SPLC

Feature modeling is a technique to model the variability of configurable systems. When working with feature models, it is possible to analyze them, for instance, by counting the number of valid configurations, searching feature model anomalies, or ...

Programming variability is central to the design and implementation of software systems that can adapt to a variety of contexts and requirements, providing increased flexibility and customization. Managing the complexity that arises from having multiple ...

Feature models are the "de facto" standard for representing variability in software-intensive systems. Automated analysis of feature models is the computer-aided extraction of information of feature models and is used in testing, maintenance, ...

In many applications of Computational Science and especially Data Science, notebooks are the cornerstone of knowledge and experiment sharing. Their diversity is multiple (problem addressed, input data, algorithm used, overall quality) and is not made ...

The planning, realization, and release of a Software Product Line (SPL) are driven by features. Therefore, many high-level decisions about the evolution of an SPL are made at the feature level. However, a feature can involve many stakeholders with ...

We introduce a new logic for expressing multi-properties of system families (Software Product Lines - SPLs). While the standard LTL logic refers only to a single trace at a time, fMultiLTL logic proposed here refers to multiple traces originating from ...

The development of feature-oriented programming (FOP) and of (its generalization) delta-oriented programming (DOP) has focused primarily on SPLs of class-based object oriented programs. In this paper, we introduce delta-oriented SPLs of functional ...

Software functional equivalence checking is a technique for analyzing the impact of change of a portion of code on the rest of the system. The existing functional equivalence checking approaches are applicable only at the individual software product ...

Ensuring the quality of Highly Configurable Systems (HCSs) during its evolution and maintenance is challenging. As an HCS evolves, new features are added, changed, or removed, which makes the test case selection for regression testing a difficult task. ...

Quality assurance for highly configurable systems uses t-wise feature interaction coverage as a metric to measure the quality of selected samples for testing. Achieving t-wise feature interaction coverage requires testing many configurations, often ...

Cross-tree constraints give feature models maximal expressive power since any interdependency between features can be captured through arbitrary propositional logic formulas. However, the existence of these constraints increases the complexity of ...

The development and maintenance of feature models is often an error-prone activity requiring different types of analysis operations that help developers to restore required feature model properties. Fulfilling such properties helps to assure compliance ...

Model management frameworks support a wide array of analyses, transformations, and workflows, but lack native support for handling product lines of models. Yet the ubiquity of domains that heavily use model-driven techniques and are built using product ...

Developers use version-control systems and software-hosting platforms to manage their software systems. They rely on the provided branching and forking mechanisms to implement new features, fix bugs, and develop customized system variants. A particular ...

Software systems are subject to frequent changes, for example to fix bugs or meet new customer requirements. In variational software systems, developers are confronted with the complexity of evolution and configurability on a daily basis; essentially ...

Software product-line engineering is concerned with developing a set of similar, yet customized, software systems that share a common codebase. To develop such a variant-rich system, various development processes, techniques, and tools have been studied ...

Today's manufacturing industry is confronted with an increasing demand for product variability that stems from product customisation needs and the engineering process. Different customer demands and the mass-customisation of physical products require ...

The products of the automotive industry are facing one of the biggest changes: becoming digital smart devices on wheels. Driven by the rising amount of vehicle functions, electronic control units, and software, today's vehicles are becoming cyber-...

Software variants of a Software Product Line (SPL) consist of a set of artifacts specified by features. Variability models document the valid relationships between features and their mapping to artifacts. However, research has shown inconsistencies ...

Software Product Lines (SPL) support the development of families of software products that share a set of core assets but differ in certain features. To generate a new product, the engineer selects the desired features and the SPL assembles and adapts ...

Many software systems require diverse data gathering and handling through processes that manipulate tabular data, often with a spreadsheet orientation. Variability in tabular data cannot be captured in a complete up-front analysis as everything is done ...

This paper provides a detailed testing strategy for Software Product Lines (SPLs), aiming to balance the variability offered with its associated cost. Utilizing feature modeling, combinatorial testing, and deployment-based testing, the strategy addresses ...

Cyber-Physical Production Systems (CPPSs) are highly robust and versatile production systems that utilize diverse hardware components through control software. Employing a systematic variability management approach for developing variants of control ...

This paper reports an industrial experience of managing the variability of a logistics robot system. Logistics centers need to dispatch products rapidly and accurately from huge inventories in accordance with the daily flow of orders, and autonomous ...

Testing is a fundamental verification activity to produce high-quality software. However, testing is a costly and complex activity. The success of software testing depends on the quality of test cases but finding a good set of test cases is laborious. ...

Managing variants, versions, and variability in system-level engineering is becoming increasingly important in industry and represents a challenge for model-based systems engineering.

With this paper, we want to raise awareness that guidance and decision ...

Highly configurable software systems play crucial roles in real-world applications, which urgently calls for useful testing methods. Combinatorial interaction testing (CIT) is an effective methodology for detecting those faults that are triggered by the ...

Automata learning is a fundamental techique for building behavioral models by actively interacting with black-box systems. Through four decades of research the community has come up with many algorithms and tools for automata learning, of which this ...