arXiv subjects

Bernhard Steffen

Publications and source records attributed to Bernhard Steffen.

18 recordsLinked to original sources

arXiv2025

It's Not the AI - It's Each of Us! Ten Commandments for the Wise & Responsible Use of AI

Artificial intelligence (AI) is no longer futuristic; it is a daily companion shaping our private and work lives. While AI simplifies our lives, its rise also invites us to rethink who we are - and who we wish to remain - as humans. Even if AI does not think, feel, or desire, it learns from our behavior, mirroring our collective values, biases, and aspirations. The question, then, is not what AI is, but what we are allowing it to become through data, computing power, and other parameters "teaching" it - and, even more importantly, who we are becoming through our relationship with AI. As the EU AI Act and the Vienna Manifesto on Digital Humanism emphasize, technology must serve human dignity,social well-being, and democratic accountability. In our opinion, responsible use of AI is not only a matter of code nor law, but also of conscientious practice: how each of us engages and teaches others to use AI at home and at work. We propose Ten Commandments for the Wise and Responsible Use of AI are meant as guideline for this very engagement. They closely align with Floridi and Cowls' five guiding principles for AI in society - beneficence, non-maleficence, autonomy, justice, and explicability.

cs.CY↗

arXiv2025

AI-Assisted Modeling: DSL-Driven AI Interactions

AI-assisted programming greatly increases software development performance. We enhance this potential by integrating transparency through domain-specific modeling techniques and providing instantaneous, graphical visualizations that accurately represent the semantics of AI-generated code. This approach facilitates visual inspection and formal verification, such as model checking. Formal models can be developed using programming, natural language prompts, voice commands, and stage-wise refinement, with immediate feedback after each transformation step. This support can be tailored to specific domains or intended purposes, improving both code generation and subsequent validation processes. To demonstrate the effectiveness of this approach, we have developed a prototype as a Visual Studio Code extension for the Lingua Franca language. This prototype showcases the potential for novel domain-specific modeling practices, offering an advancement in how models are created, visualized, and verified.

cs.PL↗

arXiv2024

Language-Driven Engineering An Interdisciplinary Software Development Paradigm

We illustrate how purpose-specific, graphical modeling enables application experts with different levels of expertise to collaboratively design and then produce complex applications using their individual, purpose-specific modeling language. Our illustration includes seven graphical Integrated Modeling Environments (IMEs) that support full code generation, as well as four browser-based applications that were modeled and then fully automatically generated and produced using DIME, our most complex graphical IME. While the seven IMEs were chosen to illustrate the types of languages we support with our Language-Driven Engineering (LDE) approach, the four DIME products were chosen to give an impression of the power of our LDE-generated IMEs. In fact, Equinocs, Springer Nature's future editorial system for proceedings, is also being fully automatically generated and then deployed at their Dordrecht site using a deployment pipeline generated with Rig, one of the IMEs presented. Our technology is open source and the products presented are currently in use.

cs.SE↗

arXiv2023

Towards Rigorous Understanding of Neural Networks via Semantics-preserving Transformations

In this paper we present an algebraic approach to the precise and global verification and explanation of Rectifier Neural Networks, a subclass of Piece-wise Linear Neural Networks (PLNNs), i.e., networks that semantically represent piece-wise affine functions. Key to our approach is the symbolic execution of these networks that allows the construction of semantically equivalent Typed Affine Decision Structures (TADS). Due to their deterministic and sequential nature, TADS can, similarly to decision trees, be considered as white-box models and therefore as precise solutions to the model and outcome explanation problem. TADS are linear algebras which allows one to elegantly compare Rectifier Networks for equivalence or similarity, both with precise diagnostic information in case of failure, and to characterize their classification potential by precisely characterizing the set of inputs that are specifically classified or the set of inputs where two network-based classifiers differ. All phenomena are illustrated along a detailed discussion of a minimal, illustrative example: the continuous XOR function.

cs.NE↗

arXiv2023

The Power of Typed Affine Decision Structures: A Case Study

TADS are a novel, concise white-box representation of neural networks. In this paper, we apply TADS to the problem of neural network verification, using them to generate either proofs or concise error characterizations for desirable neural network properties. In a case study, we consider the robustness of neural networks to adversarial attacks, i.e., small changes to an input that drastically change a neural networks perception, and show that TADS can be used to provide precise diagnostics on how and where robustness errors a occur. We achieve these results by introducing Precondition Projection, a technique that yields a TADS describing network behavior precisely on a given subset of its input space, and combining it with PCA, a traditional, well-understood dimensionality reduction technique. We show that PCA is easily compatible with TADS. All analyses can be implemented in a straightforward fashion using the rich algebraic properties of TADS, demonstrating the utility of the TADS framework for neural network explainability and verification. While TADS do not yet scale as efficiently as state-of-the-art neural network verifiers, we show that, using PCA-based simplifications, they can still scale to mediumsized problems and yield concise explanations for potential errors that can be used for other purposes such as debugging a network or generating new training samples.

cs.LG↗

arXiv2021

A Generative Approach for User-Centered, Collaborative, Domain-Specific Modeling Environments

The use of low- and no-code modeling tools is today an established way in practice to give non-programmers an opportunity to master their digital challenges independently, using the means of model-driven software development. However, the existing tools are limited to a very small number of different domains such as mobile app development, which can be attributed to the enormous demands that a user has on such a tool today. These demands exceed the mere use of a modeling environment as such and require cross-cutting concerns such as: easy access, direct usability and simultaneous collaboration, which result in additional effort in the realization of such tools. Our solution is based on the idea to support and simplify the creation of new domain-specific holistic tools by generating it entirely based on a declarative specification with a domain-specific meta-tool. The meta-tool Pyro demonstrated and analyzed here focuses on graph-based graphical languages to fully generate a complete, directly executable tool starting from a meta-model in order to meet all cross-cutting requirements.

cs.PL↗

arXiv2019

Aggressive Aggregation: a New Paradigm for Program Optimization

In this paper, we propose a new paradigm for program optimization which is based on aggressive aggregation, i.e., on a partial evaluation-based decomposition of acyclic program fragments into a pair of computationally optimal structures: an Algebraic Decision Diagram (ADD) to capture conditional branching and a parallel assignment that refers to an Expression DAG (ED) which realizes redundancy-free computation. The point of this decomposition into, in fact, side-effect-free component structures allows for powerful optimization that semantically comprise effects traditionally aimed at by SSA form transformation, code specialization, common subexpression elimination, and (partial) redundancy elimination. We illustrate our approach along an optimization of the well-known iterative Fibonacci program, which, typically, is considered to lack any optimization potential. The point here is that our technique supports loop unrolling as a first class optimization technique and is tailored to optimally aggregate large program fragments, especially those resulting from multiple loop unrollings. For the Fibonacci program, this results in a performance improvement beyond an order of magnitude.

cs.PL↗

arXiv2019

ADD-Lib: Decision Diagrams in Practice

In the paper, we present the ADD-Lib, our efficient and easy to use framework for Algebraic Decision Diagrams (ADDs). The focus of the ADD-Lib is not so much on its efficient implementation of individual operations, which are taken by other established ADD frameworks, but its ease and flexibility, which arise at two levels: the level of individual ADD-tools, which come with a dedicated user-friendly web-based graphical user interface, and at the meta level, where such tools are specified. Both levels are described in the paper: the meta level by explaining how we can construct an ADD-tool tailored for Random Forest refinement and evaluation, and the accordingly generated Web-based domain-specific tool, which we also provide as an artifact for cooperative experimentation. In particular, the artifact allows readers to combine a given Random Forest with their own ADDs regarded as expert knowledge and to experience the corresponding effect.

cs.LG↗

arXiv2019

Large Random Forests: Optimisation for Rapid Evaluation

Random Forests are one of the most popular classifiers in machine learning. The larger they are, the more precise is the outcome of their predictions. However, this comes at a cost: their running time for classification grows linearly with the number of trees, i.e. the size of the forest. In this paper, we propose a method to aggregate large Random Forests into a single, semantically equivalent decision diagram. Our experiments on various popular datasets show speed-ups of several orders of magnitude, while, at the same time, also significantly reducing the size of the required data structure.

cs.LG↗

arXiv2013

Higher-Order Process Modeling: Product-Lining, Variability Modeling and Beyond

We present a graphical and dynamic framework for binding and execution of business) process models. It is tailored to integrate 1) ad hoc processes modeled graphically, 2) third party services discovered in the (Inter)net, and 3) (dynamically) synthesized process chains that solve situation-specific tasks, with the synthesis taking place not only at design time, but also at runtime. Key to our approach is the introduction of type-safe stacked second-order execution contexts that allow for higher-order process modeling. Tamed by our underlying strict service-oriented notion of abstraction, this approach is tailored also to be used by application experts with little technical knowledge: users can select, modify, construct and then pass (component) processes during process execution as if they were data. We illustrate the impact and essence of our framework along a concrete, realistic (business) process modeling scenario: the development of Springer's browser-based Online Conference Service (OCS). The most advanced feature of our new framework allows one to combine online synthesis with the integration of the synthesized process into the running application. This ability leads to a particularly flexible way of implementing self-adaption, and to a particularly concise and powerful way of achieving variability not only at design time, but also at runtime.

cs.SE↗

arXiv2011

Microscopic insights into pedestrian motion through a bottleneck, resolving spatial and temporal variations

The motion of pedestrians is subject to a wide range of influences and exhibits a rich phenomenology. To enable precise measurement of the density and velocity we use an alternative definition using Voronoi diagrams which exhibits smaller fluctuations than the standard definitions. This method permits examination on scales smaller than the pedestrians. We use this method to investigate the spatial and temporal variation of the observables at bottlenecks. Experiments were performed with 180 test subjects and a wide range of bottleneck parameters. The anomalous flow through short bottlenecks and non-stationary states present with narrow bottlenecks are analysed.

physics.soc-ph↗

arXiv2010

Constraint-Guided Workflow Composition Based on the EDAM Ontology

Methods for the automatic composition of services into executable workflows need detailed knowledge about the application domain,in particular about the available services and their behavior in terms of input/output data descriptions. In this paper we discuss how the EMBRACE data and methods ontology (EDAM) can be used as background knowledge for the composition of bioinformatics workflows. We show by means of a small example domain that the EDAM knowledge facilitates finding possible workflows, but that additional knowledge is required to guide the search towards actually adequate solutions. We illustrate how the ability to flexibly formulate domain-specific and problem-specific constraints supports the work ow development process.

cs.SE↗

arXiv2010

Analysis of bottleneck motion using Voronoi diagrams

Standard definitions of the density exhibit large fluctuations when the size of the measurement area is comparable with the size of a pedestrian. An alternative measurement method exists where a personal space, calculated through the Voronoi diagram, is assigned to each pedestrian. In this contribution this method is applied to an experiment studying motion through a bottleneck and the reduced fluctuations demonstrated. The integrated density also permits examination on much smaller spatial scales than the standard definition, the insights into the pedestrian motion this provides are discussed.

physics.soc-ph↗

arXiv2009

Methods for measuring pedestrian density, flow, speed and direction with minimal scatter

The progress of image processing during recent years allows the measurement of pedestrian characteristics on a "microscopic" scale with low costs. However, density and flow are concepts of fluid mechanics defined for the limit of infinitely many particles. Standard methods of measuring these quantities locally (e.g. counting heads within a rectangle) suffer from large data scatter. The remedy of averaging over large spaces or long times reduces the possible resolution and inhibits the gain obtained by the new technologies. In this contribution we introduce a concept for measuring microscopic characteristics on the basis of pedestrian trajectories. Assigning a personal space to every pedestrian via a Voronoi diagram reduces the density scatter. Similarly, calculating direction and speed from position differences between times with identical phases of movement gives low-scatter sequences for speed and direction. Closing we discuss the methods to obtain reliable values for derived quantities and new possibilities of in depth analysis of experiments. The resolution obtained indicates the limits of stationary state theory.

physics.soc-ph↗

arXiv2008

The repulsive force in continous space models of pedestrian movement

Pedestrian movements can be modeled at different degrees of detail. While flux models (Predeshensky/Milinski 1971) and cellular automata models (Schreckenberg 2002) give answers to some important questions and are fast and easy to use, continuous space modeling has the potential of full flexibility in geometry and realistic description of individual movements in arbitrary fine resolution. While the acceleration forces in these models are known with good reliability, there is no agreement on the repulsive forces, not even on the functional form of these forces (Lakoba 2005, Molnar 1996, Parisi 2005, Yu 2005). We give some basic consideration to define the minimal complexity of the functional form of the repulsive forces together with some estimates of the values of parameters. From these considerations it becomes obvious that the repulsive forces have to depend not only on the relative position of persons, but also on the speeds and speed differences. The parameters of these forces will be situation dependant. They can in principle be derived from video observations of people moving, although the large scatter of data and the complexity involved makes for large uncertainties.

physics.soc-ph↗

arXiv2007

New insights into pedestrian flow through bottlenecks

Capacity estimation is an important tool for the design and dimensioning of pedestrian facilities. The literature contains different procedures and specifications which show considerable differences with respect to the estimated flow values. Moreover do new experimental data indicate a stepwise growing of the capacity with the width and thus challenge the validity of the specific flow concept. To resolve these differences we have studied experimentally the unidirectional pedestrian flow through bottlenecks under laboratory conditions. The time development of quantities like individual velocities, density and individual time gaps in bottlenecks of different width is presented. The data show a linear growth of the flow with the width. The comparison of the results with experimental data of other authors indicates that the basic assumption of the capacity estimation for bottlenecks has to be revised. In contradiction with most planning guidelines our main result is, that a jam occurs even if the incoming flow does not overstep the capacity defined by the maximum of the flow according to the fundamental diagram.

physics.soc-ph↗

arXiv2005

The Fundamental Diagram of Pedestrian Movement Revisited

The empirical relation between density and velocity of pedestrian movement is not completely analyzed, particularly with regard to the `microscopic' causes which determine the relation at medium and high densities. The simplest system for the investigation of this dependency is the normal movement of pedestrians along a line (single-file movement). This article presents experimental results for this system under laboratory conditions and discusses the following observations: The data show a linear relation between the velocity and the inverse of the density, which can be regarded as the required length of one pedestrian to move. Furthermore we compare the results for the single-file movement with literature data for the movement in a plane. This comparison shows an unexpected conformance between the fundamental diagrams, indicating that lateral interference has negligible influence on the velocity-density relation at the density domain $1 m^{-2}<ρ<5 m^{-2}$. In addition we test a procedure for automatic recording of pedestrian flow characteristics. We present preliminary results on measurement range and accuracy of this method.

physics.soc-ph↗

arXiv2005

Basics of Modelling the Pedestrian Flow

For the modelling of pedestrian dynamics we treat persons as self-driven objects moving in a continuous space. On the basis of a modified social force model we qualitatively analyze the influence of various approaches for the interaction between the pedestrians on the resulting velocity-density relation. To focus on the role of the required space and remote force we choose a one-dimensional model for this investigation. For those densities, where in two dimensions also passing is no longer possible and the mean value of the velocity depends primarily on the interaction, we obtain the following result: If the model increases the required space of a person with increasing current velocity, the reproduction of the typical form of the fundamental diagram is possible. Furthermore we demonstrate the influence of the remote force on the velocity-density relation.

physics.soc-ph↗