Automated Legacy Batch Modernization via Functional Context Analysis

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Solution Overview

Problem

Modernization of legacy batch processes to next-generation architecture is complex and time-consuming, requiring significant manual effort due to the need to understand and transform batch processes developed using legacy code to meet current business needs, especially in identifying batch hotspots and designing effective next-generation platforms.

Innovation Solution

A processor-implemented method that preprocesses metadata to derive data, generates functional context, determines average elapsed time, parses long-running job logs, identifies hotspots, and recommends batch designs for future states, incorporating event-based and parallel processing architectures.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If manual analysis and transformation of legacy batch processes is performed, then understanding of functional context and batch hotspots is achieved, but transformation time and manual effort increase significantly

Engineering Contradiction:

Improveunderstanding of functional contextVSAvoidtransformation time

Core Design Contradiction:

Measurement precisionVSLoss of time

Solution Approach 1:

The patent replaces manual mechanical analysis with automated computational systems. The system automatically parses legacy batch code, extracts metadata, generates functional context models, and identifies hotspots without human intervention, thus maintaining measurement precision while dramatically reducing transformation time

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Solution Approach 2:

The system enables self-service by allowing the legacy batch processes to automatically generate their own functional context documentation and hotspot identification through automated code parsing and metadata extraction, eliminating the need for manual analysis

Inventive Principle:

Principle #25Self-service

2Manufacturing precision

If deep study of legacy batch jobs is conducted to understand technical and functional context, then transformation accuracy is improved, but complexity of the process increases

Engineering Contradiction:

Improvetransformation accuracyVSAvoidprocess complexity

Core Design Contradiction:

Manufacturing precisionVSDevice complexity

Solution Approach 1:

The patent segments the complex transformation process into distinct automated modules: metadata extraction from legacy code, functional context generation, hotspot identification, and transformation recommendation. Each module handles a specific aspect independently, maintaining transformation accuracy while reducing overall process complexity through systematic decomposition

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The system introduces an intermediary functional context model that automatically bridges legacy batch code and modern batch processes. This intermediary layer, generated through automated code analysis, simplifies the transformation process by providing a structured intermediate representation that maintains accuracy while reducing complexity

Inventive Principle:

Principle #24Intermediary (Mediator)

3Reliability

If manual efforts are used to identify batch hotspots and design next generation platform, then processing standards are met, but productivity decreases

Engineering Contradiction:

Improveprocessing standards complianceVSAvoidmodernization speed

Core Design Contradiction:

ReliabilityVSProductivity

Solution Approach 1:

The patent replaces manual identification of batch hotspots and platform design with automated computational analysis. The system parses legacy code, extracts performance metrics, identifies hotspots through algorithmic analysis, and generates modernization recommendations that meet processing standards without human intervention, thereby maintaining reliability while dramatically improving productivity

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

4Measurement precision

If comprehensive analysis of batch metadata is performed to generate functional context, then quality of modernization recommendation is improved, but computational resources and time increase

Engineering Contradiction:

Improvequality of recommendationVSAvoidcomputational resources

Core Design Contradiction:

Measurement precisionVSUse of energy by moving object

Solution Approach 1:

The patent extracts only the essential metadata and functional context information needed for modernization recommendations from the legacy batch code, rather than performing exhaustive analysis of all code elements. This selective extraction maintains recommendation quality while significantly reducing computational resource consumption

Inventive Principle:

Principle #2Taking out (Extraction)

Data Source

PatentUS12197944B2System and method for modernization of legacy batch based on functional context

Publication Date: 2025.01.14 TATA CONSULTANCY SERVICES LTD

AI summary

This disclosure relates generally to method of modernizing a legacy batch based on at least one functional context. The method includes at least one of: preprocessing, a plurality of metadata associated with a plurality of batches to obtain a plurality of derived data; generating, the functional context based on the plurality of derived data; determining, an average elapsed time for at least one application from the at least one functional context; parsing, log of the at least one consistent long running job to identify step and associated file referenced in the at least one long running job; determining, a hotspot based on at least program; and recommending, at least one batch design associated with at least one batch job in a future state. The hotspot corresponds to long running job on a batch stream, high volume files, and program with an increased millions of instructions per second (MIPS) usage.