easiertocompute

EasierToCompute is a term used to describe a set of design principles, tools, and methodologies intended to reduce the effort required to perform and optimize computation. It is commonly used as a conceptual umbrella rather than a single project. It focuses on providing intuitive interfaces, sensible defaults, and automated workflows that help users achieve correct results with less manual tuning. The concept spans programming languages, libraries, and runtimes that prioritize accessibility without sacrificing performance where possible.

The term arose in discussions of human-centered computing and software ergonomics, particularly in contexts where complex numerical tasks, data processing, and algorithmic decisions must be implemented by practitioners who are not specialists in low-level optimization. EasierToCompute is not tied to a single technology; rather it encompasses declarative or domain-specific approaches, automatic parallelization, memoization, profiling, and resource-aware execution models.

Key principles include abstraction without excessive opacity, composability of components, reproducibility of results, safety and correctness, and portability across hardware and environments. Typical components are high-level APIs, domain-specific languages, compilers that emit optimized code, and tooling that handles data handling, error propagation, and performance diagnostics.

Common applications lie in data analysis pipelines, scientific computing, machine learning experimentation, and education, where lowering barriers accelerates experimentation and deployment. Critics warn that there can be trade-offs between ease of use and fine-grained control or optimal performance, and that automated systems may mask underlying complexity.

See also: high-level programming, declarative programming, domain-specific languages, software ergonomics, reproducible research.