Reviewerly/exHarmony huggingface dataset:
Partial Proofs to Optimize Deductive Verification of Feature-Oriented Software Product Lines

Authors:
raw_author_name: Maximilian Kodetzki
raw_affiliation_string: Karlsruhe Institute of Technology, Germany
raw_author_name: Tabea Bordis
raw_affiliation_string: Karlsruhe Institute of Technology, Germany
raw_author_name: Tobias Runge
raw_affiliation_string: Karlsruhe Institute of Technology, Germany
raw_author_name: Ina Schaefer
raw_affiliation_string: Karlsruhe Institute of Technology, Germany

Abstract: Software product lines (SPLs) are a technique to efficiently develop families of software products. Code is implemented in functional features which are composed to individual software variants. SPLs are oftentimes used in safety-critical systems, which is why functional correctness is more important than ever. As an advanced approach, deductive verification offers the possibility to verify the behaviour of software against a formal specification. When deductive verification is applied for SPLs, it meets the challenges of an SPLs variability. Since most verification approaches do not scale for variant-rich product lines, we take up existing approaches of reuse of proof parts to develop our concept of partial proofs. We split proofs into a feature-specific and a product-specific part. The feature-specific part is only proven once for all products enabling advanced proof reuse. We implement our concept of partial proofs in the tool VarCorC and evaluate it on three case studies. We found that both the number of proof steps and the verification time can be reduced by using partial proofs. Further, we determine a trend of increasing improvements of verification costs for large-scale SPLs.
Kfeature: Rendering the Kconfig System into Feature Models

Authors:
raw_author_name: Jan Willem Wittler
raw_affiliation_string: Independent Researcher, Germany
raw_author_name: Christopher Gerking
raw_affiliation_string: Karlsruhe Institute of Technology (KIT), Germany

Abstract: Kconfig is a prominent configuration system that helps manage variability of software such as the Linux kernel. To make such software accessible to feature-oriented analysis, it is desirable to transform Kconfig into equivalent feature models. In this paper, we address the problem that existing transformations do either not cover an essential part of the Kconfig language constructs, or fail to produce human-readable feature models. We address both limitations by drawing up practical guidelines for the transformation, and enable feature-oriented analysis in terms of Kfeature as a tool interface of the FeatureIDE framework. To evaluate the semantic equivalence, we apply Kfeature to synthesized variability definitions.
Managing Customizable User Interface for Web Application Product Lines using Delta Modeling

Authors:
raw_author_name: Hafiyyan Sayyid Fadhlillah
raw_affiliation_string: CDL VaSiCS, LIT CPS Lab, Johannes Kepler University Linz, Austria
raw_author_name: Maya Retno Ayu Setyautami
raw_affiliation_string: Faculty of Computer Science Universitas Indonesia, Indonesia
raw_author_name: Eko Kuswardono Budiardjo
raw_affiliation_string: Faculty of Computer Science Universitas Indonesia, Indonesia

Abstract: In web application development, engineers must implement the User Interface (UI) using diverse implementation artifacts such as HTML, CSS, and JavaScript. Employing a Model-Driven Engineering (MDE) for developing UI may reduce the development effort by automatically generating these artifacts. Additionally, we can combine an MDE approach with Software Product Line (SPL) concepts to model and generate UI variants automatically. However, UI development is a complex and multi-faceted problem. The UI must satisfy the customer preferences for various aspects (e.g., coloring scheme, choice of UI elements, and layouts) while also having a good usability level. Purely generated UI is often unable to comply with these requirements and thus forces the engineers to develop the UI manually instead. In this paper, we proposed an approach for managing customizable UI variants in the context of a web application product line. Our approach uses Interaction Flow Modeling Language (IFML) to model web application UI. Additionally, we define a delta modeling extension for IFML to support modeling UI variants. We implement a tool support that allows engineers to use our approach for modeling and generating UI variants. The tool support also provides a mechanism for UI customization based on developing a set of interchangeable interface styles. We evaluated the feasibility of our approach by applying it to three case studies and conducted a questionnaire survey to assess the usability of the generated UI variants. Our evaluation results show that our approach can be a good starting point to manage UI variants with good usability.
Incremental Identification of T-Wise Feature Interactions

Authors:
raw_author_name: Sebastian Krieter
raw_affiliation_string: University of Ulm, Germany
raw_author_name: Tobias Heß
raw_affiliation_string: University of Ulm, Germany
raw_author_name: Thomas Thüm
raw_affiliation_string: University of Ulm, Germany
raw_author_name: Malte Lochau
raw_affiliation_string: University of Siegen, Germany

Abstract: Developers of configurable software use the concept of selecting and deselecting features to create different variants of a software product. In this context, one of the most challenging aspects is to identify unwanted interactions between those features. Due to the combinatorial explosion of the number of potentially interacting features, it is currently an open question how to systematically identify a particular feature interaction that causes a specific fault in a set of software products. In this paper, we propose an incremental approach to identify such t-wise feature interactions based on testing additional configurations in a black-box setting. We present the algorithm Inciident, which generates and selects new configurations based on a divide-and-conquer strategy to efficiently identify the feature interaction with a preferably minimal number of configurations. We evaluate our approach by considering simulated and real interactions of different sizes for 48 real-world feature models. Our results show that on average, Inciident requires 80 % less configurations to identify an interaction than using randomly selected configurations.
Explaining Edits to Variability Annotations in Evolving Software Product Lines

Authors:
raw_author_name: Paul Maximilian Bittner
raw_affiliation_string: Institute of Software Engineering and Programming Languages, University of Ulm, Germany
raw_author_name: Ina Schaefer
raw_affiliation_string: TVA, Karlsruhe Institute of Technology, Germany
raw_author_name: Thomas Thüm
raw_affiliation_string: Institute of Software Engineering and Programming Languages, University of Ulm, Germany

Abstract: Software is subject to changes and revisions during its development life cycle. For configurable software systems, changes may be made to functionality of source code as well as variability information such as code-to-feature mappings. To explain how code-to-feature mappings change in edits made to configurable software, we relate the mappings before and after an edit in terms of the sets of variants they denote. We prove our explanations to be complete and unambiguous, meaning that every pair of code-to-feature mappings is explained in terms of exactly one relation. Based on a graph formalism, we provide an algorithm for fast detection of relations during commits to version control. In an initial study, we detect relations between feature annotations in 42 real-world software product-line repositories to better understand typical changes in the evolution of configurable software. We demonstrate that our formalism can be automated and that analyzing a commit requires only 135 ms on average.
A Practitioners Perspective on Addressing Cyber Security and Variability Challenges in Modern Automotive Systems

Authors:
raw_author_name: Philipp Zellmer
raw_affiliation_string: Volkswagen AG, Germany and Harz University of Applied Sciences, Germany
raw_author_name: Lennart Holsten
raw_affiliation_string: Volkswagen AG, Germany and Harz University of Applied Sciences, Germany
raw_author_name: Richard May
raw_affiliation_string: Harz University of Applied Sciences, Germany
raw_author_name: Thomas Leich
raw_affiliation_string: Harz University of Applied Sciences, Germany

Abstract: Modern cars are becoming increasingly software-driven and interconnected, including new innovative functions, such as over-the-air updates. Such functions are typically based on configurable features, making adequate variability management essential. However, the growing system complexity based on connectivity and variability leads to various risks in the context of cyber security. As a result, legal regulations, such as UNECE No. 155, are constantly being developed, involving guidelines to handle security-critical components within automotive electrics/electronics architectures. In this paper, an overview of current cyber-security challenges in the automotive domain is provided, focusing on their impacts on variability management. We share insights regarding the level of cyber-security relevance, connectivity, regulations, and software maintenance. Additionally, we propose seven practice-oriented strategies tailored to address these challenges, based on our expertise, with the goal of handling variability and increasing software quality. With our findings, we aim to guide researchers and practitioners dealing with the complexities of cyber security and variability in both the automotive and other cyber-physical domains.
Variability in data transformation: towards data migration product lines

Authors:
raw_author_name: David Benavides
raw_affiliation_string: University of Seville, Spain
raw_author_name: Jose-Miguel Horcas
raw_affiliation_string: Computer Science and Programming Languages, University of Malaga, Spain
raw_author_name: María Teresa Gómez-López
raw_affiliation_string: University of Seville, Spain

Abstract: Software evolution often requires data management and more concretely data migration. Data migration follows an ETL process: extracting (E) data from a source, transforming (T) the data depending on migration needs, and loading (L) the data in a target data storage. Data migration projects are recognised to be complex and challenging to manage, which can lead to resource loss and planning delays. Among the reasons for data migration project failure is the lack of systematic artifact reuse (e.g., transformation script) in the data migration process. Every new data migration project is often developed from scratch. Software product line (SPL) engineering has been applied in many different domains to systematically reuse artifacts (e.g., code platforms, test cases) in software development processes and there are many positive experiences when applying SPL to reduce cost and time. In this paper, we present an approach using SPL techniques for data migration projects, concretely, in the data transformation stage. Our solution facilitates the automated creation of scripts that can be reused in different data migration projects. The feasibility of the proposal is validated in the domain of web information systems modernization. The validation shows how various migration scripts can be created to transform data between different content management systems. With this work, new opportunities are opened for studying the synergies of SPL and data migration. To the best of our knowledge, this is the first proposal that uses a complete stack of SPL that materializes the reuse of artifacts for data migration.
Grammars for Feature Models

Authors:
raw_author_name: Domenik Eichhorn
raw_affiliation_string: Institute of Information Security and Dependability, Karlsruhe Institute of Technology, Germany

Abstract: Applications for feature models, such as sampling, usually involve exploring a decision structure to systematically generate product configurations. This decision structure is often learned implicitly, using SAT solvers, or explicitly by describing it in the form of a binary decision diagram. Another structure, context-free grammars, have only been discussed for constraint-free feature models. We outline two algorithms that allow the transformation of feature models into context-free grammars and argue that, though those initial algorithms do not perform well, context-free grammars show promising potential for optimizations.
How Easy is SAT-Based Analysis of a Feature Model?

Authors:
raw_author_name: Elias Kuiter
raw_affiliation_string: University of Magdeburg, Germany
raw_author_name: Tobias Heß
raw_affiliation_string: University of Ulm, Germany
raw_author_name: Chico Sundermann
raw_affiliation_string: Institute of Software Engineering and Programming Languages, University of Ulm, Germany
raw_author_name: Sebastian Krieter
raw_affiliation_string: Institute of Software Engineering and Programming Languages, University of Ulm, Germany
raw_author_name: Thomas Thüm
raw_affiliation_string: University of Ulm, Germany
raw_author_name: Gunter Saake
raw_affiliation_string: University of Magdeburg, Germany

Abstract: With feature-model analyses, stakeholders can improve their understanding of complex configuration spaces. Computationally, these analyses are typically reduced to solving satisfiability problems. While this has been found to perform reasonably well on many models, estimating the efficiency of a given analysis on a given model is still difficult. We argue that such estimates are necessary due to the heterogeneity of feature models. We discuss inherently influential factors and suggest potential algorithmic solutions.
Vulnerably (Mis)Configured? Exploring 10 Years of Developers' Q&amp;As on Stack Overflow

Authors:
raw_author_name: Richard May
raw_affiliation_string: Harz University of Applied Sciences, Germany
raw_author_name: Kai Ludwig
raw_affiliation_string: Landesamt für Geoinformation und Landesvermessung Niedersachsen, Germany
raw_author_name: Jacob Krüger
raw_affiliation_string: Eindhoven University of Technology, Netherlands
raw_author_name: Thomas Leich
raw_affiliation_string: Harz University of Applied Sciences, Germany

Abstract: The increasing number of attacks exploiting system vulnerabilities in recent years underpins the growing importance of security; especially for software comprising configuration options that may cause unintended vulnerabilities. So, not surprisingly, developers discuss secure software configurations extensively, for instance, via community-question-answering systems like Stack Overflow. In this exploratory study, we analyzed 651 Stack Overflow posts from 2013 until 2022 to investigate what vulnerabilities in the context of configuring software developers discuss. We employed a manual data analysis and automated topic modeling using Latent Dirichlet Allocation to identify and classify relevant topics and contexts. Our results show that vulnerabilities in the context of configuring receive more and more interest, with most posts discussing issues related to faulty security configurations and dependencies causing vulnerabilities that could be or have actually been exploited. Overall, we contribute insights into configuration and security issues that developers experience in the real world. Such insights help researchers and practitioners understand and resolve these issues, thereby guiding future improvements.
On Configuration Sequences in Feature Models

Authors:
raw_author_name: Kristof Meixner
raw_affiliation_string: Institute of Information Systems Engineering - Software Engineering, TU Wien, Austria and CDL-SQI, TU Wien, Austria
raw_author_name: Kevin Feichtinger
raw_affiliation_string: Karlsruhe Institute of Technology, Germany
raw_author_name: Sandra Greiner
raw_affiliation_string: Institute of Computer Science, University of Bern, Switzerland
raw_author_name: Rick Rabiser
raw_affiliation_string: CDL VaSiCS, LIT CPS Lab, Johannes Kepler University Linz, Austria

Abstract: Feature models are the de-facto standard in product line engineering to capture the commonalities and variability of systems. However, feature models provide little user guidance during configuration and are unable to represent configuration sequences. A configuration sequence refers to the specific order and combination of features that can be selected when configuring a product line. While mechanisms, such as staged configuration and configuration workflows, exist, we argue that the effort to implement these mechanisms does not pay off for small feature models. This paper motivates the use of configuration sequences for feature models to support better user guidance even for a single feature model. We highlight the need for such user guidance and configuration sequences with a real-world use case.
Quantum secure ranking based on quantum walks

Authors:
raw_author_name: Justin Joseph
raw_affiliation_string: Visvesvaraya National Institute of Technolgy, Nagpur, India
raw_author_name: Syed Taqi Ali
raw_affiliation_string: Visvesvaraya National Institute of Technolgy, Nagpur, India

Abstract: Abstract We propose a quantum secure multiparty multidata ranking (QSMMR) protocol based on quantum walks. Our protocol improves the traditional anonymous ranking protocol to secure ranking, where we ensure the confidentiality of the data. A quantum anonymous ranking protocol exposes all participants’ data, which is not ideal for practical scenarios such as personal wealth and health indexes. Hence, we propose the first quantum secure ranking protocol with semi-honest TP, that generates ranking for multiple data of multiple participants by keeping data completely secure. We use quantum resources to assign a random address to all participants, to perform comparison, and for the eavesdropper detection. Finally, we analyze and prove the security of the protocol.
Spectral mixture analysis of intimate mixtures for lithological mapping

Authors:
raw_author_name: Archana M. Nair
raw_affiliation_string: Earth System Science and Engineering Group, Department of Civil Engineering, Indian Institute of Technology Guwahati, Assam, India

Abstract: Spectral mixing is frequently encountered in remotely sensed images while imaging heterogeneous surfaces. Spectral mixing occurs at the macroscopic level due to the sensor's low spatial resolution or multiple reflections from materials received by the sensor. Due to the mixing effect, retrieving the information of spectral endmembers becomes complicated. In this study, two different unmixing methods: (i) linear mixing models (LMM) and (ii) the Hapke nonlinear mixing model, were used to quantitatively estimate the fractional abundance of various rock types that will be helpful in remotely mapping the mineral prospects. Three types of constraints using the least square approach were applied independently to LMM and Hapke models, namely FCLS (sum to unity and nonnegativity constrained), NNLS (nonnegativity constrained), and UCLS (unconstrained). AVIRIS-NG (Airborne Visible and InfraRed Imaging Spectrometer-Next Generation) and ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer) images from the Sittampundi anorthosite complex (SAC) were utilised for the spectral mixture analysis. Few studies are available on the anorthosite rocks of Sittampundi as an analogue to the Lunar anorthosite. The study area is known for its chromite deposits occurring in pyroxenite rocks. Therefore, in the present study, endmembers considered are anorthosite and pyroxenite/metagabbro. The moderately dense vegetation cover of the study area obscures the detection of rock outcrops on the surface. The study area exhibits nonlinear spectral mixing effects due to the vegetation cover. Hence apart from the two rock endmembers, vegetation is also considered as an endmembers in spectral mixture analysis. The results show a high fractional abundance of vegetation and anorthosite throughout the study region, with the pyroxenite/metagabbro mainly concentrated over the western and eastern regions. The Hapke model shows more accurate results than LMM on the AVIRIS-NG image. The Hapke model outperforms LMM in accurately retrieving the fractional abundance of endmembers due to the nonlinear spectral mixing effects caused by vegetation. Additionally, the constrained least squares methods, i.e., FCLS and NNLS, performed better than UCLS in linear and nonlinear mixing models, resulting in accurate and reliable abundance maps. AVIRIS-NG outperformed the ASTER images in fractional abundance mapping of endmembers, highlighting the importance of utilising higher spatial and spectral resolution data for more reliable land cover and lithology mapping. Overall, this study demonstrates the potential of spectral mixture analysis in identifying geologic outcrops in vegetation-covered regions. Hence, the methodology presented in this study benefits the lithological mapping of vegetation-covered regions and has wide applications in quantitatively assessing the lithology of mineral prospects.
Crafting Electronic Textiles as a Participatory Design Material for Slowing Down

Authors:
raw_author_name: Anna Blumenkranz
raw_affiliation_string: Artificial Intelligence and Human Interfaces, University of Salzburg, Austria

Abstract: To counteract the fast-paced and efficiency-driven nature of technological development, Slow Technology philosophy calls for designing technology for reflection and mental rest. However, its focus lies mainly on interaction with artifacts on the user side. There is a lack of understanding of how applying this philosophy can influence designers and shape design processes. The goal of my PhD is to investigate notions of slowing down within participatory design processes through the lens of handcrafting with e-textiles, to uncover alternative design strategies for envisioning future technologies. To achieve this, I will probe slowing-down properties of crafts like state of flow, rhythm, and repetitiveness that have a peaceful and relaxing effect. I will apply these qualities to participatory design processes, allowing time for creativity, reflection, and diverse paths of participation. My findings will provide an understanding of how temporal affordances of e-textiles can shape PD processes, and offer strategies to facilitate and document slow design processes.
Tensions and Resolutions in Hybrid Basketry: Joining 3D Printing and Handweaving

Authors:
raw_author_name: Lea Albaugh
raw_affiliation_string: Human-Computer Interaction Institute, Carnegie Mellon University, United States
raw_author_name: Scott E Hudson
raw_affiliation_string: Human-Computer Interaction Institute, Carnegie Mellon University, United States

Abstract: By documenting and annotating one author's ongoing project combining 3D printing and handweaving to produce computational hybrid baskets, we contribute a framework for understanding hybrid craft. We identify three levels of material practice as observed in the basketry project—physical joinery between rigid printed-plastic parts and soft textiles, seamful multipart fabrication workflows, and aesthetics which negotiate between "basketlike" and "computational" forms—and analyze tensions and possible resolutions at each level.