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In the race to modernise legacy systems, many organisations turn to automated code conversion tools or the latest LLM based code converters as a quick fix. These tools promise speed and efficiency but often fall short of delivering scalable, optimised results. The core problem lies in their “as-is” approach – migrating outdated code without addressing inefficiencies, technical debt, or compatibility with modern frameworks. Additionally, most of these tools fail to optimise legacy code for the efficiencies offered by modern frameworks, either by selecting inappropriate libraries or introducing unnecessary complexities.
This is where Merit stands out. We recognise that modernisation extends beyond automation—it requires a strategic, well-architected approach. By leveraging structured frameworks, advanced prompt engineering, and coding best practices, we transform legacy systems into scalable, high-performance solutions with long-term maintainability.
In this blog, we’ll examine the limitations of relying solely on automated code conversion tools, even those powered by LLMs, and highlight how Merit’s approach ensures true modernisation. While automated tools play a role, modernisation must align with strategic objectives, accounting for the constraints of these tools to deliver optimised, future-proof solutions.
Automated code conversion tools have become a common solution for organisations looking to modernise legacy systems quickly. While they achieve basic conversion, they often fail to deliver long-term benefits. Here are some critical shortcomings of “as-is” code conversion:
1. Lack of Optimisation – The converted code often replicates outdated logic without leveraging modern best practices, leading to inefficiencies in performance. Example: Directly converting SAS DATA steps to PySpark without restructuring results in multiple df.filter() calls instead of optimised Spark transformations, leading to poor performance.
2. Increased Technical Debt – Poorly converted code introduces maintenance challenges, increasing long-term costs. Example: Legacy SQL cursor-based loops converted into Python loops instead of set-based operations create bottlenecks and high execution times, making the system harder to manage.
3. Scalability Issues – Without re-architecting for modern platforms, converted code fails to support future growth or integration needs. Example: Migrating SAS scripts to Pandas without leveraging PySpark’s distributed processing leads to memory overloads when handling large datasets.
4. Inefficient Code Structures and Redundant Logic – Automated conversion tools migrate code as-is without optimising control structures, removing redundant computations, or improving data handling mechanisms. Example: Legacy SQL self-joins and deeply nested subqueries are directly migrated instead of using modern SQL CTEs or PySpark’s broadcast joins, resulting in slower query performance.
5. Failure to Adopt Modern Best Practices – Automated tools neglect essential programming best practices such as modularisation, efficient inheritance structures, and optimal library selection. Example: Converting SAS macros into repetitive Python scripts instead of reusable functions results in redundant code, increasing maintenance complexity.
While these tools may provide a quick fix, the long-term consequences can outweigh the initial benefits, leaving organisations with systems that are neither future-proof nor easy to maintain.
At Merit, we approach legacy modernisation differently. Our focus is on delivering optimised and scalable solutions, keeping in mind the overall business purpose of the legacy modernisation effort. Here’s how we achieve that:
1. Framework-Driven Optimisation
2. AI-Powered Prompt Engineering Templates
3. Coding Best Practices and Maintainability
4. Scalability by Design
A Merit customer, one of the world’s largest and fast-growing providers of industry intelligence solutions was struggling with outdated data systems that hampered agility and innovation. The organisation initially considered a standard code conversion tool but realised it would only replicate existing inefficiencies.
By partnering with Merit, they benefited from:
For the industry intelligence client, the upgraded technology platform was a game-changer, and today, we’re leveraging the same cloud infrastructure and architecture to build new GenAI functionality to the platform.
Modernising legacy applications often comes down to a strategic decision: refactor, rearchitect, rebuild, or replace.
Each approach varies in cost, risk, and outcomes, and the decision should align with the organisation’s long-term goals. Refactoring involves restructuring and optimisng existing code without changing its external behavior. This approach is ideal for addressing technical debt and improving performance while keeping costs and risks relatively low. It’s a practical choice when the existing architecture still meets business needs but requires enhanced maintainability and scalability.
Rearchitecting, on the other hand, involves materially altering the code to shift it to a new application architecture, enabling the exploitation of modern capabilities. While it comes with medium costs and risks, rearchitecting is often a critical step for businesses aiming to adopt cloud-native solutions or integrate advanced technologies.
For higher-impact results, rebuilding or replacing the application entirely may be necessary, though these options carry significantly higher costs and risks. The choice between myriad approaches - whether to encapsulate (expose APIs but not touch code), rehost, replatform, refactor, rearchitect, rebuild, or replace - depends on factors like the application’s current limitations, desired outcomes, and organisational priorities. By balancing immediate needs with future scalability, Merit’s approach ensures that the chosen modernisation strategy—whether refactoring to remove inefficiencies or rearchitecting to enable transformative capabilities - delivers optimised results with measurable business value.
Modernising legacy systems isn’t just about migrating code; it’s about transforming it for the future. With Merit’s smarter approach, organisations gain optimised, scalable solutions that drive efficiency, reduce costs, and prepare them for the challenges of tomorrow.
Don’t settle for “as-is” code conversion. Partner with Merit to modernise your systems the right way. Contact us today to learn how we can help you achieve smarter, faster, and more efficient legacy modernisation.
