相关论文: Model-Driven Engineering of Self-Adaptive Software…

Autonomous robots need to be able to handle uncertainties when deployed in the real world. For the robot to be able to robustly work in such an environment, it needs to be able to adapt both its architecture as well as its task plan.…

Adapting pre-trained language models (PLMs) for time-series text classification amidst evolving domain shifts (EDS) is critical for maintaining accuracy in applications like stance detection. This study benchmarks the effectiveness of…

Model-based development and in particular MDA [1], [2] have promised to be especially suited for the development of complex, heterogeneous, and large software systems. However, so far MDA has failed to fulfill this promise to a larger…

In recent years, research in the area of human-robot interaction has focused on developing robots capable of understanding complex human instructions and performing tasks in dynamic and diverse environments. These systems have a wide range…

The paper combines research approaches that traditionally have been disjoint: 1) model checking as used in formal verification of programs, and 2) auto-tuning as often used in high-performance computing. Auto-tuning frameworks optimize…

Model-based verification allows to express behavioral correctness conditions like the validity of execution states, boundaries of variables or timing at a high level of abstraction and affirm that they are satisfied by a software system.…

An emerging service is moving the known aviation sector in terms of technology, paradigms, and key players - the Urban Air Mobility. The reason: new developments in non-aviation industries are driving technological progress in aviation. For…

By treating data and models as the source code, Foundation Models (FMs) become a new type of software. Mirroring the concept of software crisis, the increasing complexity of FMs making FM crisis a tangible concern in the coming decade,…

We introduce RE-Adapt, an approach to fine-tuning large language models on new domains without degrading any pre-existing instruction-tuning. We reverse engineer an adapter which isolates what an instruction-tuned model has learned beyond…

In this position paper we propose a process model that provides a development infrastructure in which the usability engineering and software engineering life cycles co-exist in complementary roles. We describe the motivation, hurdles,…

Self-evolution of multimodal large language models (MLLMs) remains a critical challenge: pseudo-label-based methods suffer from progressive quality degradation as model predictions drift, while template-based methods are confined to a…

Software reliability is an important quality attrib-ute, often evaluated as either a function of time or of system structures. The goal of this study is to have this metric cover both for component-based software, be-cause its reliability…

Large Language Model (LLM) pretraining, finetuning, and evaluation rely on input-space reconstruction and generative capabilities. Yet, it has been observed in vision that embedding-space training objectives, e.g., with Joint Embedding…

Large Language Model (LLM)-based agents are increasingly employed to automate complex software engineering tasks, such as program repair and issue resolution. These agents operate by autonomously generating natural language thoughts,…

This paper provides a survey of the emerging area of Large Language Models (LLMs) for Software Engineering (SE). It also sets out open research challenges for the application of LLMs to technical problems faced by software engineers. LLMs'…

Software Engineering and the implementation of software has become a challenging task as many tools, frameworks and languages must be orchestrated into one functioning piece. This complexity increases the need for testing and analysis…

Code optimization is the process of enhancing code efficiency, while preserving its intended functionality. This process often requires a deep understanding of the code execution behavior at run-time to identify and address inefficiencies…

Video generative models are increasingly used as world models for robotics, where a model generates a future visual rollout conditioned on the current observation and task instruction, and an inverse dynamics model (IDM) converts the…

The rapid advancement of large language models (LLMs) has redefined artificial intelligence (AI), pushing the boundaries of AI research and enabling unbounded possibilities for both academia and the industry. However, LLM development faces…

This paper presents a SysML-based approach to enhance functional and software development process within an industrial context. The recent changes in technology such as electromobility and increased automation in heavy construction…