Over more than two decades, numerous variability modeling techniques have been introduced in academia and industry. However, little is known about the actual use of these techniques. While dozens experience reports on software product line engineering exist, only very few focus modeling. This lack empirical data threatens validity existing techniques, hinders their improvement. As part our effort to improve understanding modeling, we present results a survey questionnaire distributed...

Variability modeling is essential for defining and managing the commonalities variabilities in software product lines. Numerous variability approaches exist today to support domain application engineering activities. Most are based on feature (FM) or decision (DM), but so far no systematic comparison exists between these two classes of approaches. Over last decades many new features have been added both FM DM it tough decide which approach use what purpose. This paper clarifies relation DM....

Feature models describe the common and variable characteristics of a product line. Their advantages are well recognized in line methods. Unfortunately, creating feature model for an existing project is time-consuming requires substantial effort from modeler.

Feature modeling is a notation and an approach for commonality variability in product families. In their basic form, feature models contain mandatory/optional features, groups, implies excludes relationships. It known that such can be translated into propositional formulas, which enables the analysis configuration using existing logic- based tools. this paper, we consider opposite translation problem, is, extraction of from formulas. We give automatic efficient procedure computing model...

Feature models are a popular variability modeling notation used in product line engineering. Automated analyses of feature models, such as consistency checking and interactive or offline selection, often rely on translating to propositional logic using satisfiability (SAT) solvers.Efficiency individual satisfiability-based has been reported previously. We generalize quantify these studies with series independent experiments. show that previously efficiency is not incidental. Unlike the...

Configurable software systems allow stakeholders to derive program variants by selecting features. Understanding the correlation between feature selections and performance is important for be able a variant that meets their requirements. A major challenge in practice accurately predict based on small sample of measured variants, especially when features interact. We propose variability-aware approach prediction via statistical learning. The works progressively with random samples, without...

Variability models represent the common and variable features of products in a product line. Since introduction FODA 1990, several variability modeling languages have been proposed academia industry, followed by hundreds research papers on modeling. However, little is known about practical use such languages. We study constructs, semantics, usage, associated tools two languages, Kconfig CDL, which are independently developed outside used large significant software projects. analyze 128 found...

A specification theory combines notions of specifications and implementations with a satisfaction relation, refinement relation set operators supporting stepwise design.We develop complete framework for real-time systems using Timed I/O Automata as the formalism, semantics expressed in terms Transition Systems.We provide constructs refinement, consistency checking, logical structural composition, quotient -all indispensable ingredients compositional design methodology.The is implemented on...

Variability models represent the common and variable features of products in a product line. Several variability modeling languages have been proposed academia industry; however, little is known about practical use such languages. We study compare constructs, semantics, usage tools two languages, Kconfig CDL. provide empirical evidence for real-world concepts from research. Since basis automated (feature dependency checkers configurators), we believe that our findings will be interest to...

Feature-sensitive verification pursues effective analysis of the exponentially many variants a program family. However, researchers lack examples concrete bugs induced by variability, occurring in real large-scale systems. Such collection is requirement for goal-oriented research, serving to evaluate tool implementations feature-sensitive analyses testing them on bugs. We present qualitative study 42 variability collected from bug-fixing commits Linux kernel repository. analyze each bugs,...

Autonomous robots combine skills to form increasingly complex behaviors, called missions. While are often programmed at a relatively low abstraction level, their coordination is architecturally separated and expressed in higher-level languages or frameworks. State machines have been the go-to language model behavior for decades, but recently, trees gained attention among roboticists. Originally designed autonomous actors computer games, offer an extensible tree-based representation of...

Feature modeling is a notation and an approach for commonality variability in product families. In their basic form, feature models contain mandatory/optional features, groups, implies excludes relationships. It known that such can be translated into propositional formulas, which enables the analysis configuration using existing logic- based tools. this paper, we consider opposite translation problem, is, extraction of from formulas. We give automatic efficient procedure computing model...

Feature modeling is used in generative programming and software product-line engineering to capture the common variable properties of programs within an application domain. The translation feature models propositional logics enabled use reasoning systems, such as BDD engines, for analysis transformation interactive configurations. Unfortunately, size a structure highly sensitive ordering its construction inappropriately chosen may prevent model into representation tractable size. Finding...

We present probabilistic feature models (PFMs) and illustrate their use by discussing modeling, mining interactive configuration. PFMs are formalized as a set of formulas in certain logic. Such can express both hard soft constraints have well defined semantics denoting joint probability distributions over features. show how be mined from given configurations using data techniques. Finally, we demonstrate used configuration order to provide automated support for choice propagation based on...

Cloning is widely used for creating new product variants. While it has low adoption costs, often leads to maintenance problems. Long term reliance on cloning discouraged in favor of systematic reuse offered by line engineering (PLE) with a central platform integrating all reusable assets. Unfortunately, adopting an integrated requires risky and costly migration. However, industrial experience shows that some benefits can be achieved properly managing set cloned

The tutorial will present the outcome of work done by Joint Submission Team against Request For Proposals for a Common Variability Language issued OMG (Object Management Group). language and experiments some consortium members on tools supporting preliminary CVL.