A5024243792- Advanced Software Engineering Methodologies
- Service-Oriented Architecture and Web Services
- Software Engineering Research
- Software Engineering Techniques and Practices
- Software System Performance and Reliability
- Business Process Modeling and Analysis
- Flexible and Reconfigurable Manufacturing Systems
- Model-Driven Software Engineering Techniques
- Product Development and Customization
- Digital Transformation in Industry
- Manufacturing Process and Optimization
- Software Reliability and Analysis Research
- Systems Engineering Methodologies and Applications
- Semantic Web and Ontologies
- Safety Systems Engineering in Autonomy
- Software Testing and Debugging Techniques
- Cloud Computing and Resource Management
- Real-Time Systems Scheduling
- Formal Methods in Verification
- Fault Detection and Control Systems
- Data Stream Mining Techniques
- Scientific Computing and Data Management
- Data Visualization and Analytics
- Multimedia Communication and Technology
- Usability and User Interface Design
Johannes Kepler University of Linz
2015-2024
Chalmers University of Technology
2018-2022
Izmir Institute of Technology
2018-2022
University of Gothenburg
2019-2022
Volvo (Sweden)
2022
Sea Education Association
2022
Imperial College London
2021
Universidad de Málaga
2021
Swinburne University of Technology
2021
Institute Unic
2021
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....
It has been shown that product line engineering can significantly improve the productivity, quality and time-to-market of software development by leveraging extensive reuse. Variability models are currently most advanced approach to define, document manage commonalities variabilities reusable artifacts such as components, requirements, test cases, etc. These provide basis for automating derivation new products thus key artifact leverage flexibility adaptability systems in a line. Among...
Feature modelling is a cornerstone of software product line engineering, providing means to represent variability through features and their relationships. Since its inception in 1990, feature has evolved various extensions, after three decades development, there growing consensus on the need for standardised language. Despite multiple endeavours standardise creation textual languages, researchers practitioners continue use own approaches, impeding effective model sharing. In 2018,...
Product derivation is the process of constructing products from core assets in a product line. Guidance and support are needed to increase efficiency deal with complexity derivation. Research has, however, devoted comparatively little attention this process. In paper we describe an approach for supporting We show that variability models need be prepared concrete projects before they can effectively utilized Project-specific information sales knowledge should added irrelevant pruned. also...
Cyber-Physical Production Systems (CPPSs) are envisioned as next-generation adaptive production systems combining modern techniques with the latest information technology. A CPPS creates a complex environment between different domains (mechanical, electrical, software engineering), requiring multidisciplinary solutions to tackle growing complexity issues and reduce (maintenance) effort. Software plays an increasingly important role in assuring effective efficient operation of CPPSs. However,...
The complexity of product line variability models makes it hard to maintain their consistency over time regardless the modeling approach used. Engineers thus need support for detecting and resolving inconsistencies. We describe experiences applying a tool-supported incremental checking on models. Our significantly improves overall performance scalability compared batch-oriented techniques allows providing immediate feedback modelers. It is extensible as new constraints can easily be added....
Software systems are nowadays often configured by sales people, domain experts, or even customers instead of engineers. Configuration tools communicate the systems' variability to these end users and provide guidance for selecting customizing available features. However, if a configuration tool creates technically correct systems, addressing specific needs business-oriented remains challenging. We analyze existing identify key capabilities guiding discuss using cognitive dimensions notations...
Variability models are commonly used to model commonalities and variability in a product line. There is large variety of textual formats represent store models. This causes overhead researchers practitioners as they frequently need translate The MODEVAR initiative consists dozens aims find unified language for modeling. In this work, we describe the cooperative development language. We evaluate preferences community regarding properties existing applications an initial design Then, examine...
An increasing number of software systems today are very-large-scale (VLSS) with system-of-systems (SoS) architectures. Due to their heterogeneity and complexity VLSS difficult understand analyze, which results in various challenges for development evolution. Existing engineering processes, methods, tools do not sufficiently address the characteristics VLSS. Also, there only a few empirical studies on We report an exploratory case study involving engineers technical project managers...
Software-intensive Cyber-Physical Production Systems (SiCPPS), like metallurgical plants or manufacturing plants, are highly variable systems of that frequently evolve. They typically involve a large number heterogeneous components (mechanical, electrical, mechatronic, software) can be configured and combined in different ways. Variability results not only from hardware software but also development processes, disciplines engineering), methods, tools. Dealing with variability industry...
Cyber-Physical Production Systems (CPPSs) are complex systems comprised of software and hardware interacting with each other the environment. In industry, over time, a plethora CPPSs developed to satisfy varying customer requirements changing technologies. Managing variability is challenging, especially in multidisciplinary environments like CPPS engineering. For instance, when supporting automatic derivation configuration control software, one needs understand from not only perspective, but...
Cyber-Physical Production Systems (CPPSs), such as automated car manufacturing plants, execute a configurable sequence of production steps to manufacture products from product portfolio. In CPPS engineering, domain experts start with manually determining feasible step sequences and resources based on implicit knowledge. This process is hard reproduce highly inefficient. this paper, we present the Extended Iterative Process Sequence Exploration (eIPSE) approach derive variability models for...