The Role of Design in interdisciplinary Product Development – Challenges, Research Approaches and Further Research needs - Stöhr, Bernd; Koldewey, Christian; Dumitrescu, Roman (Proceedings of the Design Society)
Abstract In global competition, companies are continuously searching for a competitive advantage. A growing number of companies have identified the design of their products as a major success factor. The promises for companies associated with outstanding design are extremely attractive, ranging from better customer experience to higher sales growth. But even though the advantages of design seem to be compelling, companies are still having difficulties in leveraging the benefits of design. In this paper, we want to identify the underlying challenges that explain this gap. We are especially interested in the role and challenges of design in interdisciplinary product development. Therefore, we perform a literature review that clarifies terminology, analyses research approaches and identifies challenges. We determine seven key challenges for design in interdisciplinary product development. Furthermore, we observe a limited scope of research approaches in the reviewed literature. Based on these findings, we propose three further research directions to strengthen the role of design in interdisciplinary product development in the future.

Designing Business Models for a Circular Economy - Scholtysik, Michel; Rohde, Malte; Koldewey, Christian; Dumitrescu, Roman (Proceedings of the Design Society)
Abstract The megatrend sustainability will significantly change the future value creation of manufacturing companies. Their current linear value creation models need to change to conform to the requirements of sustainability. To face the challenges the circular economy has emerged as a promising economic model. With the shift from a linear to a circular economy, companies have to adjust their current business models. However, they still lack knowledge and adequate methods to develop circular business models. Hence, the aim of the paper is a circular business model canvas (CBMC) for designing circular businesses. A systematic literature review was conducted to identify significant criteria for circular business models. The criteria were analyzed utilizing a qualitative content analysis to derive the business model elements required for the circular economy. Existing elements from the Business Model Canvas were enriched and five new elements, e.g., reverse logistics, were found. Then, the business model elements were logically arranged resulting in the CBMC. It guides companies to systematically develop business models for the circular economy. The CBMC was evaluated by applying it within a mediumsized company in the electronics sector.

Model-based Systems Engineering using Security Design Patterns in the Context of ISO/SAE 21434 - Japs, Sergej; Faheem, Faizan; Anacker, Harald; Husung, Stephan; Dumitrescu, Roman (Proceedings of the Design Society)
Abstract The development of modern vehicles is complex, especially regarding compliance with security and safety. ISO/SAE 21434 considers security and safety along the entire product life cycle. According to the standard, a system architecture, a risk analysis, and the application of countermeasures are carried out in the early system design. Design patterns are solutions to known design problems. Security Design Patterns (SDP) describe countermeasures and are used to reduce risk. After our literature review, we did not find a suitable approach that presents SDPs that would be applicable in early system design. In this paper, we present 10 SDPs for early system design, which we evaluated during an 11-week student project with 28 teams. We present the results of the quantitative analysis and the evaluation of the feedback.

Higher order interactions lead to "reluctant" synchrony breaking - von der Gracht, Sören; Nijholt, Eddie; Rink, Bob (arXiv:2311.17186)
To model dynamical systems on networks with higher order (non-pairwise) interactions, we recently introduced a new class of ODEs on hypernetworks. Here we consider one-parameter synchrony breaking bifurcations in such ODEs. We call a synchrony breaking steady state branch "reluctant" if it is tangent to a synchrony space, but does not lie inside it. We prove that reluctant synchrony breaking is ubiquitous in hypernetwork systems, by constructing a large class of examples that support it. We also give an explicit formula for the order of tangency to the synchrony space of a reluctant steady state branch.

Privacy in the Age of Neurotechnology: Investigating Public Attitudes towards Brain Data Collection and Use - Kablo, Emiram; Arias Cabarcos, Patricia (Proceedings of the 2023 ACM SIGSAC Conference on Computer and Communications Security)

Runtime Verification of Crypto APIs: An Empirical Study - Torres, Adriano; Costa, Pedro; Amaral, Luis; Pastro, Jonata; Bonifácio, Rodrigo; d'Amorim, Marcelo; Legunsen, Owolabi; Bodden, Eric; Dias Canedo, Edna (IEEE Transactions on Software Engineering)
Keywords: Software

Can the configuration of static analyses make resolving security vulnerabilities more effective? - A user study - Piskachev, Goran; Becker, Matthias; Bodden, Eric (Empirical Software Engineering)
Abstract The use of static analysis security testing (SAST) tools has been increasing in recent years. However, previous studies have shown that, when shipped to end users such as development or security teams, the findings of these tools are often unsatisfying. Users report high numbers of false positives or long analysis times, making the tools unusable in the daily workflow. To address this, SAST tool creators provide a wide range of configuration options, such as customization of rules through domain-specific languages or specification of the application-specific analysis scope. In this paper, we study the configuration space of selected existing SAST tools when used within the integrated development environment (IDE). We focus on the configuration options that impact three dimensions, for which a trade-off is unavoidable, i.e., precision, recall, and analysis runtime. We perform a between-subjects user study with 40 users from multiple development and security teams - to our knowledge, the largest population for this kind of user study in the software engineering community. The results show that users who configure SAST tools are more effective in resolving security vulnerabilities detected by the tools than those using the default configuration. Based on post-study interviews, we identify common strategies that users have while configuring the SAST tools to provide further insights for tool creators. Finally, an evaluation of the configuration options of two commercial SAST tools, Fortify and CheckMarx , reveals that a quarter of the users do not understand the configuration options provided. The configuration options that are found most useful relate to the analysis scope.
Keywords: Software

Securing Your Crypto-API Usage Through Tool Support - A Usability Study - Krüger, Stefan; Reif, Michael; Wickert, Anna-Katharina; Nadi, Sarah; Ali, Karim; Bodden, Eric; Acar, Yasemin; Mezini, Mira; Fahl, Sascha (2023 IEEE Secure Development Conference (SecDev))

Entwicklung und Analyse von Formeln zur Abschätzung der Renderingzeit eines Frames - Nickel, Alexander

Reconstruction of 3D Surfels from Neural Radiance Fields - Telaprolu, Vipasyan

Shape Reconfiguration by Hybrid Programmable Matter - Friemel, Jonas

TCO analysis of a modular and integral product architecture in shipbuilding - Seidenberg, Tobias; Disselkamp, Jan-Philipp; Jürgenhake, Christoph; Wicker, Ansgar; Dumitrescu, Roman; Tolo, Edmund

Future production of ships – case study for modular high-speed ferries - Disselkamp, Jan-Philipp; Seidenberg, Tobias; Jürgenhake, Christoph; Anacker, Harald; Dumitrescu, Roman

Idélic Approach in Enumerating Heisenberg Extensions - Klüners, Jürgen; Wang, Jiuya (La Matematica)

On the Impact of Basic Mutation Operators and Populations within Evolutionary Algorithms for the Dynamic Weighted Traveling Salesperson Problem - Bossek, Jakob; Neumann, Aneta; Neumann, Frank (Proceedings of the Genetic and Evolutionary Computation Conference)
Evolutionary algorithms have been shown to obtain good solutions for complex optimization problems in static and dynamic environments. It is important to understand the behaviour of evolutionary algorithms for complex optimization problems that also involve dynamic and/or stochastic components in a systematic way in order to further increase their applicability to real-world problems. We investigate the node weighted traveling salesperson problem (W-TSP), which provides an abstraction of a wide range of weighted TSP problems, in dynamic settings. In the dynamic setting of the problem, items that have to be collected as part of a TSP tour change over time. We first present a dynamic setup for the dynamic W-TSP parameterized by different types of changes that are applied to the set of items to be collected when traversing the tour. Our first experimental investigations study the impact of such changes on resulting optimized tours in order to provide structural insights of optimization solutions. Afterwards, we investigate simple mutation-based evolutionary algorithms and study the impact of the mutation operators and the use of populations with dealing with the dynamic changes to the node weights of the problem.
Keywords: dynamic optimization; evolutionary algorithms; re-optimization; weighted traveling salesperson problem

Runtime Analysis of Quality Diversity Algorithms - Bossek, Jakob; Sudholt, Dirk (Proceedings of the Genetic and Evolutionary Computation Conference)
Quality diversity (QD) is a branch of evolutionary computation that gained increasing interest in recent years. The Map-Elites QD approach defines a feature space, i.e., a partition of the search space, and stores the best solution for each cell of this space. We study a simple QD algorithm in the context of pseudo-Boolean optimisation on the "number of ones" feature space, where the ith cell stores the best solution amongst those with a number of ones in [(i - 1)k, ik - 1]. Here k is a granularity parameter 1 {$≤$} k {$≤$} n+1. We give a tight bound on the expected time until all cells are covered for arbitrary fitness functions and for all k and analyse the expected optimisation time of QD on OneMax and other problems whose structure aligns favourably with the feature space. On combinatorial problems we show that QD finds a (1 - 1/e)-approximation when maximising any monotone sub-modular function with a single uniform cardinality constraint efficiently. Defining the feature space as the number of connected components of a connected graph, we show that QD finds a minimum spanning tree in expected polynomial time.
Keywords: quality diversity; runtime analysis

Generating Diverse and Discriminatory Knapsack Instances by Searching for Novelty in Variable Dimensions of Feature-Space - Marrero, Alejandro; Segredo, Eduardo; Hart, Emma; Bossek, Jakob; Neumann, Aneta (Proceedings of the Genetic} and Evolutionary Computation Conference)
Generating new instances via evolutionary methods is commonly used to create new benchmarking data-sets, with a focus on attempting to cover an instance-space as completely as possible. Recent approaches have exploited Quality-Diversity methods to evolve sets of instances that are both diverse and discriminatory with respect to a portfolio of solvers, but these methods can be challenging when attempting to find diversity in a high-dimensional feature-space. We address this issue by training a model based on Principal Component Analysis on existing instances to create a low-dimension projection of the high-dimension feature-vectors, and then apply Novelty Search directly in the new low-dimension space. We conduct experiments to evolve diverse and discriminatory instances of Knapsack Problems, comparing the use of Novelty Search in the original feature-space to using Novelty Search in a low-dimensional projection, and repeat over a given set of dimensions. We find that the methods are complementary: if treated as an ensemble, they collectively provide increased coverage of the space. Specifically, searching for novelty in a low-dimension space contributes 56% of the filled regions of the space, while searching directly in the feature-space covers the remaining 44%.
Keywords: evolutionary computation; instance generation; instance-space analysis; knapsack problem; novelty search

Do Additional Target Points Speed Up Evolutionary Algorithms? - Bossek, Jakob; Sudholt, Dirk (Theoretical Computer Science)
Most runtime analyses of randomised search heuristics focus on the expected number of function evaluations to find a unique global optimum. We ask a fundamental question: if additional search points are declared optimal, or declared as desirable target points, do these additional optima speed up evolutionary algorithms? More formally, we analyse the expected hitting time of a target set OPT{$\cup$}S where S is a set of non-optimal search points and OPT is the set of optima and compare it to the expected hitting time of OPT. We show that the answer to our question depends on the number and placement of search points in S. For all black-box algorithms and all fitness functions with polynomial expected optimisation times we show that, if additional optima are placed randomly, even an exponential number of optima has a negligible effect on the expected optimisation time. Considering Hamming balls around all global optima gives an easier target for some algorithms and functions and can shift the phase transition with respect to offspring population sizes in the (1,{$λ$}) EA on OneMax. However, for the one-dimensional Ising model the time to reach Hamming balls of radius (1/2-{$ϵ$})n around optima does not reduce the asymptotic expected optimisation time in the worst case. Finally, on functions where search trajectories typically join in a single search point, turning one search point into an optimum drastically reduces the expected optimisation time.
Keywords: Evolutionary algorithms; pseudo-Boolean functions; runtime analysis

On Single-Objective Sub-Graph-Based Mutation for Solving the Bi-Objective Minimum Spanning Tree Problem - Bossek, Jakob; Grimme, Christian (Evolutionary Computation)
We contribute to the efficient approximation of the Pareto-set for the classical NP-hard multi-objective minimum spanning tree problem (moMST) adopting evolutionary computation. More precisely, by building upon preliminary work, we analyse the neighborhood structure of Pareto-optimal spanning trees and design several highly biased sub-graph-based mutation operators founded on the gained insights. In a nutshell, these operators replace (un)connected sub-trees of candidate solutions with locally optimal sub-trees. The latter (biased) step is realized by applying Kruskal’s single-objective MST algorithm to a weighted sum scalarization of a sub-graph.We prove runtime complexity results for the introduced operators and investigate the desirable Pareto-beneficial property. This property states that mutants cannot be dominated by their parent. Moreover, we perform an extensive experimental benchmark study to showcase the operator’s practical suitability. Our results confirm that the subgraph based operators beat baseline algorithms from the literature even with severely restricted computational budget in terms of function evaluations on four different classes of complete graphs with different shapes of the Pareto-front.

Expertise and professionalism for inclusive (mathematics) teaching and learning: reflections on findings from interdisciplinary professionalisation research - Seitz, Simone; Häsel-Weide, Uta; Wilke, Yannik; Wallner, Melina (Teachers and Teaching)