Extractive Product Line Requirements Engineering

A software product line (SPL) succeeds because we exploit the similarities between a set of software-intensive systems, together with an understanding of their differences, to reduce development cost, maintenance cost, and user confusion. In SPL engineering, reuse is planned, enabled, and enforced. It is through the development of a set of core assets that reuse is systematically practiced. Requirements assets enhance the effectiveness of reuse since engineers can work on the abstractions closer to the systems' initial concepts. Contemporary SPL requirements engineerin (RE) approaches often adopt the proactive model to build a relatively complete and stable asset base. In practice, the substantial up-front effort and the abrupt transition from existing practices associated with the proactive model present a prohibitive SPL adoption barrier for many organizations that could otherwise benefit. The extractive model overcomes these shortcomings by reusing existing products for the SPL's initial baseline. In this thesis, we present a framework for applying lightweight techniques to extract, model, and analyze a SPL's requirements assets. We define the notion of functional requirements profiles (FRPs) according to the linguistic characterization of a domain's action-oriented concerns, and show that the FRPs can be extracted from a natural language document on the basis of domain-aware lexical affinities that bear a 'verb - direct object' relation. We model the extracted FRPs by analyzing their semantic cases and by extending the orthogonal variability model (OVM). We contribute a set of heuristic rules for uncovering the variation dimensions and dependencies, and discuss merging the OVMs extracted from multiple sources. We relate functional profiles to quality requirements via scenarios, and manage requirements interactions via concept analysis. We present two applications of FRPs to support some other activities in SPL engineering. We conduct several empirical studies to evaluate our framework. The results show that our approach allows the engineers to identify the domain elements more easily and develop the domain models more systematically. Our work fills the void with respect to extracting a SPL's requirements assets, and the main thrust of our work is to promote a set of lightweight, low adoption threshold techniques as a critical enabler for practitioners to capitalize on the order-of-magnitude improvements offered by SPL engineering.Ph