Beyond Rewrites: An SDLC Automation Approach to Legacy Systems

Introduction: 

IMost enterprises want the same thing from modernization: keep the business logic that works, retire the risk that doesn’t, and do it without multi-year rewrites. What slows teams down isn’t a lack of technical intent—it’s the scale of change, the unknowns hiding in old code, and the operational risk of touching mission-critical systems.

Sanciti AI takes that path. It’s an SDLC automation framework that discovers what you have, plans safe change, generates the tests you’re missing, and validates outcomes in CI/CD. In practice, that helps enterprises reduce QA costs, accelerate deployment cycles, and boost developer productivity—while improving quality without a big-bang rewrite.

Before any change, Sanciti AI builds an accurate picture of the landscape, so the first decision is the right one: what to change, when to change it, and how to prove it worked. With that foundation, you can automate software delivery step by step—protecting what the business already depends on.

What happens before you change a line of code

• Discovery and mapping of code, dependencies, build scripts, and CI/CD.
• Compatibility and risk profiling (frameworks, deprecated APIs, library CVEs).
• Refactor candidates and change rules aligned to your target stack.
• Coverage uplift with generated unit/functional tests where gaps exist.
• Security and compliance checks aligned to ADA, HIPAA, OWASP, and NIST.

Results you can expect in well-run programs: shorter cycles (up to ~40%), faster time-to-market (~25%), leaner QA effort (up to ~40%), and fewer production defects (~20%). Practically, that means you automate software delivery with traceable controls, measurable ROI, and lower risk.

Path 1 — Java 8 → Java 17/24 (JDK upgrade)

Why it’s on the roadmap
Long-term support, performance improvements, modern APIs, and more predictable behavior in containers and CI.

Common friction points
Removed/deprecated APIs, library and plugin incompatibilities, build tool drift, GC changes, and tests that were never built for newer runtimes.

How Sanciti AI helps
It scans JDK usage, flags sensitive areas, and proposes safe refactors; upgrades dependencies (with BOM suggestions and CVE fixes); updates build targets; and auto-generates regression tests so behavior is preserved. Performance is profiled before/after. Security hardening covers TLS, logging, and deserialization hazards—helping teams accelerate deployment cycles without surprises.

What you receive
A compatibility-and-effort matrix, patched build files, dependency reports, security notes, regression reports, performance diffs, and a rollback plan if needed.

How you measure progress
Build success rate, regression pass rate, CVE closures, performance deltas, and cycle-time trends.

Path 2 — Struts → Spring Boot

Why teams move
Security posture, ecosystem velocity, cloud readiness, and operational tooling move faster in Spring Boot.

Typical risks
XML-heavy configs, action mappings, custom taglibs, interceptors, and tight coupling across layers.

How Sanciti AI helps
It maps Struts actions to Spring MVC controllers, translates configs to properties, extracts services, and generates tests to validate endpoint parity. For rollout, it uses strangler or blue/green patterns with measurable readiness—so you accelerate deployment cycles while keeping production stable.

What you receive
A modular Spring Boot codebase, endpoint parity inventory, and security/test reports you can share.

How you measure progress
Endpoint parity, latency improvement, defect escape rate, and deployment frequency.

Path 3 — Legacy ASP/.NET → latest .NET

Why it’s worth it
Modern C# features, stronger performance, cross-platform options, and better alignment with cloud-native patterns.

Common friction points
WebForms rewrites, configuration transforms, auth/identity changes, EF migrations.

How Sanciti AI helps
It inventories controllers/pages, auth flows, and configs; proposes modern project structures; and auto-creates tests (API, integration, UI smoke). OWASP controls are verified in the pipeline—reducing rework so teams boost developer productivity while improving security.

What you receive
A modern .NET solution, a migration cookbook with diffs, CI/CD pipelines, and a compliance pack.

How you measure progress
Startup/throughput gains, API response times, test coverage uplift, and deployment frequency.

Path 4 — COBOL → Java or .NET

Why organizations consider it
Mainframe cost, talent scarcity, and the need to integrate with modern platforms—balanced against the need to modernize legacy systems without losing decades of embedded rules.

Real risks
Rules hidden in code, batch complexity, VSAM/DB2 nuances, and operational risk at cutover.

How Sanciti AI helps
It reverse-engineers domain entities, data flows, and screen/record formats; maps copybooks to domain models; and auto-generates parity tests across batches and services. Schedulers and adapters are created for file/database access with reconciliation checks. Parity tests protect functionality; production parity is monitored after go-live—so you modernize legacy systems with evidence, not guesswork.

What you receive
A target service blueprint, generated service stubs, data mapping specs, a parity/validation suite, and a runbook.

How you measure progress
Functional parity, batch SLA attainment, MIPS reduction, and post-go-live incident trends.

This approach allows enterprises to modernize legacy systems without the risk of losing critical functionality.

Governance, security, and compliance (baked in)

Modernization isn’t only technical. Teams need guardrails and evidence.

• Change governance. Automated diffs, traceability from requirement → commit → test → release, and audit-ready artifacts.
• Security & compliance. Rulesets aligned to HIPAA, OWASP, NIST, and ADA; SBOM and dependency policies; customer VPC deployment options; HiTRUST-compliant setups supported.
• Operations and support. Log analysis, ticket triage, and reporting to keep health visible and actionable after cutover.

These controls let enterprises scale AI securely—governing how automation is applied, proving what changed, and showing why it’s compliant.

A run approach that respects time and risk

Assessment (2–4 weeks)
Repository ingest, dependency/risk analysis, coverage gaps, parity targets, and a pilot plan. You get a clear modernization map, not a slide deck.

Pilot (6–12 weeks)
One representative path (for example, Struts → Spring Boot) taken end-to-end with automated refactors, uplifted tests, secure CI/CD, and a documented cutover plan. The goal: prove you can reduce QA costs and accelerate deployment cycles on something real.

Scale-out
Playbooks and automation move from one application to many. The output is capability teams can run with—automating software delivery at scale without creating another dependency.

What helps the work move faster

• Source access and build scripts (or containers).
• Non-functional targets (performance SLAs, security boundaries, compliance constraints).
• Environment constraints and change windows.
• Named approvers for parity and cutover criteria.

What success looks like on a single page

• Time to first modernized release.
• Test coverage added and regression pass rates.
• CVEs closed and security findings resolved.
• Throughput/latency and resource-use deltas.
• Post-release incident rate and MTTR.
• Cycle-time reduction and cost-per-change trends.

Why a framework helps

Point tools can generate code, create tests, or scan for vulnerabilities. But without continuity across discovery, change, validation, and release, teams re-learn the same lesson in every project. Sanciti AI connects the steps. That continuity is what reduces QA costs, boosts developer productivity, and accelerates deployment cycles—while keeping risk low.

Ready to move forward—without starting over

Whether you’re upgrading Java 8 → 17/24, moving from Struts to Spring Boot, modernizing ASP/.NET, or translating COBOL into Java or .NET, the objective is the same: protect what works and modernize what doesn’t. With Sanciti AI, you don’t need to pause the business for a rewrite—you automate software delivery and move incrementally.

Sanciti AI provides the analysis, automation, and assurance to do exactly that: modernize legacy systems, reduce QA costs, accelerate deployment cycles, boost developer productivity, and scale AI securely across portfolios. Your teams deliver change with less effort and more confidence.

Book a demo today at www.sanciti.ai