Sebastian Werner

SE
h-index10
5papers
15citations
Novelty33%
AI Score41

5 Papers

7.1SEApr 10
The Need for a Green ICT Reference Framework

Marco Aiello, Mina Alipour, Antonio Brogi et al.

The sustainability impacts of ICT systems are difficult to assess and govern due to structural complexity, fragmented measurement practices, and unclear responsibilities across system layers. We argue that these challenges cannot be addressed solely by metrics and motivate the need for a shared Green ICT reference framework that integrates sustainability across multiple perspectives and domains, lifecycle phases, and governance contexts. We present an initial framework developed within the Informatics Europe Green ICT Working Group as a first step towards a comprehensive reference framework.

5.8CRMay 20
An Evidence-driven Protocol for Trustworthy CI Pipelines

Fernando Castillo, Eduardo Brito, Pille Pullonen-Raudvere et al.

Enterprise software supply chains are increasingly vulnerable to infrastructure attacks, resulting in financial and reputational damage. Ensuring the integrity and provenance of software artifacts remains a significant challenge, where re-execution of the build and tests by every consumer to guarantee provenance produces a verification bottleneck and credibility reduction. This paper presents an evidence-driven protocol for trustworthy Continuous Integration (CI) pipelines that combines Deterministic Build Systems (DBS) with Trusted Execution Environments (TEEs). The approach provides cryptographically verifiable guarantees of integrity, authenticity, and attestation for CI artifacts in distributed environments, reducing implicit trust without requiring costly re-execution by consumers. We introduce a protocol that binds deterministic builds with TEE-based attestations, formalizing the evidence life cycle, together with a practical implementation using Nix and Intel TDX. Experimental results show that artifact verification is reduced from redundant computation to lightweight signature and policy checks. These findings demonstrate that evidence-driven CI pipelines establish scalable and verifiable trust in digital infrastructure, effectively amortizing the initial computational overhead introduced by TEEs.

7.0SEMay 6
Architectural Constraints Alignment in AI-assisted, Platform-based Service Development

Julius Irion, Moritz Leugers, Paul Hartwig et al.

AI-assisted development tools enable rapid prototyping of services but often lack awareness of architectural constraints, infrastructure dependencies, and organizational standards required in production environments. Consequently, generated artifacts may exhibit brittle behavior and limited deployability. We propose a retrieval-augmented scaffolding approach that combines platform-based code generation with agentic clarification loops to expose and resolve architectural constraint ambiguities. By combining template retrieval with structured interaction, the method embeds production-relevant considerations during service scaffolding. Evaluation indicates improved architectural consistency and deployability compared to general-purpose AI code generation workflows, suggesting that constraint-aware retrieval is essential for aligning AI-assisted service development with production software engineering practices.

3.6SEOct 29, 2021
Application-Platform Co-Design for Serverless Data Processing

Sebastian Werner, Stefan Tai

"Application-platform co-design" refers to the phenomenon of new platforms being created in response to changing application needs, followed by application design and development changing due to the emergence (and the specifics, limitations) of the new platforms, therefore creating, again, new application and platform requirements. This continuous process of application and platform (re-)design describes an engineering and management responsibility to constantly evaluate any given platform for application fit and platform-specific application design, and to consider a new or evolutionary platform development project due to evolving and changing application needs. In this paper, we study this phenomenon in the context of serverless computing and (big) data processing needs, and thus, for application-platform co-design for serverless data processing (SDP). We present an analysis of the state-of-the-art of function-as-a-service (FaaS) platforms, which reveals several configuration, deployment, execution, and measurement differences between popular platforms happening at-speed. These differences indicate already ongoing platform (re-)design processes resulting in more specialized serverless platforms and new, platform-specific challenges for application design. We discuss data processing needs of applications using the serverless model and present common initial (and undesirable) workaround solutions on the application level, giving additional argument to the creation of new SDP platforms. We present critical SDP requirements and possible new platform augmentations, but identify the need for engineering methods and tooling to better guide application-platform co-design. We argue to pay appropriate attention to the phenomenon of continuous application-platform co-design to better anticipate and to control future platform and application developments.

6.4SEOct 7, 2021
FaaSter Troubleshooting -- Evaluating Distributed Tracing Approaches for Serverless Applications

Maria C. Borges, Sebastian Werner, Ahmet Kilic

Serverless applications can be particularly difficult to troubleshoot, as these applications are often composed of various managed and partly managed services. Faults are often unpredictable and can occur at multiple points, even in simple compositions. Each additional function or service in a serverless composition introduces a new possible fault source and a new layer to obfuscate faults. Currently, serverless platforms offer only limited support for identifying runtime faults. Developers looking to observe their serverless compositions often have to rely on scattered logs and ambiguous error messages to pinpoint root causes. In this paper, we investigate the use of distributed tracing for improving the observability of faults in serverless applications. To this end, we first introduce a model for characterizing fault observability, then provide a prototypical tracing implementation - specifically, a developer-driven and a platform-supported tracing approach. We compare both approaches with our model, measure associated trade-offs (execution latency, resource utilization), and contribute new insights for troubleshooting serverless compositions.