A number of product-line analysis approaches lift analyses such as type checking, model checking, and theorem proving from the level of single programs to the level of product lines. These approaches share concepts and mechanisms that suggest an unexplored potential for reuse of key analysis steps and properties, implementation, and verification efforts. Despite the availability of taxonomies synthesizing such approaches, there still remains the underlying problem of not being able to describe product-line analyses and their properties precisely and uniformly. We propose a formal framework that models product-line analyses in a compositional manner, providing an overall understanding of the space of family-based, feature-based, and product-based analysis strategies. It defines precisely how the different types of product-line analyses compose and inter-relate. To ensure soundness, we formalize the framework, providing mechanized specification and proofs of key concepts and properties of the individual analyses. The formalization provides unambiguous definitions of domain terminology and assumptions as well as solid evidence of key properties based on rigorous formal proofs. To qualitatively assess the generality of the framework, we discuss to what extent it describes five representative product-line analyses targeting the following properties: safety, performance, dataflow facts, security, and functional program properties.

Nowadays, cloud users face three important problems: (a) choosing one or more appropriate cloud provider(s) to run their application(s), (b) selecting appropriate cloud resources, which implies having enough information about the available resources, including their characteristics and constraints, and (c) configuring the cloud resources. These problems are mostly due to the wide range of resources. These resources usually have distinct dependencies, and they are offered at various clouds' layers. In this complex scenario, the users often have to handle cloud resources and their dependencies manually. This is an error-prone and time-consuming activity, even for skilled cloud users and system administrators. In this context, this paper proposes a software product line engineering (SPLE) method and a tool to deal with these issues. Our SPL-based engineering method enables a declarative and goal-oriented strategy. Furthermore, it allows resource selection and configuration in inter-cloud environments. In our proposal, the cloud users specify their applications and requirements, and our tool automatically selects and configures a suitable computing environment, taking into account temporal and functional dependencies. Experimental results on Amazon EC2 and Google Compute Engine (GCE) show that our approach enables unskilled users to have access to advanced inter-cloud computing configurations, without being concerned with the characteristics of each cloud.

A product line refinement theory formalizes safe evolution in terms of a refinement notion, which does not rely on particular languages for the elements that constitute a product line. Based on this theory, we can derive refinement templates to support safe evolution scenarios. To do so, we need to provide formalizations for particular languages, to specify and prove the templates. Without a systematic approach, this leads to many similar templates and thus repetitive verification tasks. We investigate and explore similarities between these concrete languages, which ultimately results in a product line of theories, where different languages correspond to features, and products correspond to theory instantiations. This also leads to specifying refinement templates at a higher abstraction level, which, in the long run, reduces the specification and proof effort, and also provides the benefits of reusing such templates for additional languages plugged into the theory. We use the Prototype Verification System to encode and prove soundness of the theories and their instantiations. Moreover, we also use the refinement theory to reason about safe evolution of the proposed product line of theories.

The adoption of a product line strategy can bring significant productivity and time to market improvements. However, evolving a product line is risky because it might impact many products and their users. So when evolving a product line to introduce new features or to improve its design, it is important to make sure that the behavior of existing products is not affected. In fact, to preserve the behavior of existing products one usually has to analyze different artifacts, like feature models, configuration knowledge and the product line core assets. To better understand this process, in this paper we discover and analyze concrete product line evolution scenarios and, based on the results of this study, we describe a number of safe evolution templates that developers can use when working with product lines. For each template, we show examples of their use in existing product lines. We evaluate the templates by also analyzing the evolution history of two different product lines and demonstrating that they can express the corresponding modifications and then help to avoid the mistakes that we identified during our analysis.

Small and Medium Enterprises (SME) represent a significant percentage of software companies. Although there are some experience reports on using Software Product Line (SPL) techniques in SMEs, there is a lack of such reports on the Mobile Games domain. This domain is attractive both economically and technically, with a significant amount of variability, thus suggesting the use of a SPL approach. Accordingly, we conduct an exploratory study in a company in this domain, eliciting the main challenges, determining if and how SPL approaches help to address them, and raising hypotheses to guide future studies.

Summary form only given. The extractive and the reactive software product line (SPL) adoption strategies involve, respectively, bootstrapping existing products into a SPL and extending an existing SPL to encompass another product. In both cases, product line refactorings are useful to guide the SPL derivation process by extracting product variations and appropriately structuring them. They also help to assure the safety of the whole process by preserving SPL configurability. In this context, we describe FLiP, which is a suite of tools implemented as Eclipse plugins and has been designed and tested in the context of mobile game SPLs.

Domain analysis involves not only looking at standard requirements documents (e.g., use case specifications) but also at customer information packs, market analyses, etc. Looking across all these documents and deriving, in a practical and scalable way, a feature model that is comprised of coherent abstractions is a fundamental and non-trivial challenge. We conduct an exploratory study to investigate the suitability of Information Retrieval (IR) techniques for scalable identification of commonalities and variabilities in requirement specifications for software product lines. Accordingly, based on observations derived from industrial experience and on state-of-the-art research and practice, we also propose an initial framework, leveraging IR to systematically abstract requirements from existing specifications of a given domain into a feature model. We evaluate this framework, present a roadmap for its further extension, and formulate hypotheses to guide future work in exploring IR techniques for domain analysis.

Early aspects deal with crosscutting concerns in requirements analysis, domain analysis and architecture design [1]. Work on early aspects focuses on systematically identifying, modularizing, and analyzing such crosscutting concerns and their impact at the early phases of the software development life cycle.

Adoption strategies for Software Product Lines (SPL) frequently involve bootstrapping existing products into a SPL and extending an existing SPL to encompass another product. One way to do that is to use program refactorings. However, the traditional notion of refactoring does not handle appropriately feature models (FM), nor transformations involving multiple instances of the same SPL. For instance, it is not desirable to apply a refactoring into a SPL and reduce its configurability. In this paper, we extend the traditional notion of refactoring to an SPL context. Besides refactoring programs, FMs must also be refactored. We present a set of sound refactorings for FMs. We evaluate this extended refactoring definition for SPL in a real case study in the mobile games domain.

Porting is a critical task in mobile device game development. The high diversity of devices requires correspondingly customized versions of a single game. Managing the variabilities among these customized versions while exploring the latent game commonality cannot be solely addressed with a single technique. This paper contributes to this task by identifying and analyzing porting challenges, and by evaluating and contrasting existing approaches within industrial-strength case studies of J2ME games. Further, we present lessons learned, proposing more effective guidelines for this process, aiming at improving the quality of the resulting applications and porting process productivity.