computeranalyse

Computeranalyse, or computer analysis, is the systematic study and evaluation of computing systems, algorithms, and data using computational methods. It combines concepts from computer science, mathematics, statistics, and engineering to assess performance, correctness, scalability, and behavior under various conditions.

Theoretical components include algorithm analysis and computational complexity, numerical methods, and formal verification. Empirical components rely on benchmarking, profiling, statistical analysis, and experimental studies to measure real-world performance and reliability.

Common techniques involve mathematical modeling, simulations of systems and workloads, performance modeling, and data-driven analysis. Tools range from static analysis and formal methods to software profilers, performance counters, and data analysis libraries. Machine learning is increasingly used to predict behavior and guide optimization.

Applications span software engineering, high-performance computing, network and systems analysis, operations research, financial analytics, and scientific computing. Computeranalyse supports decision making, capacity planning, debugging, and security assessment by translating complex behavior into actionable metrics.

Historically, the field emerged from early algorithm analysis and numerical computing, evolving with advances in hardware, programming languages, and data science. In many contexts the term is used interchangeably with computational analysis or data analytics applied to computing systems.

See also: algorithm analysis, numerical analysis, data analysis, performance engineering.