A program family might degenerate due to unplanned changes in its implementation, thus hindering the maintenance of family members. This degeneration is often induced by feature code of the program family that is changed individually in each member without considering other family members. In extreme cases, the program family code is fully or partially replicated and individually changed across several evolving members. Hence, as a family evolves over time, it might no longer be possible to identify and classify the implementation elements realizing common and variable features. One of the imminent activities to address these problems is the history-sensitive recovery of program family s features. This recovery process encompasses the historical analysis of each family member in order to identify and classify the implementation elements (i.e. methods, attributes) according to their variability nature. Existing work fails to analyse the evolution of the family members with the goal of recovering features implementation elements. Additionally, existing techniques for feature analysis are not effective as they only take into consideration the history of a single member product. In summary, the contributions of this thesis are threefold: (i) a catalogue of mapping mismatches to guide software engineers in promoting the correctness and completeness of their feature mappings. This catalogue is useful to ensure a better effectiveness of the recovery process during the mapping analysis; (ii) a suite of five heuristics for the automatic expansion of feature mappings throughout the program family history. Those heuristics rely on both the multi-dimensional historical analysis of program families and the catalogue of mapping mismatches; and (iii) a suite of history-sensitive heuristics for classifying the implementation elements realizing each family feature according to their variability degree.