anticipability

Anticipability is a concept from compiler theory and program analysis used to determine which values or conditions will be known at a particular point in a program. In a control‑flow graph, a value is called anticipatable at a node if, along every path from that node to the program’s exit, the value will be computed before it is used again. This information is employed in optimizations such as constant propagation, dead‑code elimination and the generation of efficient register allocation schedules.

Static analysis techniques compute anticipability through a data‑flow framework. The analysis works backwards, starting from program exits where no values are considered anticipatable. For each node, the algorithm intersects the anticipatable sets of successor nodes and then adds to the set any value that the node itself computes, provided that no overriding definition occurs along any path to the exit. The process iterates until a fixed point is reached, ensuring that all anticipatable values are correctly identified.

In practice, anticipability information aids in the creation of better intermediate representations. For example, if a variable is anticipatable at a code location, the compiler can safely move its calculation earlier or eliminate redundant recomputations. It also plays a role in security analyses, where knowing what data will be available when can help detect information‑leakage paths. Despite its utility, anticipability computation must account for side effects and indirect jumps, making precise analysis challenging, especially in languages with dynamic dispatch or reflection.

Overall, anticipability is a foundational tool in modern compilers and static analysis frameworks, enabling more aggressive optimization while preserving program correctness.