Detection strategies: metrics-based rules for detecting design flaws

In order to support the maintenance of an object-oriented software system, the quality of its design must be evaluated using adequate quantification means. In spite of the current extensive use of metrics, if used in isolation metrics are oftentimes too fine grained to quantify comprehensively an investigated design aspect (e.g., distribution of system's intelligence among classes). To help developers and maintainers detect and localize design problems in a system, we propose a novel mechanism - called detection strategy - for formulating metrics-based rules that capture deviations from good design principles and heuristics. Using detection strategies an engineer can directly localize classes or methods affected by a particular design flaw (e.g., God Class), rather than having to infer the real design problem from a large set of abnormal metric values. We have defined such detection strategies for capturing around ten important flaws of object-oriented design found in the literature and validated the approach experimentally on multiple large-scale case-studies.