A Product Line Systems Engineering Process for Variability Identification and Reduction

Software Product Line Engineering has attracted attention in the last two decades due to its promising capabilities to reduce costs and time to market through reuse of requirements and components. In practice, developing system level product lines in a large-scale company is not an easy task as there may be thousands of variants and multiple disciplines involved. The manual reuse of legacy system models at domain engineering to build reusable system libraries and configurations of variants to derive target products can be infeasible. To tackle this challenge, a Product Line Systems Engineering process is proposed. Specifically, the process extends research in the System Orthogonal Variability Model to support hierarchical variability modeling with formal definitions; utilizes Systems Engineering concepts and legacy system models to build the hierarchy for the variability model and to identify essential relations between variants; and finally, analyzes the identified relations to reduce the number of variation points. The process, which is automated by computational algorithms, is demonstrated through an illustrative example on generalized Rolls-Royce aircraft engine control systems. To evaluate the effectiveness of the process in the reduction of variation points, it is further applied to case studies in different engineering domains at different levels of complexity. Subject to system model availability, reduction of 14% to 40% in the number of variation points are demonstrated in the case studies.Comment: 12 pages, 6 figures, 2 tables; submitted to the IEEE Systems Journal on 3rd June 201

A Model-Based Approach to Managing Feature Binding Time in Software Product Line Engineering

Software Product Line Engineering (SPLE) is a software reuse paradigm for developing software products, from managed reusable assets, based on analysis of commonality and variability (C & V) of a product line. Many approaches of SPLE use a feature as a key abstraction to capture the C&V. Recently, there have been increasing demands for the provision of flexibility about not only the variability of features but also the variability of when features should be selected (i.e., variability on feature binding times). Current approaches to support variations of feature binding time mostly focused on ad hoc implementation mechanisms. In this paper, we first identify the challenges of feature binding time management and then propose an approach to analyze the variation of feature binding times and use the results to specify model-based architectural components for the product line. Based on the specification, components implementing variable features are parameterized with the binding times and the source codes for the components and the connection between them are generated

AUnit - a testing framework for alloy

textWriting declarative models of software designs and analyzing them to detect defects is an effective methodology for developing more dependable software systems. However, writing such models correctly can be challenging for practitioners who may not be proficient in declarative programming, and their models themselves may be buggy. We introduce the foundations of a novel test automation framework, AUnit, which we envision for testing declarative models written in Alloy -- a first-order, relational language that is supported by its SAT-based analyzer. We take inspiration from the success of the family of xUnit frameworks that are used widely in practice for test automation, albeit for imperative or object-oriented programs. The key novelty of our work is to define a basis for unit testing for Alloy, specifically, to define the concepts of test case and test coverage as well as coverage criteria for declarative models. We reduce the problems of declarative test execution and coverage computation to partial evaluation without requiring SAT solving. Our vision is to blend how developers write unit tests in commonly used programming languages with how Alloy users formulate their models in Alloy, thereby facilitating the development and testing of Alloy models for both new Alloy users as well as experts. We illustrate our ideas using a small but complex Alloy model. While we focus on Alloy, our ideas generalize to other declarative languages (such as Z, B, ASM).Electrical and Computer Engineerin