DataflowAnalysen

DataflowAnalysen, or dataflow analyses, are a family of static program analysis techniques used to determine information about the values that may propagate through a program's variables and expressions during execution. They typically operate on an intermediate representation such as a control-flow graph, and aim to answer questions about possible values, definitions, usages, and effects at different program points.

In dataflow analyses, the program is modeled as a lattice of facts with a partial order, and transfer functions describe how each program statement updates these facts. Analyses are categorized as forward or backward, depending on whether information flows with the control from the entry point or from the exit point backward. The computation uses a fixed-point iteration to solve dataflow equations until a stable solution is reached. Classic analyses include reaching definitions, live variable analysis, constant propagation, available expressions, and available definitions.

Dataflow analyses support optimizations within compilers, such as dead code elimination, register allocation hints, constant folding, and copy propagation. They also enable static verification by proving certain properties or detecting potential errors, and underpin taint tracking and security analyses in some tools.

Practical challenges include precision versus performance, scaling to large codebases, and handling language features like pointers, aliases, and dynamic dispatch. Theoretical foundations trace back to early 1970s work by Kenneth C. Kildall and colleagues, which established the dataflow framework as a general method for global program analysis.