Development & technology · Legacy Modernisation

AI training for Legacy Modernisation

Many business-critical systems still run on mainframe COBOL, ageing Java EE applications or .NET Framework solutions whose original developers moved on long ago. AI coding assistants and agents make these codebases far more approachable: they explain programme logic, reconstruct business rules, generate characterisation tests and support stepwise migration to modern languages, frameworks and cloud platforms. Successful modernisation is still engineering work, though, because automated translation without understanding simply produces new legacy code. In this course you learn to apply AI along proven patterns such as strangler fig, branch by abstraction and anti-corruption layers, lock down existing behaviour with tests before every change and base modernisation decisions on a solid analysis of what you already have.

Who is this course for?

  • Developers maintaining COBOL, PL/I or RPG systems
  • Java and .NET teams with ageing monoliths and outdated frameworks
  • Software and enterprise architects in modernisation programmes
  • IT managers and project leads responsible for migrations
  • Application modernisation and cloud migration consultants

Typical challenges we address

  • Business rules are buried undocumented in code and the original developers’ knowledge is gone
  • Missing automated tests make every change risky
  • Outdated frameworks, unpatched libraries and proprietary runtimes
  • Big-bang migrations fail on scope, data migration and parallel operation

Practical scenarios from your field

Extracting business rules

Analyse COBOL paragraphs, copybooks or Java service classes, document the embedded calculation and decision logic as readable business rules and validate them together with domain experts.

Mapping dependencies

Reconstruct call graphs, JCL job chains, database access and interfaces from source code and visualise them as diagrams to find sensible seams for stepwise replacement.

Generating characterisation tests

Capture current behaviour with golden master and approval tests, derive anonymised test data from production patterns and build a safety net before any migration begins.

Framework upgrades

Plan migrations from Java EE to Jakarta EE or Spring Boot and from .NET Framework to modern .NET, identify API breaks and apply consistent changes across many files.

Translating and refactoring code

Turn COBOL modules into idiomatic Java or C# rather than translating line by line, map data types such as packed decimals correctly and verify the result against the original with comparison tests.

Designing a strangler fig architecture

Design facades, routing layers and anti-corruption layers through which new services take over legacy functions step by step, including data synchronisation and fallback options. Each stage remains independently deployable.

Possible hands-on projects

Copybook to schema converter

A tool that reads COBOL copybooks and generates JSON schemas, Java records or SQL tables, correctly mapping decimal and REDEFINES fields.

Legacy knowledge portal

A small web app that makes analysed programmes, business rules and dependencies searchable and answers questions about the legacy system with source references.

Comparison test harness

A test harness that sends identical inputs to the old and new system, compares outputs field by field and logs discrepancies clearly.

All 10 courses for Legacy Modernisation

Vibe & agentic coding (10)

Data protection & compliance

Legacy systems often process customer, financial or insurance data: you learn to sanitise code and test data before using AI, clarify licensing and copyright questions around translated code and address the requirements of the GDPR, DORA and sector regulators for changes to critical systems.

Prerequisites

You have programming experience in at least one language of the legacy or target platform, such as COBOL, Java or C#, plus a basic grasp of software architecture.

Frequently asked questions

Can AI automatically translate a COBOL system into Java?

AI translates individual modules far faster than manual work, but a pure one-to-one translation often yields code that is hard to maintain. A better approach is to understand and test the business rules first and design the target architecture deliberately. In the course you combine AI-assisted translation with comparison tests and refactoring.

How do we handle very large codebases?

Large legacy systems do not fit entirely into a model’s context. What works is systematic inventory, per-module summaries, dependency graphs and targeted retrieval of relevant code. Agents then work module by module with a clearly defined brief. You learn to build this structure and turn the results into input for architecture decisions.

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Total €949 plus VAT