Hardware-bound software
Resources, peripherals and physical consequences are part of the software problem.
Course foundations: what embedded software is, why physical effects change engineering, and how product and service business models frame the work.
Resources, peripherals and physical consequences are part of the software problem.
Functional safety treats unintended faults; cybersecurity treats intentional hostile actions.
Product companies own market/product risk; service companies sell engineering capability.
Confidentiality and ownership must be read from actual agreements, not assumed.
Embedded engineering is a coupled technical-and-business system: hardware, verification, ownership and delivery constraints shape the software from day one.
The complete English academic notes follow the Ukrainian source, retaining the original argument, engineering examples, terminology, diagrams, tasks and editorial qualifications. The original transcripts remain available separately in Ukrainian.
Chronology: 1 September 2026 · course opening. Primary source: the complete automatic transcript. Status: reconstructed from the original recording and frozen on 28 September 2026.
This course is concerned less with programming-language syntax or algorithm theory than with the entire engineering and business lifecycle of an embedded project. The ambition stated in the lecture is to follow the journey from an idea to initial revenue, through routine delivery work and eventually to completion of the project or business.
The course's central framework:
idea
↓
definition of the need
↓
customer / market / funding
↓
team + processes + deliverables
↓
embedded-system development
↓
verification / validation / integration
↓
delivery / support / closure
Assessment is based on a team project and demonstrations, not merely on reproducing theory. Students organize into teams themselves; the roles and deliverables of those teams will evolve as the course progresses.
The practical characteristic of embedded software is that it is designed for a particular hardware environment and forms part of a physical product or system. Beyond program functions, memory, computational resources, energy consumption, peripherals, interfaces, timing characteristics and the physical consequences of an error are all important.
The lecture contrasts two common topologies.
For relatively small MCU designs, application logic may operate directly on top of the vendor's HAL or driver layer.
Application / business logic
↓
HAL + low-level drivers
↓
MCU / DSP / SoC / another target
Advantages include a smaller stack, controlled resource use and predictability. The trade-off is tighter coupling to the target and the need to implement more infrastructural functionality yourself.
In larger systems, reusing existing networking, filesystem, diagnostics and other services may be appropriate.
Application
↓
Middleware / services
↓
Operating system / runtime
↓
HAL / drivers
↓
Hardware
This does not automatically make the system “better”. It is another trade-off: greater reuse and flexibility, but also a more complex software stack, integration, update and security attack surfaces, and more interdependencies.
The code ultimately affects the physical world: it generates electrical signals, controls actuators and exchanges data over physical interfaces. Consequently, a defect may manifest not merely as incorrect on-screen text but as:
The lecture's central claim follows: high-quality embedded development is inseparable from testing, systems engineering and risk management.
The lecture introduces two different sources of unwanted behavior:
| Dimension | What happened | Typical question |
|---|---|---|
| Functional safety | a random failure or defect puts the system into a hazardous state | “What happens if a component fails?” |
| Cybersecurity | an actor deliberately attempts to alter behavior or gain unauthorized access | “What could an attacker do, and how do we limit it?” |
These fields interact but cannot substitute for one another.
The spoken formulation in the lecture was broader than the standard's actual scope. ISO 26262 is a functional-safety standard for electrical/electronic systems in series-production road vehicles. Industrial, aerospace, railway, medical and other domains have their own applicable standards; ISO 26262 is not a universal baseline for every safety-critical industry.
Official source: https://www.iso.org/standard/68385.html
Automotive ISO 26262 uses QM and ASIL A–D. The ASIL resulting from HARA is not calculated by simply multiplying “probability × consequence”. Classification involves the combination of Severity, Exposure and Controllability. The detailed method should be studied in ISO 26262-3 itself.
For cybersecurity engineering throughout the automotive E/E lifecycle, the domain-specific reference is ISO/SAE 21434: https://www.iso.org/standard/70918.html.
The lecture presents a business in terms of two necessary ingredients:
IDEA + RESOURCES → TECHNOLOGY → VALUE FOR THE MARKET
An idea alone does not guarantee a product. People, time, money, equipment, manufacturing, marketing, legal/IP work, testing and market access are needed. Money is a convenient general representation of resources, but it is not the only resource.
A team develops its own product idea and assumes the associated market risk: what to build, for whom, how to protect IP, how to scale manufacturing and how to support the product.
A customer has a business or technical need but obtains external engineering capacity. A service company provides people, processes, infrastructure, domain expertise and sometimes hardware or manufacturing capability, receiving payment under an agreed engagement model.
| Question | Product | Service |
|---|---|---|
| Who defines the market idea? | product owner | customer |
| Who finances engineering? | owner / investor | customer, under contract |
| Principal risk | product–market fit + engineering | delivery + commercial + reputational |
| Principal asset | product / IP / brand / distribution channels | expertise / delivery capability / reputation |
| What is sold? | a product or licence | engineering services / project deliverables |
The course deliberately starts with the service model because it offers access to real processes—lead generation, pre-sales, proposal, staffing and delivery—before moving to the product model.
The lecture stresses two practical constraints on service engagements: confidentiality and the rights to work products.
The correct expansion is Non-Disclosure Agreement, not “Not Discussion Agreement”. An NDA defines obligations not to disclose confidential information; its actual limits depend on the agreement's wording and the applicable law.
The claim that “IP in a service company always belongs to the customer” describes a common business arrangement, not a universal legal rule. Ownership, assignments, licences, background IP, foreground IP and rights of reuse depend on the contract and applicable law. These provisions must be read in MSA, SOW and IP clauses rather than inferred from the mere fact of outsourcing.
The lecture offers a personal perspective: it is helpful first to acquire experience on real service projects, observe strong and weak processes, and learn to work with customers and risks. Then, once an idea and sufficient resources are available, one can move toward developing a proprietary product.
This is the lecturer's career advice, not a single universally required path.
Describe one embedded-system idea in two arrangements:
For each arrangement, identify the owner of the idea, who bears the risk, the funding source, the expected outcome and the principal IP/NDA questions.
Once an embedded system and two business models have been defined, the next logical question is: who turns the idea into a physical product? The next session moves from the abstract model to the engineering team—firmware, hardware, mechanics, architecture, management and the physical supply chain.