Heuristic expansion of feature mappings in evolving program families

Abstract

SUMMARYEstablishing explicit mappings between features and their implementation elements in code is one of the critical factors to maintain and evolve software systems successfully. This is especially important when developers have to evolve program families, which have evolved from one single core system to similar but different systems to accommodate various requirements from customers. Many techniques and tools have emerged to assist developers in the feature mapping activity. However, existing techniques and tools for feature mapping are limited as they operate on a single program version individually. Additionally, existing approaches are limited to recover features on demand, that is, developers have to run the tools for each family member version individually. In this paper, we propose a cohesive suite of five mapping heuristics addressing those two limitations. These heuristics explore the evolution history of the family members in order to expand feature mappings in evolving program families. The expansion refers to the action of automatically generating the feature mappings for each family member version by systematically considering its previous change history. The mapping expansion starts from seed mappings and continually tracks the features of the program family, thus eliminating the need of on demand algorithms. Additionally, we present the MapHist tool that provides support to the application of the proposed heuristics. We evaluate the accuracy of our heuristics through two evolving program families from our industrial partners. Copyright © 2013 John Wiley & Sons, Ltd.

On the proactive and interactive visualization for feature evolution comprehension: An industrial investigation

“…The heuristics are decoupled from the SME tool and thus they can be used for any mapping and/or visualization tool. The heuristics have presented a good accuracy in the expanded mappings regarding precision (about 95%) and coverage ranging from 66% to 100% [27]. It is not the focus on this paper to analyse the effectiveness of the mapping expansion heuristics.…”

“…It is not the focus on this paper to analyse the effectiveness of the mapping expansion heuristics. More details about the rationale and strategy of the heuristics and their analyses can be found in [26,27].…”

“…As SME requires the feature mappings of each application version, it uses a set of heuristics to generate the mappings for all the versions (Vi in Figure 1). This process is named feature mapping expansion (Vi.xml in Figure 1) and is based on a seed mapping (Seed.xml in Figure 1) [26,27].…”

“…In order to realize this strategy, we combined a set of heuristics [26,27] for proactively detecting feature evolution and extended our interactive differential visualization [18]. A tool, named SourceMiner Evolution (SME) [18] supports this strategy, which currently produces three different views of the analysed versions.…”

SourceMiner Evolution: A Tool for Supporting Feature Evolution Comprehension

“…For this reason, SME uses an external suite of heuristics to automatically generate the mappings for all the software system versions from a seed (Figure 1) [10]. This process, named feature mapping expansion is detailed in [10] [11]. Feature mapping expansion involves the automatic identification of feature elements in the code departing from an initial (seed) mapping.…”