Recalculable

Recalculable is an adjective describing a quantity, calculation, or process that can be recomputed efficiently when input data changes. In computing and numerical analysis, recalculability is often achieved with incremental or online algorithms that reuse prior results to update outputs without performing a full calculation from scratch. This property supports interactivity, real-time feedback, and resource efficiency in dynamic systems.

Applications of recalculable computations include streaming data analytics (updating averages or aggregates as new observations arrive), financial risk or pricing models (recalculating metrics as market inputs change), and computer graphics or simulations (adjusting results after small parameter edits). In spreadsheet software, recalculation is a core mechanism: when a cell value changes, dependent formulas are reevaluated to produce updated results.

Common approaches to achieve recalculability include maintaining sufficient statistics, incremental or differential updates, memoization, and reactive programming techniques that propagate changes only where they affect outputs. The term emphasizes the ability to update rather than restart a calculation.

Limitations exist: some calculations resist efficient recalculation and require a complete re-evaluation; numerical accuracy can drift if incremental updates accumulate errors. The notion is closely related to incremental computation, online algorithms, and memoization. Etymology-wise, recalculable is derived from recalculare (to calculate again) with the -able suffix; in English it is relatively rare, but used in technical contexts and translations from Romance languages.