IMPROVING FEATURE LOCATION BY COMBINING DYNAMIC ANALYSIS AND STATIC INFERENCES

Identifying the code needed to perform software main-tenance and evolution tasks can be very difficult and time consuming for large, complex software systems. A number of techniques have been proposed that employ either static or dynamic analysis to isolate code related to a feature of interest. Static approaches suffer from poor precision by in-cluding irrelevant code, while dynamic approaches can suf-fer from poor recall by excluding relevant code. This paper presents and evaluates a hybrid approach for feature loca-tion that augments execution trace analysis with an analysis based on the program structure and associated semantics. This approach improves the completeness of feature loca-tion results by expanding the mapping of features to code provided by dynamic analysis in light of the static structure and semantics of the program. The approach is evaluated relative to a well-known dynamic approach using several features in an open source system. 1