RED-PL, a Method for Deriving Product Requirements from a Product Line Requirements Model

International audienceSoftware product lines (SPL) modeling has proven to be an effective approach to reuse in software development. Several variability approaches were developed to plan requirements reuse, but only little of them actually address the issue of deriving product requirements. Indeed, while the modeling approaches sell on requirements reuse, the associated derivation techniques actually focus on deriving and reusing technical product data.This paper presents a method that intends to support requirements derivation.Its underlying principle is to take advantage of approaches made for reuse PL requirements and to complete them by a requirements development process by reuse for single products. The proposed approach matches users' product requirements with PL requirements models and derives a collection ofrequirements that is (i) consistent, and (ii) optimal with respect to users' priorities and company's constraints. The proposed methodological process was validated in an industrial setting by considering the requirement engineering phase of a product line of blood analyzers

Deriving Product Line Requirements: the RED-PL Guidance Approach

Product lines (PL) modeling have proven to be an effective approach to reuse in software development.Several variability approaches were developed to plan requirements reuse, but only little of them actuallyaddress the issue of deriving product requirements.This paper presents a method, RED-PL that intends to support requirements derivation. The originality ofthe proposed approach is that (i) it is user-oriented, (ii) it guides product requirements elicitation andderivation as a decision making activity, and (iii) it provides systematic and interactive guidance assistinganalysts in taking decisions about requirements. The RED-PL methodological process was validatedin an industrial setting by considering the requirement engineering phase of a product line of blood analyzers

Conformance Checking with Constraint Logic Programming: The Case of Feature Models

Developing high quality systems depends on developing high quality models. An important facet of model quality is their consistency with respect to their meta-model. We call the verification of this quality the conformance checking process. We are interested in the conformance checking of Product Line Models (PLMs). The problem in the context of product lines is that product models are not created by instantiating a meta-model: they are derived from PLMs. Therefore it is usually at the level of PLMs that conformance checking is applied. On the semantic level, a PLM is defined as the collection of all the product models that can be derived from it. Therefore checking the conformance of the PLM is equivalent to checking the conformance of all the product models. However, we would like to avoid this naïve approach because it is not scalable due to the high number of models. In fact, it is even sometimes infeasible to calculate the number of product models of a PLM. Despite the importance of PLM conformance checking, very few research works have been published and tools do not adequately support it. In this paper, we present an approach that employs Constraint Logic Programming as a technology on which to build a PLM conformance checking solution. The paper demonstrates the approach with feature models, the de facto standard for modeling software product lines. Based on an extensive literature review and an empirical study, we identified a set of 9 conformance checking rules and implemented them on the GNU Prolog constraints solver. We evaluated our approach by applying our rules to 50 feature models of sizes up to 10000 features. The evaluation showed that our approach is effective and scalable to industry size models

A Systematic Approach to Express IS Evolution Requirements Using Gap Modelling and Similarity Modelling Techniques

International audienceGaps and similarities are two important concepts used in Information System (IS) projects that deal with the evolution issue. The idea in using these concepts is to analyse what changes or what remains similar between two situations, typically the changed situation and the new one, rather than just describing the new situation. Although in the industry, the daily practice consists in expressing evolution requirements with gaps and similarities, little attention has been paid in research to better systematically define these two kinds of concepts so as to better support the expression of evolution requirements. This paper proposes an approach that combines meta-modelling with generic typologies of gap operators and similarity predicates. Our purpose is not to define yet another requirement modelling language. On the contrary, the two generic typologies can be adapted to existing modelling language such as Use Cases, I* and KAOS goal models, Goal/Strategy maps, Entity-Relationship diagrams, and Workflow models