Clafer: Lightweight Modeling of Structure, Behaviour, and Variability

Embedded software is growing fast in size and complexity, leading to intimate mixture of complex architectures and complex control. Consequently, software specification requires modeling both structures and behaviour of systems. Unfortunately, existing languages do not integrate these aspects well, usually prioritizing one of them. It is common to develop a separate language for each of these facets. In this paper, we contribute Clafer: a small language that attempts to tackle this challenge. It combines rich structural modeling with state of the art behavioural formalisms. We are not aware of any other modeling language that seamlessly combines these facets common to system and software modeling. We show how Clafer, in a single unified syntax and semantics, allows capturing feature models (variability), component models, discrete control models (automata) and variability encompassing all these aspects. The language is built on top of first order logic with quantifiers over basic entities (for modeling structures) combined with linear temporal logic (for modeling behaviour). On top of this semantic foundation we build a simple but expressive syntax, enriched with carefully selected syntactic expansions that cover hierarchical modeling, associations, automata, scenarios, and Dwyer's property patterns. We evaluate Clafer using a power window case study, and comparing it against other notations that substantially overlap with its scope (SysML, AADL, Temporal OCL and Live Sequence Charts), discussing benefits and perils of using a single notation for the purpose

Feature-Oriented Modelling Using Event-B

Event-B is a formal method for specification and verification of reactive systems. Its Rodin toolkit provides comprehensive support for modelling, refinement and analysis using theorem proving, animation and model checking. There has always been a need to reuse existing models and their associated proofs when modelling related systems to save time and effort. Software product lines (SPLs) focus on the problem of reuse by providing ways to build software products having commonalities and managing variations within products of the same family. Feature modelling is a well know technique to manage variability and configure products within the SPLs. We have combined the two approaches to formally specify SPLs using Event-B. This will contribute the concept of formalism to SPLs and re-usability to Event-B. Existing feature modelling notations were adapted and extended to include refinement mechanism of Event-B. An Eclipse-based graphical feature modelling tool has been developed as a plug-in to the Rodin platform. We have modelled the "production cell" case-study in Event-B, an industrial metal processing plant, which has previously been specified in a number of formalisms. We have also highlighted future directions based on our experience with this framework so far

Analysis of Feature Models Using Alloy: A Survey

Feature Models (FMs) are a mechanism to model variability among a family of closely related software products, i.e. a software product line (SPL). Analysis of FMs using formal methods can reveal defects in the specification such as inconsistencies that cause the product line to have no valid products. A popular framework used in research for FM analysis is Alloy, a light-weight formal modeling notation equipped with an efficient model finder. Several works in the literature have proposed different strategies to encode and analyze FMs using Alloy. However, there is little discussion on the relative merits of each proposal, making it difficult to select the most suitable encoding for a specific analysis need. In this paper, we describe and compare those strategies according to various criteria such as the expressivity of the FM notation or the efficiency of the analysis. This survey is the first comparative study of research targeted towards using Alloy for FM analysis. This review aims to identify all the best practices on the use of Alloy, as a part of a framework for the automated extraction and analysis of rich FMs from natural language requirement specifications.Comment: In Proceedings FMSPLE 2016, arXiv:1603.0857

Design and evaluation of the FAMILIAR tool

2014 Spring.Includes bibliographical references.Software Product Line Engineering (SPLE) aims to efficiently produce multiple software products, on a large scale, that share a common set of core development features. Feature Modeling is a popular SPLE technique used to describe variability in a product family. FAMILIAR (FeAture Model scrIpt Language for manipulation and Automatic Reasoning) is a Domain-Specific Modeling Language (DSML) for manipulating Feature Models (FMs). One of the strengths of the FAMILIAR language is that it provides rich semantics for FM composition operators (aggregate, merge, insert) as well as decomposition operators (slice). The main contribution of this thesis is to provide an integrated graphical modeling environment that significantly improves upon the initial FAMILIAR framework that was text-based and consisted of loosely coupled parts. As part of this thesis we designed and implemented a new FAMILIAR Tool that provides (1) a fast rendering framework for the graphically representing feature models, (2) a configuration editor and (3) persistence of feature models. Furthermore, we evaluated the usability of our new FAMILIAR Tool by performing a small experiment primarily focusing on assessing quality aspects of newly authored FMs as well as user effectiveness and efficiency

Automated analysis of feature models: Quo vadis?

Feature models have been used since the 90's to describe software product lines as a way of reusing common parts in a family of software systems. In 2010, a systematic literature review was published summarizing the advances and settling the basis of the area of Automated Analysis of Feature Models (AAFM). From then on, different studies have applied the AAFM in different domains. In this paper, we provide an overview of the evolution of this field since 2010 by performing a systematic mapping study considering 423 primary sources. We found six different variability facets where the AAFM is being applied that define the tendencies: product configuration and derivation; testing and evolution; reverse engineering; multi-model variability-analysis; variability modelling and variability-intensive systems. We also confirmed that there is a lack of industrial evidence in most of the cases. Finally, we present where and when the papers have been published and who are the authors and institutions that are contributing to the field. We observed that the maturity is proven by the increment in the number of journals published along the years as well as the diversity of conferences and workshops where papers are published. We also suggest some synergies with other areas such as cloud or mobile computing among others that can motivate further research in the future.Ministerio de Economía y Competitividad TIN2015-70560-RJunta de Andalucía TIC-186

Intersection of Feature Models

In this paper, we present an algorithm for the construction of the intersection of two feature models. The feature models are allowed to have "requires" and "excludes" constraints, and should be parent-compatible. The algorithm is applied to the problem of combining feature models from stakeholders with different viewpoints