Properties of a Feature in Code-Assets: An Exploratory Study

Software product line engineering is a paradigm for developing a family of software products from a repository of reusable assets rather than developing each individual product from scratch. In featureoriented software product line engineering, the common and the variable characteristics of the products are expressed in terms of features. Using software product line engineering approach, software products are produced en masse by means of two engineering phases: (i) Domain Engineering and, (ii) Application Engineering. At the domain engineering phase, reusable assets are developed with variation points where variant features may be bound for each of the diverse products. At the application engineering phase, individual and customized products are developed from the reusable assets. Ideally, the reusable assets should be adaptable with less effort to support additional variations (features) that were not planned beforehand in order to increase the usage context of SPL as a result of expanding markets or when a new usage context of software product line emerges. This paper presents an exploration research to investigate the properties of features, in the code-asset implemented using Object-Oriented Programming Style. In the exploration, we observed that program elements of disparate features formed unions as well as intersections that may affect modifiability of the code-assets. The implication of this research to practice is that an unstable product line and with the tendency of emerging variations should aim for techniques that limit the number of intersections between program elements of different features. Similarly, the implication of the observation to research is that there should be subsequent investigations using multiple case studies in different software domains and programming styles to improve the understanding of the findings.

Software Product Line Analysis Using Variability-aware Datalog

Applying program analyses to Software Product Lines (SPLs) has been a fundamental research problem at the intersection<br>of Product Line Engineering and software analysis. Different attempts have been made to "lift" particular product-level analyses to run on the entire product line. In this paper, we tackle the class of Datalog-based analyses (e.g., pointer and taint analyses), study the theoretical aspects of lifting Datalog inference, and implement a lifted inference algorithm inside the Souffl Datalog engine. We evaluate our implementation on a set of Java and C-language benchmark product lines. We show significant savings in processing time and fact database size (billions of times faster on one of the benchmarks) compared to brute-force analysis of each product individually.