Reviewerly/exHarmony huggingface dataset:
Kfeature: Rendering the Kconfig System into Feature Models

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

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

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

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

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

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

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?

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

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

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

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

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

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

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.
DataChest: a Constructive Data Physicalization Toolkit

Increasingly individuals use devices, diaries, or applications to track aspects of their lives. Visualizing diverse sets of data and exploring their relationships poses challenges when data is fragmented across different devices or sources. Constructive Physicalization offers an alternative approach by creating visualizations using tangible tokens, allowing for greater expressive freedom and a new visual mapping process. To address this, we developed DataChest. DataChest functions as a constructive data physicalization toolkit for self-tracking, enabling users to visualize and make sense of their data. Comprising of 1057 3D-printed components, including trays, tokens, and a guidebook. DataChest can be used to explore how individuals engage with their self-tracking data and gain insights into the effectiveness of different visualization approaches. Additionally, we introduce users to the toolkit by showcasing various data types and visualization expertise levels, reflecting different levels of toolkit complexity. Our insights are relevant for the development of constructive data physicalization toolkits.
Electronic Embedded Lace: A Sampler of Functional Interactive Tatting Techniques and Circuits

This paper presents an e-textile sampler of techniques embedding conductive thread and conventional electronic components in tatting lace. It has been proven that wires and connections to components can be made with the tatting structure of half-hitch knots around a foundational core thread. Structures for making components such as sensors entirely out of tatted lace made with conductive and insulating threads are proposed. Lace e-textiles are presented as appending existing garments with an embedded fabric to add functionality rather than replacement, providing opportunities for soft, deformable open lace structure textile interactions. At the event, the author aims to connect global lacemaking traditions and solicit contributions from the integrated textile community by demonstrating the tatting technique and samples of work.
A Phenomenological Approach to Enhancing Mixed Reality User Adoption for Improved Data Interpretation and Visualization in Digital Twin Environments

The ever-increasing availability, use and convergence of data, in the context of industry, means a holistic approach to understanding its potential and possible limitations is required to unlock greater insights and productivity. The objective of my proposed research is to investigate an individual user's experience when presented with visualized data through mixed reality (MR) as the chosen modality. More specifically, data from industrial contexts i.e., manufacturing process data, systems data, energy data, etc. Thus, an immersive digital twin (DT) through a holographic medium and user interface. The incorporation of neurophenomenology in the methodology with observations on objective neural processes as well as phenomenological methods can create a multi-layered approach which will enable the analysis of user experiences from subjective, behavioral, and neurological perspectives. It explores whether the experiential feedback impacts the user positively or negatively and whether that transition from conventional 2-dimensional (2D) monitor interface to immersive 3D holograms have a significant impact on the human user due to this modality change with MR offering visuospatial context.
Hand Thought: Craft-oriented hybrid analogue/digital practice and a Digital Craft Ethos

Exploring the boundaries/edges of analogue and digital making practices, Hand Thought is a hybrid making research project that originated from an ongoing interest in investigating the aesthetic opportunities that digital design and production technologies holds for the craftsperson. Alongside this motivation this project seeks to explore and demonstrate how a disruptive craft-based approach to engaging with digital making tools can act as a stimulus to reconsider the relationship between hand and machine, and our wider relationship with technologies and how we assess their role and value.
Are Conferences Sus?: Fostering Conversations on the Sustainability of HCI Conferences Through Data Physicalization

Against the backdrop of a climate crisis, HCI researchers and designers are reflecting upon, reconsidering, and re-imagining the work that we do through the lens of sustainability. In this Studio, we propose to adopt this critical perspective to Sustainable HCI through an examination and reflection on the environmental impact of research conferences. Our Studio builds upon our prior work that explored sustainable methods and toolkits for facilitating data physicalization workshops. We apply the tools and strategies developed through this prior work within a Studio in which participants are facilitated to engage with, reflect upon, and create with data relating to the sustainability of HCI conferences such as Tangible, Embedded and Embodied Interaction (TEI). Through the creation of data artefacts that can be displayed, worn, or shared throughout the conference beyond the Studio, we aim to spark wider conversations about the environmental sustainability of TEI2024, as well as HCI conferences more generally.
Hybrid Crochet: Exploring Integrating Digitally-Fabricated and Electronic Materials with Crochet

Human-computer interaction research with yarn-based crafts has concentrated on those that can be done by machine, like knitting and weaving. Crochet, on the other hand, has received little attention in HCI, because it cannot be automated. We explore integrating both electronics and digitally-fabricated materials—like 3D prints—into handcrafted crochet objects. We use 3D printed structures to guide crochet stitches by constraining stitch sizes and placement, and infill patterns to change the works' form, stiffness, and appearance. We also explore printed ring structures that bridge soft crochet and hard electronics, and whether different conductors can be crocheted. We demonstrate combining these primitives to build crocheted input devices like buttons and an interactive octopus. Our techniques can help crafters design and create interactive crochet objects.
Knitting Interactive Spaces: Fabricating Data Physicalizations of Local Community Visitors with Circular Knitting Machines

Innovations in digital fabrication technologies are increasingly enabling artists and designers to create data physicalizations in real time. In this paper, we discuss how we adapted a circular knitting machine to physicalize visitors at a local art gallery during the pandemic recovery year. To evaluate this year-long installation, we conducted design critiques with 15 individuals including those who worked in the building and lived alongside it for a year, as well as subject matter experts. We then iteratively worked with 11 of those individuals to gain insights for re-deploying the visualization for interpretation. Overall, this paper contributes long-term reflections and recommendations for using digital fabrication for real-time data physicalizations.