Architectural Software Engineering
for Systems Engineers (+ AI tools)בהנחה לחברי האיגוד

Course Objectives
The objectives of this course are to provide systems engineers with essential tools and a common language for their work in environments rich with modern software systems, and to show how modern AI tools (LLMs and generative AI assistants) can support the day-to-day work of systems engineers - from use cases and UML diagrams to architecture definition and documentation.
Software development is a core component in every modern system, whether it be large multidisciplinary systems or small IoT devices embedded in products. Today, software development is integral to the development lifecycle of every project and product.
This course will explore various types of architectural software systems and products (Embedded, SaaS, AI/ML, etc.), methodologies, tools, and standard architectures, along with presenting practical case studies and equipping participants with the necessary tools.

Detailed Outline
 
Day 1 – With Gil
Part 1 - Core Syllabus
·        New Course Methodology – Dr. Moshe Weiler
·        Course outline
·        Intro to Software Engineering vs Systems Engineering
·        Software Product types
·        Modern development life cycle
·        Methodologies – V model, Waterfall, Agile, SCRUM
·        DevOps and CICD intro
·        Architecture types
·        Day 1 summary (KPIs) and briefing for day 2
Practice
·        Preparations to rolling exercise
·        Teams' selection for exercises 
·        Breakout Rooms tutorial and testing
·        Minor exercise in Breakout Rooms 
Rolling exercise for days 1-4
Corny
Goal/MRD - building a corn field monitoring and yield prediction application for US farmers for optimizing yield and cost reduction.
This is a HW-SW mixed system, for extra challenge for system engineers, but the focus is on the SW architecture design, supported by modern AI/LLM tools.
The HW selection will be given in advance by the course staff or might be free to choose from the students - TBD (e.g.: sensors, drones, etc.).
 
Day 2 – With Daniel
Part 2 - Core Syllabus
·        Day 1 Recap
·        Use Case Mapping
·        Use Case Analysis
·        Activity Diagrams
·        Using LLMs to generate and review Use Cases and Activity Diagrams
·        Day 2 summary (KPIs)
 
Practice
·        Breakout Rooms Exercise ~ 30-45 min:
o   Use Case and Activity Diagrams

AI in the modern SE workflow:
·        SE workflow before and after AI/LLM tools - from a system's architect POV
o   Practical examples of “assistant tools” (minor impact)
o   Practical examples of “strategic tools” (major impact)
·        Building modern Engineering Teams using “Strategic Value” tools like Copilot, AI for testing and automation
 
Day 3 – With Daniel
Part 3 - Core Syllabus
·               Day 2 Recap
·               Activity Diagrams cont.
·               Sequence Diagrams
·               Using LLMs to build and validate Sequence Diagrams - modern alternatives for classic UML tools
·               Day 3 summary (KPIs)
 
Practice
Exercise Breakout Rooms
·        Activity and Sequence Diagrams for the rolling exercise (Corny)
 
Day 4 – With Daniel
Part 4 - Core Syllabus
·        Day 3 Recap
·        ICD building
·        Interfaces, SOLID
·        API architectures, types and selection
·        Architecture types and topologies - deep dive (Event Driven, Micro Services, Tiers, Layered, Client-Server)
·        Demonstrating how choosing a physical design is an enabler for SW architecture types and implied interfaces
·        Application design - low level, main, web back end, web front end, UI and UX
·        Using LLMs for ICD drafting and API definitions
·        Days 2-4 summary (KPIs)
 
Practice
Exercise Breakout Rooms
·        Sequence Diagrams, ICD and Architecture types
 
Day 5 – With Gil
Part 5 - Advanced Topics
·        Virtualization and Scale - Docker, Containers, Cloud based tools
·        Cloud Services
·        Modern visualization tools as a concept
·        Data flow in a system - Understanding data types, database types and selection - from the system's architect POV
·        SDLC - Modern security standards and practices - cyber-attacks and concepts, cryptography management, secure boot, supply chain security, various attack vectors and mitigation, data plane and control plane concepts
·        Team's Ownership and Best Practices - building creativity and ownership by utilizing SWE and AGILE methodologies and frameworks
·        AI for systems engineers - practical LLM usage across the development life cycle (requirements, diagrams, documentation, code comprehension, testing and automation)
·        Day 5 summary (KPIs) and briefing for the final exercise
Practice
Exercise Breakout Rooms
·        Teams' preparation for the final exercise
 
Day 6 – With Gil
Part 6 - Final Exercise (course summary)
All teams practice the full design flow in Breakout Rooms and present their results to the class.
AiCart
Goal/MRD - building a retail targeted product that transforms any existing retail business to the AI era, both customers/users and the organization.
Exercise guided outline:
·        What is the “Goal” / “Vision” of the product?
·        What are the Use Cases?
·        Who are the users?
·        Who are the major “Actors” in the system?
·        Build a Use-Case Diagram with all the components
·        How does the data look (structure, scale, format, consistency, etc.)
·        What is the general data flow in the system?
·        Build a Sequence Diagram for the main Use-Case
·        SW architecture alternatives
·        SW architecture Selection
·        What is the application topology?
·        Which AI capabilities does the product need and how do they affect the architecture?
·        Where can LLM tools accelerate the design and documentation work?
How can the system scale?