Forwarded from TechLead Bits
GenAI for Legacy Systems Modernization
While most people actively write about using GenAI tools to generate new code, there is a new Thoughtworks publication that focuses on the opposite — using AI to understand and refactor legacy systems.
What makes legacy systems modernization expensive?
- Lack of design and implementation details knowledge
- Lack of actual documentation
- Lack of automated tests
- Absence of human experts
- Difficulty to measure the impact of the change
To address these challenges Thoughtworks team developed a tool called CodeConcise. But the authors highlighted that you don't need exactly this tool, the approach and ideas can be used as a reference to implement your own solution.
Key concepts:
✏️ Treat code as data
✏️ Build Abstract Syntax Trees (ASTs) to identify entities and relationships in the code
✏️ Store these ASTs in graph database (neo4j)
✏️ Use a comprehension pipeline that traverses the graph using multiple algorithms, such as Depth-first Search with backtracking in post-order traversal, to enrich the graph with LLM-generated explanations at various depths (e.g. methods, classes, packages)
✏️ Integrate the enriched graph with a frontend application that implements Retrieval-Augmented Generation (RAG) approach
✏️ The RAG retrieval component pulls nodes relevant to the user’s prompt, while the LLM further traverses the graph to gather more information from their neighboring nodes to provide the LLM-generated explanations at various levels of abstraction
✏️ The same enrichment pipeline can be used to generate documentation for the existing system
For now the tool was tested with several clients to generate explanations for low-level legacy code. The next goal is to improve the model to provide answers at the higher level of abstraction, keeping in mind that it might not be directly possible by examining the code alone.
The work looks promising and could significantly reduce the time and cost of modernizing old systems (especially written on exotic languages like COBOL). It simplifies reverse-engineering and helps generate knowledge about the current system. The authors also promised to share results on improving the current model and provide more real life examples for the tool usage.
#news #engineering #ai
While most people actively write about using GenAI tools to generate new code, there is a new Thoughtworks publication that focuses on the opposite — using AI to understand and refactor legacy systems.
What makes legacy systems modernization expensive?
- Lack of design and implementation details knowledge
- Lack of actual documentation
- Lack of automated tests
- Absence of human experts
- Difficulty to measure the impact of the change
To address these challenges Thoughtworks team developed a tool called CodeConcise. But the authors highlighted that you don't need exactly this tool, the approach and ideas can be used as a reference to implement your own solution.
Key concepts:
✏️ Treat code as data
✏️ Build Abstract Syntax Trees (ASTs) to identify entities and relationships in the code
✏️ Store these ASTs in graph database (neo4j)
✏️ Use a comprehension pipeline that traverses the graph using multiple algorithms, such as Depth-first Search with backtracking in post-order traversal, to enrich the graph with LLM-generated explanations at various depths (e.g. methods, classes, packages)
✏️ Integrate the enriched graph with a frontend application that implements Retrieval-Augmented Generation (RAG) approach
✏️ The RAG retrieval component pulls nodes relevant to the user’s prompt, while the LLM further traverses the graph to gather more information from their neighboring nodes to provide the LLM-generated explanations at various levels of abstraction
✏️ The same enrichment pipeline can be used to generate documentation for the existing system
For now the tool was tested with several clients to generate explanations for low-level legacy code. The next goal is to improve the model to provide answers at the higher level of abstraction, keeping in mind that it might not be directly possible by examining the code alone.
The work looks promising and could significantly reduce the time and cost of modernizing old systems (especially written on exotic languages like COBOL). It simplifies reverse-engineering and helps generate knowledge about the current system. The authors also promised to share results on improving the current model and provide more real life examples for the tool usage.
#news #engineering #ai
martinfowler.com
Legacy Modernization meets GenAI
Lessons from building and using a GenAI tool to assist legacy modernization.
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💊 t.me/czerwpig
🗣https://t.me/Czerwonapigula
Niewygodne info😈 #news #nwo #ciekawostki #info #globalizacja #świat #Polska #wojna #konflikty #news #wiadomości #świat #europa
Forwarded from TechLead Bits
Open Infrastructure is Not Free
There was a piece of news last week that might not be very noticeable, but it's really important for the whole open source community. On Sep 23 open source foundations like Sonatype (Maven Central), Open Source Security Foundation (OpenSSF), Python Software Foundation (PyPI) and others published a joined letter - Open Infrastructure is Not Free: A Joint Statement on Sustainable Stewardship.
What problem they highlighted:
🔸 Open source infrastructure is the foundation of any modern digital infrastructure.
🔸 User expects this infrastructure to be secure, fast, reliable, and global.
🔸 Public registries are often used to distribute proprietary software (it may have open source license but it can work only as a part of a paid product).
🔸 Commercial organizations heavily use open source infrastructure as free CDN and distribution systems.
🔸 Open source infrastructure is supported by non-profit foundations and enthusiasts. They don't have enough resources to meet growing expectations.
🔸 Load on the infrastructure grows exponentially, donations - linearly.
🔸 This situation produces a disbalance: billion-dollars ecosystems live on services that are built on goodwill, unpaid weekends and sponsorships.
The problem is obvious: too many companies make money on open source infrastructure without giving a cent back. They profit, while the real costs are carried by volunteers and foundation sponsors. The claim is fair enough.
Proposed ideas:
🔸 Commercial Partnership: Fund infrastructure in proportion to usage.
🔸 Tiered Access: Free access for individual contributors, paid options for scale and performance for high-volume consumers.
🔸 Additional Capabilities: Provide additional capabilities that might be interesting for commercial entities (e.g. some statistics or analytics)
The authors said that this letter is only the beginning: they will start to actively work with foundations, governments, and industry partners to improve the situation. Looks like in 2-3 years we'll have totally different infrastructure, and, most probably, it will not be free.
#news #technologies
There was a piece of news last week that might not be very noticeable, but it's really important for the whole open source community. On Sep 23 open source foundations like Sonatype (Maven Central), Open Source Security Foundation (OpenSSF), Python Software Foundation (PyPI) and others published a joined letter - Open Infrastructure is Not Free: A Joint Statement on Sustainable Stewardship.
What problem they highlighted:
🔸 Open source infrastructure is the foundation of any modern digital infrastructure.
🔸 User expects this infrastructure to be secure, fast, reliable, and global.
🔸 Public registries are often used to distribute proprietary software (it may have open source license but it can work only as a part of a paid product).
🔸 Commercial organizations heavily use open source infrastructure as free CDN and distribution systems.
🔸 Open source infrastructure is supported by non-profit foundations and enthusiasts. They don't have enough resources to meet growing expectations.
🔸 Load on the infrastructure grows exponentially, donations - linearly.
🔸 This situation produces a disbalance: billion-dollars ecosystems live on services that are built on goodwill, unpaid weekends and sponsorships.
The problem is obvious: too many companies make money on open source infrastructure without giving a cent back. They profit, while the real costs are carried by volunteers and foundation sponsors. The claim is fair enough.
Proposed ideas:
🔸 Commercial Partnership: Fund infrastructure in proportion to usage.
🔸 Tiered Access: Free access for individual contributors, paid options for scale and performance for high-volume consumers.
🔸 Additional Capabilities: Provide additional capabilities that might be interesting for commercial entities (e.g. some statistics or analytics)
The authors said that this letter is only the beginning: they will start to actively work with foundations, governments, and industry partners to improve the situation. Looks like in 2-3 years we'll have totally different infrastructure, and, most probably, it will not be free.
#news #technologies