programmanalyse

Programmanalyse describes the systematic examination of computer programs to determine properties about their behavior, structure, or correctness, often without executing the program fully. It encompasses methods aimed at bug detection, safety verification, performance estimation, and general program understanding.

Static analysis analyzes source code or binaries without running the program. Techniques include data-flow analysis, control-flow graphs, abstract interpretation, and symbolic execution. Static analysis can reveal potential runtime errors, security vulnerabilities, code quality issues, and performance hotspots.

Dynamic analysis observes the program during execution. Profiling, instrumentation, tracing, and runtime verification provide empirical data on resource use, timing, memory behavior, and real-time properties. Dynamic approaches complement static analysis by exposing issues that appear only at run time.

Formal methods and model checking apply mathematical models to prove or disprove properties such as correctness, termination, and safety. Tools range from theorem provers to automated model checkers, and they are especially used in safety-critical domains, compilers, and high-assurance software.

Applications and limitations: Programmanalyse supports software development, debugging, optimization, and security auditing, but faces challenges in scalability, false positives, and language-specific constraints. An effective approach often combines several techniques tailored to the domain, language, and required guarantees.