Blog posts exploring the concept "Systems-Programming"
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← Back to all tagsRust’s trait system is often compared to Haskell’s type classes, suggesting that Rust has successfully brought type class polymorphism to systems programming. While Rust’s traits are indeed inspired by type classes and provide powerful abstractions, examining the actual mechanics reveals important differences. Rust’s traits, as a multi-paradigm systems language feature, make deliberate design tradeoffs that differ in important ways from Haskell’s type classes. It’s worth taking a sidebar to also review how it compares to F#’s approach to polymorphism.
Read MoreThe blog post “Abstract Machine Models - Also: what Rust got particularly right” makes a compelling case for Abstract Machine Models (AMMs) as a missing conceptual layer between computer science and hardware. The author, reflecting on a failed microprocessor project, discovers that programmers don’t reason about either programming theory or raw hardware, but rather about intermediate mental models that predict extra-functional behavior: execution time, memory usage, concurrency patterns, energy consumption. These AMMs, the author argues, exist independently of both languages and hardware, explaining how a C programmer can transfer skills to Python despite their semantic differences.
Read MoreWhen we set out to build Firefly, we faced a fundamental question that cuts to the heart of functional systems programming: how far down the compilation stack can we preserve the elegant abstractions that make F# powerful? Specifically, can delimited continuations - the theoretical foundation for async/await, generators, and algebraic effects - survive the journey from high-level F# through MLIR’s SSA form to executable code? And perhaps more importantly, should they?
Read MoreSoftware tools face an eternal tension: wait to build fast executables or speed up workflow at the cost of the end result. Traditional approaches have forced developers to choose between aggressive optimization (and long compilation cycles) that produces efficient code versus rapid compilation cycles often yield code bloat. What if we could have both? Or rather, what if we could have the choice that matters when it matters most? The answer lies in understanding something most programmers miss about functional programming:
Read MoreThe Fidelity framework’s Farscape CLI addresses a pressing challenge in modern software development: how to enhance the safety of battle-tested C/C++ tools without disrupting the countless systems that depend on them. Every day, organizations rely on command-line tools like OpenSSL, libzip, and many others that represent decades of engineering expertise but carry the inherent memory safety risks of their C/C++ heritage. Farscape’s “shadow-api” design aims to provide a breakthrough solution: the ability to generate drop-in replacements for these critical tools that maintain perfect compatibility while adding comprehensive type and memory safety guarantees.
Read MoreThe cybersecurity landscape has shifted dramatically in recent years, with memory safety vulnerabilities accounting for approximately 70% of critical security issues in systems software. This reality has prompted governments and industries to mandate transitions to memory-safe languages for critical infrastructure. Yet the economics of wholesale rewrites are daunting: decades of refined C and C++ code represent trillions of dollars in intellectual property and domain expertise. What if, instead of rewriting everything, we could wrap existing code in provably safe interfaces?
Read MoreThe “byref problem” in .NET represents one of the most fundamental performance bottlenecks in managed programming languages. While seemingly technical, this limitation cascades through entire application architectures, not only hijacking developer productivity but also forcing them into defensive copying patterns that can devastate performance in memory-intensive applications. The Fidelity framework doesn’t just solve this problem; our designs transform the limitation into the foundation for an entirely new approach to systems programming that maintains functional programming elegance while delivering hardware-level performance.
Read MoreAt the intersection of two powerful but largely separate computing paradigms stands the Fidelity framework, a revolutionary approach to systems programming that re-imagines what’s possible when functional programming meets direct native compilation. For decades, developers have been forced into an artificial choice: embrace the productivity and safety of managed runtimes like .NET and the JVM while accepting their performance limitations, or pursue the raw efficiency of direct compilation while shouldering the burden of manual memory management and more complex development workflows.
Read MoreHere at SpeakEZ we’re rethinking how developers interact with memory management in systems programming. The conventional wisdom suggests we face a stark choice: embrace the ubiquitous memory burdens of Rust or abdicate all memory concerns and accept the performance penalties of garbage collection. We believe there’s a better way. Mandatory vs. Optional Memory Management Rust’s borrow checker has revolutionized systems programming by statically preventing memory safety issues, but it comes at a significant cost: every line of code must consider ownership and borrowing.
Read MoreThe promise of functional programming has always been apparent: write code that expresses a process to an end result, not how the machine should perform those actions. Yet for decades, this elegance came with a tax - runtime overhead, garbage collection pauses, and the implicit assumption that “real” systems programming belonged to C and its descendants. The Fidelity Framework challenges this assumption by asking a different question: What if we could preserve F#’s expressiveness, safety and precision while compiling to native code that rivals hand-written C in efficiency?
Read MoreIn the evolving landscape of programming languages, Mojo has emerged as a fascinating experiment in bridging disparate worlds. Created by Chris Lattner, whose pioneering work on LLVM and MLIR has fundamentally transformed how we think about compiler infrastructure, Mojo represents an ambitious vision: bringing Python’s accessibility to systems programming while leveraging the revolutionary capabilities of MLIR. At SpeakEZ, we’ve been exploring similar territory with our Fidelity framework built on F#. Both projects share a common foundation in MLIR, yet approach the challenge of modern language design from remarkably different philosophical starting points.
Read MoreA recent ONNX conference presentation reveals an illuminating reality about the current state of AI development infrastructure. In a Groq engineer’s talk on “How to Win Friends and Influence Hardware,” they describe an elaborate system of workarounds needed to preserve basic metadata through PyTorch’s compilation pipeline. What they present as innovation actually highlights fundamental architectural challenges inherent in Python’s design for systems programming. The complexity of their solution suggests we should examine the underlying problem more closely.
Read MoreThe Rust programming ecosystem has transformed how the software industry views systems programming. By pioneering its ownership system with “borrowing” and “lifetimes”, Rust brought compile-time memory safety into mainstream development. Beyond memory management, Rust’s innovations in zero-cost abstractions, trait-based generics, and “fearless concurrency” philosophy have influenced an entire echelon of language designers. 🔄 Updated September 2025 Aligned with our analysis of Abstract Machine Models and heterogeneous computing Cross-referenced with detailed SRTP vs traits comparison Updated MLIR dialect discussion to include DCont and Inet Clarified PHG architecture and nanopass compilation strategy At SpeakEZ, we’ve analyzed Rust’s design choices while developing the Fidelity Framework.
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