings
1.3.3 Control Flow Graph
1.3.4 Identifying Network Functions
1.4 Conclusions and Future Work
References
2 Feature-Based Cloud Provisioning for Rehosting
2.1 Introduction
2.2 Motivating Examples
2.2.1 Trial-and-Error Searches for Optimal Cloud Service Configuration in Design Process
2.2.2 Manual Provisioning with Console Used by Engineers in Construction Process
2.3 Feature-Based Cloud Provisioning Method for Rehosting
2.3.1 Overview of Proposed Method
2.3.2 Cloud Feature Model
2.3.3 Cloud Provisioning Tool
2.4 Evaluation
2.4.1 Evaluation Method
2.4.2 Results
2.5 Discussion
2.5.1 Effects of Application to Design Process
2.5.2 Effects of Application to Construction Process
2.6 Related Work
2.7 Conclusion
References
3 Pattern to Improve Reusability of Numerical Simulation
3.1 Introduction
3.2 Background
3.2.1 Modelica Language
3.2.2 Adopting Design Patterns to Modelica
3.3 Patterns for Physical Modeling and Their Adaptation
3.4 Case Study
3.4.1 Moving Ball
3.4.2 SIR Model
3.5 Conclusions
References
4 SpiderTailed: A Tool for Detecting Presentation Failures Using Screenshots and DOM Extraction
4.1 Introduction
4.2 Proposed Method
4.2.1 Take Screenshots
4.2.2 Extract Visual Properties
4.2.3 Comparison of Visual Properties
4.2.4 Output of Comparison Results
4.3 Implementation
4.3.1 Take Screenshots Function
4.3.2 Extract Visual Properties Function
4.3.3 Comparison of Visual Properties Function
4.3.4 Comparison Results Output Function
4.4 Evaluation
4.4.1 Preparing Web Page for Evaluation
4.4.2 Establishment of Evaluation Criteria
4.4.3 Experiment: 1 Evaluation of SpiderTailed
4.4.4 Experiment: 2 Evaluation of Manual Observation
4.5 Results and Discussion
4.5.1 RQ1: What Are the Strengths of SpiderTailed Compared to the Manual Observation
4.5.2 RQ2: Comparison of the Time Consumption
4.5.3 RQ3: Challenges of the SpiderTailed Method
4.6 Related Work
4.7 Limitations and Validity
4.7.1 Limitations
4.7.2 Validity
4.8 Conclusion
References
Part II AI/ML-Based Software Development
5 Collecting Insights and Developing Patterns for Machine Learning Projects Based on Project Practices
5.1 Introduction
5.2 Related Work
5.3 Research Subject and Hypothesis
5.3.1 ML-based Service System
5.3.2 Architecture Design Pattern for ML Service Systems
5.3.3 Research Hypothesis
5.4 Proposed Method
5.4.1 Overview
5.4.2 Reference Development Model and Collection of Insights
5.4.3 Construction of Patterns from Collected Insights
5.5 Practice
5.6 Discussion
5.7 Conclusions
References
6 Supporting Code Review by a Neural Network Using Program Images
6.1 Introduction
6.2 Related Work
6.3 CNN-BI System
6.3.1 Training Method and the Training Data
6.3.2 Preparing the Learning Data
6.3.3 Check List
6.4 Experimental Study
6.4.1 Overview
6.4.2 Applying Supervised Learning
6.4.3 Visualization of the Training
6.4.4 Verification of the Categorization
6.4.5 Types of Defects Inferred
6.4.6 Review Process
6.4.7 Result
6.5 Discussion
6.5.1 The Answer to RQ1
6.5.2 The Answer to RQ2
6.5.3 Internal Validity
6.5.4 External Validity
6.6 Conclusion
References
7 Safety and Risk Analysis and Evaluation Methods for DNN Systems in Automated Driving
7.1 Introduction
7.2 Related Work
7.2.1 Machine Learning Systems Engineering and Safety
7.2.2 Safety Guidelines and Research Trends for Automated Driving
7.2.3 Model and STAMP and Related Methods
7.3 Safety Challenges for Machine Learning Systems
7.3.1 Safety Challenges of Automated Driving
7.3.2 The “Question” that Forms the Core of the Research
7.3.3 Research Goals
7.4 Proposal of Safety and Risk Analysis and Evaluation Methods for DNN Systems
7.4.1 Step 1: System-level Safety Analysis
7.4.2 Step 2: Scenario and Training Data Generation for High-Risk Scenes
7.4.3 Step 3: DNN Design Modeling and Problem Analysis
7.4.4 Step 4: Design Labels with Safety in Mind
7.4.5 Step 5: Model Evaluation by Risk
7.4.6 Step 6: Setting Evaluation Criteria
7.4.7 Step 7: Model Improvement Through Debugging and Modification Techniques
7.5 Safety Arguments and Case Studies
7.5.1 Safety Arguments for DNN Safety Analysis and Assessment Methodology
7.5.2 Embodiment of Steps 1–3
7.6 Conclusion
References
8 Regulation and Validation Challenges in Artificial Intelligence-Empowered Healthcare Applications—The Case of Blood-Retrieved Biomarkers
8.1 Introduction
8.2 Key Issues and Challenges
8.2.1 Biomarkers
8.2.2 Automating Interventions and Patient's Journey
8.2.3 The Importance of Regulation
8.2.4 Validation of Neural Networks in Health Applications and Continuous Integration
8.2.5 The Role of Machine Learning in Health Care
8.3 Related Work
8.4 Building a Blood Exam-Based Personalised Recommender System
8.4.1 Development Methodologies
8.5 Conclusion and Research Key Findings
References
Part III Educational and Assistive Software
9 Multi-agent Simulation for Risk Prediction in Student Projects with Real Clients
9.1 Introduction
9.2 Software Development Project Course with Real Clients
9.3 Multi-agent Model of Student Projects
9.3.1 NetLogo
9.3.2 Student Project Model
9.3.3 Dependencies Among Tasks in a Project
9.3.4 Task Allocation to Project Members
9.3.5 Members’ Skill and Performance
9.3.6 Risk Prediction by Simulating in Our Model
9.4 Simulation Results
9.5 Questionnaire Survey
9.6 Related Work
9.7 Conclusion and Future Works
References
10 Automatic Scoring in Programming Examinations for Beginners
10.1 Introduction
10.2 Preliminaries
10.2.1 Presburger Arithmetic
10.2.2 Notation
10.3 Proposed Methods
10.3.1 Programming Language
10.3.2 Program Verification
10.3.3 Automatic Scoring
10.3.4 Examination System
10.4 Experiments
10.4.1 Count
10.4.2 Bubble Sort
10.4.3 Binary Search
10.5 Discussion
10.6 Conclusion
References
11 A Study on Analyzing Learner Behaviors in State Machine Modeling Using Process Mining and Statistical Test
11.1 Introduction
11.2 Theoretical Background
11.2.1 State Machine Model
11.2.2 Model Log
11.2.3 Event Log
11.2.4 Process Mining
11.2.5 Identification of Different Activity and Transition
11.3 Method
11.3.1 Activity and Transition Extraction
11.3.2 Difference Identification
11.4 Experiment
11.4.1 Modeling Task and Answers
11.4.2 Result
11.4.3 Consideration
11.5 Related Work
11.6 Conclusion
References
12 Supporting Conveyance of Webpages by Highlighting Text for Visually Impaired Persons
12.1 Introduction
12.2 Related Work
12.3 Emphasis Expressions in this Research
12.4 Outline of Our Method
12.4.1 Approach of Our Method
12.4.2 Structure of Our Method
12.5 Deciding the Reading Voice for Emphasized Expressions
12.5.1 Weighting of Text
12.5.2 Weighting of Voice
12.5.3 Determination of the Reading Method
12.6 Evaluation
12.6.1 Experimental Design
12.6.2 Results
12.6.3 Discussion
12.7 Conclusion
References
Part IV Requirements Analysis and Software Modeling
13 Comparative Study on Functional Resonance Matrices
13.1 Introduction
13.2 Related Work
13.2.1 Fram
13.2.2 FRAM Matrix Representation
13.2.3 Matrix Representation
13.3 Functional Aspect Resonance Matrix
13.4 Comparative Study on Matrix Representations
13.5 Discussion
13.5.1 Novelty
13.5.2 Effectiveness
13.5.3 Computational Cost
13.5.4 Limitations
13.6 Summary
References
14 A Method for Matching Patterns Based on Event Semantics with Requirements
14.1 Introduction
14.2 Related Work
14.3 Proposed Method
14.3.1 Characteristic Semantic Representation
14.4 Experimental Pattern Matching
14.5 Conclusions
References
15 Digital SDGs Framework Towards Knowledge Integration
15.1 Introduction
15.2 Related Work
15.2.1 SDGs
15.2.2 Dx
15.2.3 Knowledge Integration
15.3 Issues
15.4 DSDG Framework
15.4.1 Classification of SDGs in Enterprises
15.4.2 DSDG Strategy Map
15.4.3 DSDG Framework
15.4.4 SDGsVCM
15.5 Case Study
15.5.1 DSDG Strategy Map
15.5.2 DSDG Framework
15.5.3 SDGsVCM
15.6 Discussion
15.7 Summary
References
16 Hierarchical User Review Clustering Based on Multiple Sub-goal Generation
16.1 Introduction
16.2 Relevant Work
16.3 The Existing Clustering Method
16.3.1 Ward Method
16.4 Comprehensive Clustering Method
16.4.1 LDA Topic Model
16.4.2 The Distance-Based Clustering Algorithm
16.5 Experiment and Evaluation
16.5.1 Purpose of Experiments
16.5.2 Experiment and Discussion
16.6 Conclusion
References