1. Software Architecture Fundamentals

• 1.1. The Senses of “Architecture”
• 1.2. Stakeholders and Concerns
• 1.3. Uses of Architecture

2. Software Architecture Description

• 2.1. Architecture Views and Viewpoints
• 2.2. Architecture Patterns, Styles and Reference Architectures
• 2.3. Architecture Description Languages and Architecture Frameworks
• 2.4. Architecture as Significant Decisions

3. Software Architecture Process

• 3.1. Architecture in Context
• 3.1.1. Relation of Architecture to Design
• 3.2. Architectural Design
• 3.2.1. Architecture Analysis
• 3.2.2. Architecture Synthesis
• 3.2.3. Architecture Evaluation
• 3.3. Architecture Practices, Methods, and Tactics
• 3.4. Architecting in the Large

4. Software Architecture Evaluation

• 4.1. Goodness in Architecture
• 4.2. Reasoning about Architectures
• 4.3. Architecture Reviews
• 4.4. Architecture Metrics

1. Software Design Fundamentals

• 1.1. Design Thinking
• 1.2. Context of Software Design
• 1.3. Key Issues in Software Design
• 1.4. Software Design Principles

2. Software Design Processes

• 2.1. High-Level Design
• 2.2. Detailed Design

3. Software Design Qualities

• 3.1. Concurrency
• 3.2. Control and Event Handling
• 3.3. Data Persistence
• 3.4. Distribution of Components
• 3.5. Errors and Exception Handling, Fault Tolerance
• 3.6. Integration and Interoperability
• 3.7. Assurance, Security, and Safety
• 3.8. Variability

4. Recording Software Designs

• 4.1. Model-Based Design
• 4.2. Structural Design Descriptions
• 4.3. Behavioral Design Descriptions
• 4.4. Design Patterns and Styles
• 4.5. Specialized and Domain-Specific Languages
• 4.6. Design Rationale

5. Software Design Strategies and Methods

• 5.1. General Strategies
• 5.2. Function-Oriented (or Structured) Design
• 5.3. Data-Centered Design
• 5.4. Object-Oriented Design
• 5.5. User-Centered Design
• 5.6. Component-Based Design (CBD)
• 5.7. Event-Driven Design
• 5.8. Aspect-Oriented Design (AOD)
• 5.9. Constraint-Based Design
• 5.10. Other Methods

6. Software Design Quality Analysis and Evaluation

• 6.1. Design Reviews and Audits
• 6.2. Quality Attributes
• 6.3. Quality Analysis and Evaluation Techniques
• 6.4. Measures and Metrics
• 6.5. Verification, Validation, and Certification

1. Software Construction Fundamentals

• 1.1. Minimizing Complexity
• 1.2. Anticipating and Embracing Change
• 1.3. Constructing for Verification
• 1.4. Reusing Assets
• 1.5. Applying Standards in Construction

2. Managing Construction

• 2.1. Construction in Life Cycle Models
• 2.2. Construction Planning
• 2.3. Construction Measurement
• 2.4. Managing Dependencies

3. Practical Considerations

• 3.1. Construction Design
• 3.2. Construction Languages
• 3.3. Coding
• 3.4. Construction Testing
• 3.5. Reuse in Construction
• 3.6. Construction Quality
• 3.7. Integration
• 3.8. Cross-Platform Development and Migration

4. Construction Technologies

• 4.1. API Design and Use
• 4.2. Object-Oriented Runtime Issues
• 4.3. Parameterization, Templates, and Generics
• 4.4. Assertions, Design by Contract, and Defensive Programming
• 4.5. Error Handling, Exception Handling, and Fault Tolerance
• 4.6. Executable Models
• 4.7. State-Based and Table-Driven Construction Techniques
• 4.8. Runtime Configuration and Internationalization
• 4.9. Grammar-Based Input Processing
• 4.10. Concurrency Primitives
• 4.11. Middleware
• 4.12. Construction Methods for Distributed and Cloud-Based Software
• 4.13. Constructing Heterogeneous Systems
• 4.14. Performance Analysis and Tuning
• 4.15. Platform Standards
• 4.16. Test-First Programming
• 4.17. Feedback Loop for Construction

5. Software Construction Tools

• 5.1. Development Environments
• 5.2. Visual Programming and Low-Code/Zero-Code Platforms
• 5.3. Unit Testing Tools
• 5.4. Profiling, Performance Analysis, and Slicing Tools

1. Software Testing Fundamentals

• 1.1. Faults vs. Failures1.2. Key Issues
• 1.2.1. Test Case Creation
• 1.2.2. Test Selection and Adequacy Criteria
• 1.2.3. Prioritization/Minimization
• 1.2.4. Purpose of Testing
• 1.2.5. Assessment and Certification
• 1.2.6. Testing for Quality Assurance/Improvement
• 1.2.7. The Oracle Problem
• 1.2.8. Theoretical and Practical Limitations
• 1.2.9. The Problem of Infeasible Paths
• 1.2.10. Testability
• 1.2.11. Test Execution and Automation
• 1.2.12. Scalability
• 1.2.13. Test Effectiveness
• 1.2.14. Controllability, Replication, and Generalization
• 1.2.15. Off-Line vs. Online Testing
• 1.3. Relationship of Testing to Other Activities

2. Test Levels

• 2.1. The Target of the Test
• 2.1.1. Unit Testing
• 2.1.2. Integration Testing
• 2.1.3. System Testing
• 2.1.4. Acceptance Testing
• 2.2. Objectives of Testing
• 2.2.1. Conformance Testing
• 2.2.2. Compliance Testing
• 2.2.3. Installation Testing
• 2.2.4. Alpha and Beta Testing
• 2.2.5. Regression Testing
• 2.2.6. Prioritization Testing
• 2.2.7. Non-functional Testing
• 2.2.8. Security Testing
• 2.2.9. Privacy Testing
• 2.2.10. Interface and Application Program Interface (API) Testing
• 2.2.11. Configuration Testing
• 2.2.12. Usability and Human-Computer Interaction Testing

3. Test Techniques

• 3.1. Specification-Based Techniques
• 3.1.1. Equivalence Partitioning
• 3.1.2. Boundary-Value Analysis
• 3.1.3. Syntax Testing
• 3.1.4. Combinatorial Test Techniques
• 3.1.5. Decision Table
• 3.1.6. Cause-Effect Graphing
• 3.1.7. State Transition Testing
• 3.1.8. Scenario-Based Testing
• 3.1.9. Random Testing
• 3.1.10. Evidence-Based
• 3.1.11. Forcing Exception
• 3.2. Structure-Based Test Techniques
• 3.2.1. Control Flow Testing
• 3.2.2. Data Flow Testing
• 3.2.3. Reference Models for Structure-Based Test Techniques
• 3.3. Experience-Based Techniques
• 3.3.1. Error Guessing
• 3.3.2. Exploratory Testing
• 3.3.3. Further Experience-Based Techniques
• 3.4. Fault-Based and Mutation Techniques
• 3.5. Usage-Based Techniques
• 3.5.1. Operational Profile
• 3.5.2. User Observation Heuristics
• 3.6. Techniques Based on the Nature of the Application
• 3.7. Selecting and Combining Techniques
• 3.7.1. Combining Functional and Structural
• 3.7.2. Deterministic vs. Random
• 3.8. Techniques Based on Derived Knowledge

4. Test-Related Measures

• 4.1. Evaluation of the SUT
• 4.1.1. SUT Measurements that Aid in Planning and Designing Tests
• 4.1.2. Fault Types, Classification and Statistics
• 4.1.3. Fault Density
• 4.1.4. Life Test, Reliability Evaluation
• 4.1.5. Reliability Growth Models
• 4.2. Evaluation of the Tests Performed
• 4.2.1. Fault Injection
• 4.2.2. Mutation Score
• 4.2.3. Comparison and Relative Effectiveness of Different Techniques

5. Test Process

• 5.1. Practical Considerations
• 5.1.1. Attitudes/Egoless Programming
• 5.1.2. Test Guides and Organizational Process
• 5.1.3. Test Management and Dynamic Test Processes
• 5.1.4. Test Documentation
• 5.1.5. Test Team
• 5.1.6. Test Process Measures
• 5.1.7. Test Monitoring and Control
• 5.1.8. Test Completion
• 5.1.9. Test Reusability
• 5.2. Test Sub-Processes and Activities
• 5.2.1. Test Planning Process
• 5.2.2. Test Design and Implementation
• 5.2.3. Test Environment Set-up and Maintenance
• 5.2.4. Controlled Experiments and Test Execution
• 5.2.5. Test Incident Reporting
• 5.3. Staffing

6. Software Testing in the Development Processes and the Application Domains

• 6.1. Testing Inside Software Development Processes
• 6.1.1. Testing in Traditional Processes
• 6.1.2. Testing in Line with Shift-Left Movement
• 6.2. Testing in the Application Domains

7. Testing of and Testing Through Emerging Technologies

• 7.1. Testing of Emerging Technologies
• 7.2. Testing Through Emerging Technologies

8. Software Testing Tools

• 8.1. Testing Tool Support and Selection
• 8.2. Categories of Tools

1. Software Engineering Operations Fundamentals

• 1.1. Definition of Software Engineering Operations
• 1.2. Software Engineering Operations Processes
• 1.3. Software Installation
• 1.4. Scripting and Automating
• 1.5. Effective Testing and Troubleshooting
• 1.6. Performance, Reliability and Load Balancing

2. Software Engineering Operations Planning

• 2.1. Operations Plan and Supplier Management
• 2.1.1. Operations Plan
• 2.1.2. Supplier Management
• 2.2. Development and Operational Environments
• 2.3. Software Availability, Continuity, and Service Levels
• 2.4. Software Capacity Management
• 2.5. Software Backup, Disaster Recovery, and Failover
• 2.6. Software and Data Safety, Security, Integrity, Protection, and Controls

3. Software Engineering Operations Delivery

• 3.1. Operational Testing, Verification, and Acceptance
• 3.2. Deployment/Release Engineering
• 3.3. Rollback and Data Migration
• 3.4. Change Management
• 3.5. Problem Management

4. Software Engineering Operations Control

• 4.1. Incident Management
• 4.2. Monitor, Measure, Track, and Review
• 4.3. Operations Support
• 4.4. Operations Service Reporting

5. Practical Considerations

• 5.1. Incident and Problem Prevention
• 5.2. Operational Risk Management
• 5.3. Automating Software Engineering Operations
• 5.4. Software Engineering Operations for Small Organizations

6. Software Engineering Operations Tools

• 6.1. Containers and Virtualization
• 6.2. Deployment
• 6.3. Automated Test
• 6.4. Monitoring and Telemetry

1. Software Maintenance Fundamentals

• 1.1. Definitions and Terminology
• 1.2. Nature of Software Maintenance
• 1.3. Need for Software Maintenance
• 1.4. Majority of Maintenance Costs
• 1.5. Evolution of Software
• 1.6. Categories of Software Maintenance

2. Key Issues in Software Maintenance

• 2.1. Technical Issues
• 2.1.1. Limited Understanding
• 2.1.2. Testing
• 2.1.3. Impact Analysis
• 2.1.4. Maintainability
• 2.2. Management Issues
• 2.2.1. Alignment with Organizational Objectives
• 2.2.2. Staffing
• 2.2.3. Process
• 2.2.4. Supplier Management
• 2.2.5. Organizational Aspects of Maintenance
• 2.3. Software Maintenance Costs
• 2.3.1. Technical Debt Cost Estimation
• 2.3.2. Maintenance Cost Estimation
• 2.4. Software Maintenance Measurement

3. Software Maintenance Processes

• 3.1. Software Maintenance Processes
• 3.2. Software Maintenance Activities and Tasks
• 3.2.1. Supporting and Monitoring Activities
• 3.2.2. Planning Activities
• 3.2.3. Configuration Management
• 3.2.4. Software Quality

4. Software Maintenance Techniques

• 4.1. Program Comprehension
• 4.2. Software Reengineering
• 4.3. Reverse Engineering
• 4.4. Continuous Integration, Delivery, Testing, and Deployment
• 4.5. Visualizing Maintenance

5. Software Maintenance Tools

1. Management of the SCM Process

• 1.1. Organizational Context for SCM
• 1.2. Constraints and Guidance for the SCM Process
• 1.3. Planning for SCM
• 1.3.1. SCM Organization and Responsibilities
• 1.3.2. SCM Resources and Schedules
• 1.3.3. Tool Selection and Implementation
• 1.3.4. Vendor/Subcontractor Control
• 1.3.5. Interface Control
• 1.4. SCM Plan
• 1.5. Monitoring of Software Configuration Management
• 1.5.1. SCM Measures and Measurement
• 1.5.2. In-Process Audits of SCM

2. Software Configuration Identification

• 2.1. Identifying Items to Be Controlled
• 2.1.1. Software Configuration
• 2.1.2. Software Configuration Item
• 2.2. Configuration Item Identifiers and Attributes
• 2.3. Baseline Identification
• 2.4. Baseline Attributes
• 2.5. Relationships Scheme Definition
• 2.6. Software Libraries

3. Software Configuration Change Control

• 3.1. Requesting, Evaluating, and Approving Software Changes
• 3.1.1. Software Configuration Control Board
• 3.1.2. Software Change Request Process
• 3.1.3. Software Change Request Forms Definition
• 3.2. Implementing Software Changes
• 3.3. Deviations and Waivers

4. Software Configuration Status Accounting

• 4.1. Software Configuration Status Information
• 4.2. Software Configuration Status Reporting

5. Software Configuration Auditing

• 5.1. Software Functional Configuration Audit
• 5.2. Software Physical Configuration Audit
• 5.3. In-Process Audits of a Software Baseline

6. Software Release Management and Delivery

• 6.1. Software Building
• 6.2. Software Release Management

7. Software Configuration Management Tools

1. Initiation and Scope Definition

• 1.1. Determination and Negotiation of Requirements
• 1.2. Feasibility Analysis
• 1.3. Process for the Review and Revision of Requirements

2. Software Project Planning

• 2.1. Process Planning
• 2.2. Determine Deliverables
• 2.3. Effort, Schedule, and Cost Estimation
• 2.4. Resource Allocation
• 2.5. Risk Management
• 2.6. Quality Management
• 2.7. Plan Management

3. Software Project Execution

• 3.1. Implementation of Plans
• 3.2. Software Acquisition and Supplier Contract Management
• 3.3. Implementation of Measurement Process
• 3.4. Monitor Process
• 3.5. Control Process
• 3.6. Reporting

4. Review and Evaluation

• 4.1. Determining Satisfaction of Requirements
• 4.2. Reviewing and Evaluating Performance

5. Closure

• 5.1. Determining Closure
• 5.2. Closure Activities

6. Software Engineering Measurement

• 6.1. Establish and Sustain Measurement Commitment
• 6.2. Plan the Measurement Process
• 6.3. Perform the Measurement Process
• 6.4. Evaluate Measurement

7. Software Engineering Management Tools

1. Software Engineering Process Fundamentals

• 1.1. Introduction
• 1.2. Software Engineering Process Definition

2. Life Cycles

• 2.1. Life Cycle Definition, Process Categories, and Terminology
• 2.2. Rationale for Life Cycles
• 2.3. The Concepts of Process Models and Life Cycle Models
• 2.4. Some Paradigms for Development Life Cycle Models
• 2.5. Development Life Cycle Models and Their Engineering Dimension
• 2.6. The Management of SLCPs
• 2.7. Software Engineering Process Management
• 2.8. Software Life Cycle Adaptation
• 2.9. Practical Considerations
• 2.10. Software Process Infrastructure, Tools, Methods
• 2.11. Software Engineering Process Monitoring and its Relationship with the Software Product

3. Software Process Assessment and Improvement

• 3.1. Overview of Software Process Assessment and Improvement
• 3.2. Goal-Question-Metric (GQM)
• 3.3. Framework-Based Methods
• 3.4. Process Assessment and Improvement in Agile

1. Modeling

• 1.1. Modeling Principles
• 1.2. Properties and Expression of Models
• 1.3. Syntax, Semantics, and Pragmatics
• 1.4. Preconditions, Postconditions, and Invariants

2. Types of Models

• 2.1. Structural Modeling
• 2.2. Behavioral Modeling

3. Analysis of Models

• 3.1. Analyzing for Completeness
• 3.2. Analyzing for Consistency
• 3.3. Analyzing for Correctness
• 3.4. Analyzing for Traceability
• 3.5. Analyzing for Interaction

4. Software Engineering Methods

• 4.1. Heuristic Methods
• 4.2. Formal Methods
• 4.3. Prototyping Methods
• 4.4. Agile Methods

1. Software Quality Fundamentals

• 1.1. Software Engineering Culture and Ethics
• 1.2. Value and Costs of Quality
• 1.3. Standards, Models, and Certifications
• 1.4. Software Dependability and Integrity Levels
• 1.4.1. Dependability
• 1.4.2. Integrity Levels of Software

2. Software Quality Management Process

• 2.1. Software Quality Improvement
• 2.2. Plan Quality Management
• 2.3. Evaluate Quality Management
• 2.3.1. Software Quality Measurement
• 2.4. Perform Corrective and Preventive Actions
• 2.4.1. Defect Characterization

3. Software Quality Assurance Process

• 3.1. Prepare for Quality Assurance
• 3.2. Perform Process Assurance
• 3.3. Perform Product Assurance
• 3.4. V&V and Testing
• 3.4.1. Static Analysis Techniques
• 3.4.2. Dynamic Analysis Techniques
• 3.4.3. Formal Analysis Techniques
• 3.4.4. Software Quality Control and Testing
• 3.4.5. Technical Reviews and Audits

4. Software Quality Tools

1. Software Security Fundamentals

• 1.1. Software Security
• 1.2. Information Security
• 1.3. Cybersecurity

2. Security Management and Organization

• 2.1. Capability Maturity Model
• 2.2. Information Security Management System
• 2.3. Agile Practice for Software Security

3. Software Security Engineering and Processes

• 3.1. Security Engineering and Secure Development Life Cycle (SDLC)
• 3.2. Common Criteria for Information Technology Security Evaluation

4. Security Engineering for Software Systems

• 4.1. Security Requirements
• 4.2. Security Design
• 4.3. Security Patterns
• 4.4. Construction for Security
• 4.5. Security Testing
• 4.6. Vulnerability Management

5. Software Security Tools

• 5.1. Security Vulnerability Checking Tools
• 5.2. Penetration Testing Tools

6. Domain-Specific Software Security

• 6.1. Security for Container and Cloud
• 6.2. Security for IoT Software
• 6.3. Security for Machine Learning-Based

1. Professionalism

• 1.1. Accreditation, Certification and Qualification, and Licensing
• 1.1.1. Accreditation
• 1.1.2. Certification and Qualification
• 1.1.3. Licensing
• 1.2. Codes of Ethics and Professional Conduct
• 1.3. Nature and Role of Professional Societies
• 1.4. Nature and Role of Software Engineering Standards
• 1.5. Economic Impact of Software
• 1.6. Employment Contracts
• 1.7. Legal Issues
• 1.7.1. Standards
• 1.7.2. Trademarks
• 1.7.3. Patents
• 1.7.4. Copyrights
• 1.7.5. Trade Secrets
• 1.7.6. Professional Liability
• 1.7.7. Legal Requirements
• 1.7.8. Trade Compliance
• 1.7.9. Cybercrime
• 1.7.10. Data Privacy
• 1.8. Documentation
• 1.9. Trade-Off Analysis

2. Group Dynamics and Psychology

• 2.1. Dynamics of Working in Teams/Groups
• 2.2. Individual Cognition
• 2.3. Dealing with Problem Complexity
• 2.4. Interacting with Stakeholders
• 2.5. Dealing with Uncertainty and Ambiguity
• 2.6. Dealing with Equity, Diversity, and Inclusivity

3. Communication Skills

• 3.1. Reading, Understanding, and Summarizing
• 3.2. Writing
• 3.3. Team and Group Communication
• 3.4. Presentation Skills

1. Software Engineering Economics Fundamentals

• 1.1. Proposals
• 1.2. Cash Flow
• 1.3. Time-Value of Money
• 1.4. Equivalence
• 1.5. Bases for Comparison
• 1.6. Alternatives
• 1.7. Intangible Assets
• 1.8. Business Model

2. The Engineering Decision-Making Process

• 2.1. Process Overview
• 2.2. Understand the Real Problem
• 2.3. Identify All Reasonable Technically Feasible Solutions
• 2.4. Define the Selection Criteria
• 2.5. Evaluate Each Alternative Against the Selection Criteria
• 2.6. Select the Preferred Alternative
• 2.7. Monitor the Performance of the Selected Alternative

3. For-Profit Decision-Making

• 3.1. Minimum Acceptable Rate of Return
• 3.2. Economic Life
• 3.3. Planning Horizon
• 3.4. Replacement Decisions
• 3.5. Retirement Decisions
• 3.6. Advanced For-Profit Decision Considerations

4. Nonprofit Decision-Making

• 4.1. Benefit-Cost Analysis
• 4.2. Cost-Effectiveness Analysis

5. Present Economy Decision-Making

• 5.1. Break-Even Analysis
• 5.2. Optimization Analysis

6. Multiple-Attribute Decision-Making

• 6.1. Compensatory Techniques
• 6.2. Non-Compensatory Techniques

7. Identifying and Characterizing Intangible Assets

• 7.1. Identify Processes and Define Business Goals
• 7.2. Identify Intangible Assets Linked with Business Goal
• 7.3. Identify Software Products That Support Intangible Assets
• 7.4. Define and Measure Indicators
• 7.5. Intangible Asset Characterization
• 7.6. Link Specific Intangible Assets with the Business Model
• 7.7. Decision-Making

8. Estimation

• 8.1. Expert Judgment
• 8.2. Analogy
• 8.3. Decomposition
• 8.4. Parametric
• 8.5. Multiple Estimates

9. Practical Considerations

• 9.1. Business Case
• 9.2. Multiple-Currency Analysis
• 9.3. Systems Thinking

10. Related Concepts

• 10.1. Accounting
• 10.2. Cost and Costing
• 10.3. Finance
• 10.4. Controlling
• 10.5. Efficiency and Effectiveness
• 10.6. Productivity
• 10.7. Product or Service
• 10.8. Project
• 10.9. Program
• 10.10. Portfolio
• 10.11. Product Life Cycle
• 10.12. Project Life Cycle
• 10.13. Price and Pricing
• 10.14. Prioritization

1. Basic Concepts of a System or Solution

2. Computer Architecture and Organization

• 2.1. Computer Architecture
• 2.2. Types of Computer Architectures
• 2.2.1. Von Neumann Architecture
• 2.2.2. Harvard Architecture
• 2.2.3. Instruction Set Architecture
• 2.2.4. Flynn’s Architecture or Taxonomy
• 2.2.5. System Architecture
• 2.3. Microarchitecture or Computer Organization
• 2.3.1. Arithmetic Logic Unit
• 2.3.2. Memory Unit
• 2.3.3. Input/Output Devices
• 2.3.4. Control Unit

3. Data Structures and Algorithms

• 3.1. Types of Data Structures
• 3.2. Operations on Data Structures
• 3.3. Algorithms and Attributes of Algorithms
• 3.4. Algorithm Complexity
• 3.5. Measurement of Complexity
• 3.6. Designing Algorithms
• 3.7. Sorting Techniques
• 3.8. Searching Techniques
• 3.9. Hashing

4. Programming Fundamentals and Languages

• 4.1. Programming Language Types
• 4.2. Programming Syntax, Semantics, Type Systems
• 4.3. Subprograms and Coroutines
• 4.4. Object-Oriented Programming
• 4.5. Distributed Programming and Parallel Programming
• 4.6. Debugging
• 4.7. Standards and Guidelines

5. Operating Systems

• 5.1. Processor Management
• 5.2. Memory Management
• 5.3. Device Management
• 5.4. Information Management
• 5.5. Network Management

6. Database Management

• 6.1. Schema
• 6.2. Data Models and Storage Models
• 6.3. Database Management Systems
• 6.4. Relational Database Management Systems and Normalization
• 6.5. Structured Query Language
• 6.6. Data Mining and Data Warehousing
• 6.7. Database Backup and Recovery

7. Computer Networks and Communications

• 7.1. Types of Computer Networks
• 7.2. Layered Architectures of Networks
• 7.3. Open Systems Interconnection Model
• 7.4. Encapsulation and Decapsulation
• 7.5. Application Layer Protocols
• 7.6. Design Techniques for Reliable and Efficient Network
• 7.7. Internet Protocol Suite
• 7.8. Wireless and Mobile Networks
• 7.9. Security and Vulnerabilities

8. User and Developer Human Factors

• 8.1. User Human Factors
• 8.2. Developer Human Factors

9. Artificial Intelligence and Machine Learning

• 9.1. Reasoning
• 9.2. Learning
• 9.3. Models
• 9.4. Perception and Problem-Solving
• 9.5. Natural Language Processing
• 9.6. AI and Software Engineering

1. Basic Logic

• 1.1. Propositional Logic
• 1.2. Predicate Logic

2. Proof Techniques

• 2.1. Direct Proof
• 2.2. Proof by Contradiction
• 2.3. Proof by Induction
• 2.4. Proof by Example

3. Set, Relation, Function

• 3.1. Set Operations
• 3.2. Properties of Sets
• 3.3. Relation and Function

4. Graph and Tree

• 4.1. Graph
• 4.2. Tree

5. Finite-State Machine

6. Grammar

• 6.1. Language Recognition

7. Number Theory

• 7.1. Types of Numbers
• 7.2. Divisibility
• 7.3. Prime Number
• 7.4. Greatest Common Divisor

8. Basics of Counting

9. Discrete Probability

10. Numerical Precision, Accuracy, and Error

11. Algebraic Structures

• 11.1. Group
• 11.2. Ring

12. Engineering Calculus

13. New Advancements

• 13.1. Computational Neurosciences
• 13.2. Genomics

1. The Engineering Process

2. Engineering Design

• 2.1. Engineering Design in Engineering Education
• 2.2. Design as a Problem-Solving Activity

3. Abstraction and Encapsulation

• 3.1. Levels of Abstraction
• 3.2. Encapsulation
• 3.3. Hierarchy
• 3.4. Alternate Abstractions

4. Empirical Methods and Experimental Techniques

• 4.1. Designed Experiment
• 4.2. Observational Study
• 4.3. Retrospective Study

5. Statistical Analysis

• 5.1. Unit of Analysis (Sampling Units), Population, and Sample
• 5.2. Correlation and Regression

6. Modeling, Simulation, and Prototyping

• 6.1. Modeling
• 6.2. Simulation
• 6.3. Prototyping

7. Measurement

• 7.1. Levels (Scales) of Measurement
• 7.2. Implications of Measurement Theory for Programming Languages
• 7.3. Direct and Derived Measures
• 7.4. Reliability and Validity
• 7.5. Assessing Reliability
• 7.6. Goal-Question-Metric Paradigm: Why Measure?

8. Standards

9. Root Cause Analysis

• 9.1. Root Cause Analysis Techniques
• 9.2. Root Cause–Based Improvement

10. Industry 4.0 and Software Engineering