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Minimizing Technical Debt Under Contract Deadlines

Written by Grady Oates | Nov 21, 2025 3:47:05 PM
Deadlines in software are unavoidable, and often immovable. They’re written into contracts, tied to specific rounds of funding, and aligned to larger program milestones. Missing a deadline risks financial penalties, strains customer relationships, and delays fielded capabilities. To meet these deadlines, teams often push forward with good enough solutions, with the intention to clean it up later. However, in practice, later rarely comes. Technical debt is often inevitable on tight timelines, but how you handle it makes all the difference. The best strategy isn’t just to wait until right before delivering a release to pay off that debt, it’s to minimize it as you go. That means building discipline into daily practices, making pragmatic trade-offs, and aligning contractual deliverables with sustainable engineering. This post explores strategies for doing exactly that.  
 

The High Stakes of Technical Debt 

In typical commercial software, technical debt might mean lost productivity or missed revenue. In the industries that we support (including avionics and defense), the consequences are far steeper: 

  • Unsafe execution costing substantial financial loss, or even loss of human life. 
  • Security vulnerabilities that could jeopardize mission effectiveness or at least compliance requirements. 
  • Integration failures that greatly increase the time taken to test with scarcely available hardware. 
  • Fragile architectures that can’t hold up to real world operational stresses. 
  • Increased costs of maintenance that aren’t sustainable in the long term. 

 

A rushed patch that works in an isolated testing environment may later snowball into a costly rewrite. Because these systems often stay in service for decades, shortcuts today will become tomorrow’s liabilities. 

The goal isn’t to limit technical debt altogether, but by using a few simple principles we can make sure it never spirals beyond our control. 

 

1) Refactor As You Go

Refactoring doesn’t have to mean grinding to a halt to rewrite entire systems or modules. It can be done incrementally by making many small improvements each time a section of code is updated. 

 

Example 1: 

When updating the following code to support a new status code: 

if (status == 1) 

    execute(); 

else 

    log_error(“ERROR: Can not execute!”) 

}

 

Instead of simply adding a second conditional check against another hard coded integer, we can make a small refactor as part of the update. 

enum SystemState { Undefined=0, Running=1, Standby=2, Error=7 }; 

if (status == SystemState::Running || status == SystemState::Standby) 

    execute(); 

else if (status == SystemState::Error) 

    log_error(“ERROR: Error status received! Skipping Execution.”) 

else if (status == SystemState::Undefined) 

    log_erorr(“ERROR: Undefined status received! Skipping Execution.”) 

else 

    log_error(“ERROR: Unsupported status received! Skipping Execution.”) 

 

By refactoring with a SystemState enumeration, we can improve clarity, reduce risk of misuse, and provide more robust error messaging for whoever maintains this system years down the road. Simple and painless refactors like this can be done in a moment. If deferred as additional technical debt, encountering these error cases in the future could cause confusion and become costly to investigate. 

This is a somewhat trivial example, but I’ve seen similar far too often, persist for far too long. Large refactors or rewrites should be documented and planned, but it doesn’t hurt to keep an eye out for small areas of improvement any time code is being updated or expanded. 

 

2) Code Defensively

In real world operational environments, the “happy path” is often the least likely outcome. Defensive coding is about anticipating that things will go wrong. Hardware fails, networks degrade, external systems send malformed data, and operators improvise in unexpected ways. A defensive mindset ensures that your software fails gracefully instead of collapsing catastrophically. 

Some key defensive strategies: 

  • Validate all inputs. Never assume upstream systems will provide valid data. This includes range checks, null checks, and format validations. 
  • Fail Fast and Fail Safe. If an unexpected state is encountered, return to a safe default or execute a controlled shutdown instead of proceeding with unsafe assumptions. This provides predictability, and prevents cascading errors, making the root cause easier to diagnose. 
  • Expect Concurrency Errors. Whenever working in multithreaded environments, assume that any possible deadlock or race condition will occur. Use atomic operations, locks, and design patterns like publisher-subscriber to mitigate these types of errors. 
  • Limit Assumptions About the Environment. Don’t assume that there will always be disk space, a stable network, or synchronized timings. Implement timeouts, sanity checks, and fallbacks when these edge cases occur. 

The earlier these things are considered the cheaper they are to prevent. Patching these issues up as they occur can be quite costly in terms of time spent debugging and testing. 

 

3) Align Requirements with Reality

Technical debt often begins before any code is written. It can begin with contracts or requirements that are too vague or place emphasis only on features rather than sustainability or error handling. This is how software is delivered that “works” in the demo but can’t survive integration. 

When possible, advocate for the software requirements to help manage technical debt. Have requirements: 

  • Define the behavior of unexpected or even seemingly impossible edge cases. 
  • Provide performance expectations to serve as a benchmark for when optimizations should be prioritized. 
  • Include lightweight documentation deliverables, to ensure the code is easily understood and maintainable (even by future teams). 

This level of detail helps keep a focus on the end user experience of the software, and primary use cases, rather than merely implementing a list of features in an oversimplified checklist. 

 

4) Document at Point of Change

Engineers rotate off programs, contractors change, programs shift direction. The constant is the codebase and the trail of documentation you leave behind. This doesn’t mean creating massive binders of documents that collect dust. Documentation is important, but if it’s disorganized or overwhelming, it can be counterproductive. When moving fast, it’s most effective to focus on “just-in-time” documentation. Things like:

  • Providing breadcrumbs in commit messages, tying commits to requirement IDs. 
  • Limited inline comments. Only adding them where the reasoning isn’t obvious. 
  • Simple design notes. Providing one-page documents of architectural decisions, and trade-off discussions. 

Doing these things can keep overhead costs low while still providing much needed context and direction to future maintainers. 

 

5) Lean on Tools and Culture

Mitigating technical debt is only possible within a team culture that values it and streamlined with the right set of tools and processes. 

Possibly the most important principle of all is cultivating a shared mindset that embraces good practices and continually seeks out opportunities for improvement. If every team member has the goal of leaving code “better than they found it,” technical debt tends to accrue much more slowly. 

It’s much easier to manage technical debt when processes and tools are set in place to enforce consistency and quality. Such as: 

  • Code reviews. Not every change needs a design discussion amongst the whole team, but every change should at least be reviewed and understood by a peer. This improves interoperability between systems and prevents siloing of knowledge. 
  • Static Analysis. Running these tools early and throughout the development process can help highlight potential pitfalls, and unforeseen vulnerabilities. 
  • Automated Testing. Even though it may seem like overhead, especially early on, even a minimal test suite can pay dividends over the course of a project. The earlier an issue is detected the easier it is to investigate and fix. Setting up automated tests can also provide confidence to both the team and managers that constant progress is being made and there won’t be as many “gotchas” when it comes time to integrate with a larger system or hardware. 

 

Closing Thoughts

Minimizing technical debt under contract deadlines isn’t endlessly polishing. It’s maintaining a disciplined but practical approach. It can sometimes feel like progress is being made slowly, but addressing technical debt throughout development will pay for itself when it comes time to validate, integrate, and deliver. Following these principles consistently will not only help deliver on time, but will deliver quality products that remain secure, maintainable, and interoperable for many years to come.

Reducing technical debt takes more than discipline, it takes the right foundation. Lynx software platforms are engineered for sustainable development under real-world program constraints. From secure separation kernels to streamlined DevSecOps integration, we help teams deliver robust, certifiable systems faster, and keep them maintainable for decades.

See how Lynx can help you access your software architecture or contact us here.