Practical Software Testing and Verification Training for Engineering Teams

Develop practical testing and verification skills across C/C++, Python and Rust, progressing from software test fundamentals and static analysis through unit testing, structural coverage, requirements traceability, integration testing, embedded systems, AI/ML verification, automotive testing and CI/CD automation. Alpinum’s Software Testing & Verification Training Programme is a 12-module, cross-industry programme designed for engineers working across avionics, defence, rail, nuclear, automotive, embedded software, IoT and other high-assurance engineering environments.

Why Choose This Software Testing & Verification Programme?

Modern engineering teams need more than familiarity with individual testing tools. Reliable software requires a structured verification approach that connects requirements, source code, test design, coverage, integration behaviour and evidence.

This programme develops those capabilities progressively across C/C++, Python and Rust.

Participants move from foundational verification and validation principles into practical static and dynamic testing, structural coverage and MC/DC, requirements-based testing, protocol and integration testing, embedded and real-time systems, IoT, AI/ML verification, automotive/ADAS testing and automated CI/CD workflows.

The programme culminates in applying these techniques across recognised high-assurance engineering contexts.

From Software Development to Software Verification

This programme is designed as a companion to Alpinum’s Software Development Programme Using Python, C/C++ and Rust.

Engineers who have completed that programme, or who already have equivalent working knowledge of the three languages, can progress into structured software testing and verification across the development lifecycle.

Who Should Attend?

The programme is suitable for:

  • Software engineers and developers
  • Software test and QA engineers
  • Verification & Validation engineers
  • Embedded systems engineers
  • Network and systems programmers
  • AI/ML engineers
  • Automotive and ADAS software engineers
  • IoT engineers
  • Engineers moving into regulated-industry testing
  • Recent engineering graduates
  • Technical leads and architects responsible for software quality

What You Will Learn

By completing the programme, participants will develop the ability to:

  • Apply software verification and validation principles throughout the development lifecycle
  • Perform static analysis across C/C++, Python and Rust
  • Design unit and component tests across multiple languages
  • Measure structural code coverage and apply MC/DC
  • Derive tests from requirements and maintain traceability
  • Verify protocol, network and middleware integrations
  • Test embedded, real-time, IoT and networked applications
  • Apply verification and validation approaches to AI/ML systems
  • Apply safety-critical software testing approaches
  • Integrate static and dynamic verification into CI/CD
  • Relate testing practice to high-assurance industry standards

How the Software Testing Modules Fit Together

The Software Testing & Verification Programme follows a progressive pathway from testing foundations and code-level verification through requirements, system integration and domain-specific testing, before bringing the learning together through automation, assurance and cross-industry application.

Module 1 – Foundations of Testing, V&V & Test Design
Module 2
Static Analysis & Code Quality Across Languages		Module 3
Unit & Component Testing Across Languages		Module 4
Structural Code Coverage & MC/DC
Module 5
Requirements-Based Testing & Traceability		Module 6
Integration & Protocol-Level Testing
Module 7
Embedded & Real-Time Systems Testing		Module 8
IoT & Networking Applications Testing		Module 9
AI/ML Verification & Validation		Module 10
Automotive/ADAS Safety-Critical Testing
Module 11 – Test Automation & CI/CD Integration
Module 12 – Cross-Industry Standards Bridge & Capstone

Software Testing & Verification Training Modules

Module 1: Foundations of Testing, V&V & Test Design

Build a common foundation in software testing and verification, covering test levels, black-box and white-box test design, the V&V lifecycle, test strategy and entry/exit criteria.

Practical focus: derive test cases from sample requirements and develop a short test plan.

Module 2: Static Analysis & Code Quality Across Languages

Apply static analysis across C/C++, Python and Rust using practical open-source tooling, while learning how to consolidate findings into a coherent cross-language quality strategy.

Topics include cppcheck, clang-tidy, Clang Static Analyzer, pylint, mypy, clippy, SAST concepts, Semgrep and cargo-audit.

Module 3: Unit & Component Testing Across Languages

Design and execute unit and component tests across C/C++, Python and Rust using frameworks including GoogleTest/Catch2, pytest and cargo test.

The module also covers property-based testing, runtime error detection, test doubles and test architecture for multi-language systems.

Module 4: Structural Code Coverage & MC/DC

Learn how to measure test thoroughness using statement, branch and condition coverage before progressing into Modified Condition/Decision Coverage (MC/DC) and coverage-gap analysis.

Practical tooling includes gcov/lcov, coverage.py and cargo-tarpaulin.

Module 5: Requirements-Based Testing & Traceability

Connect software tests directly to engineering requirements and build traceability between requirements, test cases and results.

Participants develop a practical traceability matrix from a sample specification.

Module 6: Integration & Protocol-Level Testing

Test communication and integration across distributed and networked systems.

Topics include protocol conformance, Wireshark, Scapy, TCP/UDP testing, fuzz testing, schema validation, MQTT, Kafka, gRPC, REST and data-server integration.

Module 7: Embedded & Real-Time Systems Testing

Apply static and dynamic testing to embedded and real-time software, including embedded-aware static analysis, MISRA-C awareness, hardware-in-the-loop-style testing and runtime monitoring using FreeRTOS-based examples.

Module 8: IoT & Networking Applications Testing

Develop end-to-end testing approaches for connected systems, covering device-to-cloud scenarios, OTA updates, provisioning, load testing, reliability and observability.

Module 9: AI/ML Verification & Validation

Apply verification thinking to AI/ML systems and pipelines, including dataset and schema validation, model documentation review, model-output validation and ML pipeline integration testing.

Module 10: Automotive/ADAS Safety-Critical Testing

Apply software testing techniques to automotive and ADAS environments, including standards-aware static analysis, sensor-fusion testing and HIL-style testing.

Module 11: Test Automation & CI/CD Integration

Integrate the techniques learned throughout the programme into automated engineering pipelines.

Participants build CI/CD workflows covering static analysis, unit testing, coverage, integration testing and quality gates using GitHub Actions or GitLab CI.

Module 12: Cross-Industry Standards Bridge

Bring the complete programme together by relating software testing and verification practices to high-assurance engineering environments and assembling a cross-standard verification plan.

The supplied course currently includes DO-178C, EN 50128, IEC 61508, ISO 26262 and IEC 60880, alongside tool qualification, safety-case and audit-readiness considerations.

Practical Software Testing Labs

The programme includes practical work across:

  • Static analysis in C/C++, Python and Rust
  • Unit/component testing
  • Memory and runtime error detection
  • Property-based testing
  • Structural coverage and MC/DC
  • Requirements traceability
  • Wireshark and protocol analysis
  • Network and socket testing
  • MQTT, Kafka and gRPC integration
  • REST/gRPC data servers
  • FreeRTOS and HIL-style testing
  • IoT end-to-end testing
  • AI/ML pipeline validation
  • ADAS/sensor-fusion testing
  • CI/CD pipeline construction
  • Cross-standard verification mapping

Final Software Testing Capstone

Apply the Complete Verification Lifecycle

he programme culminates in a team-based capstone built around a hypothetical cross-industry system containing networked embedded software and an ML-based decision component. Participants progress through requirements-based test planning, static analysis, unit testing, structural coverage and MC/DC, traceability, integration testing, embedded and IoT validation, AI/ML verification and CI/CD automation before mapping the resulting verification evidence against relevant standards.

Assessment

Assessment can include:

  • Module quizzes
  • Hands-on laboratory exercises
  • Coverage and MC/DC exercise
  • Traceability matrix assignment
  • CI/CD pipeline exercise
  • Final team capstone
  • End-of-course assessment

Training Duration and Delivery

62 Lecture Hours Across 12 Modules

The programme comprises 62 lecture hours, with individual teaching sessions capped at a maximum of four hours.

Practical labs, demonstrations and hands-on exercises are additional to the lecture-hour total and can be scheduled as dedicated practical blocks or structured exercises between teaching sessions.

Who Can Use This Programme?

Individual Engineers

Build a structured software testing and verification skillset across multiple languages and engineering domains.

Graduate Engineering Teams

For participants completing networking, systems software and data infrastructure modules.

Engineering Organisations

Develop internal capability across static analysis, test automation, traceability, coverage and high-assurance workflows.

Existing Software Development Teams

Extend software-development skills into structured verification, test automation and evidence-based quality engineering.

Discuss Software Testing & Verification Training for Your Team

Build practical software testing and verification capability across C/C++, Python and Rust, from static analysis and unit testing through MC/DC, traceability, CI/CD, embedded systems and safety-critical applications.

Speak to Alpinum about the right training pathway for your engineers.

Frequently Asked Questions

The programme covers testing fundamentals, static analysis, unit and component testing, structural coverage and MC/DC, requirements traceability, integration testing, embedded and real-time testing, IoT, AI/ML verification, automotive/ADAS testing, CI/CD automation and cross-industry verification practices.

The programme contains 62 lecture hours across 12 modules. Individual sessions are capped at a maximum of four hours, with practical labs and exercises scheduled separately.

The programme applies testing and verification techniques across C/C++, Python and Rust.

Yes. The programme contains hands-on exercises covering static analysis, unit testing, code coverage, MC/DC, requirements traceability, protocols, embedded systems, AI/ML pipelines, CI/CD and other practical testing workflows.

It is designed for software engineers, test engineers, QA engineers, V&V engineers, embedded engineers, AI/ML engineers, automotive engineers, graduates and technical leads.

Participants should either have completed or be concurrently taking Alpinum’s Software Development Programme, or have equivalent practical knowledge of C/C++, Python and Rust.

Yes. Structural coverage and Modified Condition/Decision Coverage form a dedicated part of the programme.

Yes. Participants learn how to derive tests from requirements and build traceability between requirements, tests and results.

Yes. The modular structure makes it suitable for graduate programmes, internal technical training and targeted capability development.