Michael Kläs

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A Framework for the Balanced Optimization of Quality Assurance Strategies Focusing on Small and Medium Sized Enterprises

Rolf Hendrik van Lengen, Frank Elberzhager, Michael Kläs, 2009, 2009 35th Euromicro Conference on Software Engineering and Advanced Applications.

7 Handling Uncertainty in Collaborative Embedded Systems Engineering

Boris Wirtz, Michael Kläs, Lisa Jöckel, 2020 .

From Complexity Measurement to Holistic Quality Evaluation for Automotive Software Development pdf

Jochen Quante, Adam Trendowicz, Thomas Grundler, 2021, ArXiv.

The Use of Simulation Techniques for Hybrid Software Cost Estimation and Risk Analysis

Jürgen Münch, Adam Trendowicz, Nahomi Kikuchi, 2008, Adv. Comput..

Support planning and controlling of early quality assurance by combining expert judgment and defect data—a case study

Frank Elberzhager, Jürgen Münch, Michael Kläs, 2010, Empirical Software Engineering.

Predicting Defect Content and Quality Assurance Effectiveness by Combining Expert Judgment and Defect Data - A Case Study

Frank Elberzhager, Jürgen Münch, Michael Kläs, 2008, 2008 19th International Symposium on Software Reliability Engineering (ISSRE).

Could We Relieve AI/ML Models of the Responsibility of Providing Dependable Uncertainty Estimates? A Study on Outside-Model Uncertainty Estimates

Michael Kläs, Lisa Jöckel, Michael Kläs, 2021, SAFECOMP.

Comprehensive Landscapes for Software-related Quality Models pdf

Jürgen Münch, Adam Trendowicz, Michael Kläs, 2014, ArXiv.

CQML Scheme: A Classification Scheme for Comprehensive Quality Model Landscapes

Jürgen Münch, Adam Trendowicz, Michael Kläs, 2009, 2009 35th Euromicro Conference on Software Engineering and Advanced Applications.

Uncertainty in Machine Learning Applications: A Practice-Driven Classification of Uncertainty

Michael Kläs, Anna Maria Vollmer, Michael Kläs, 2018, SAFECOMP Workshops.

A Comprehensive Code-Based Quality Model for Embedded Systems: Systematic Development and Validation by Industrial Projects

Reinhold Plösch, Michael Kläs, Constanza Lampasona, 2012, 2012 IEEE 23rd International Symposium on Software Reliability Engineering.

Uncertainty Wrappers for Data-Driven Models - Increase the Transparency of AI/ML-Based Models Through Enrichment with Dependable Situation-Aware Uncertainty Estimates

Michael Kläs, Lena Sembach, L. Sembach, 2019, SAFECOMP Workshops.

Safe Traffic Sign Recognition through Data Augmentation for Autonomous Vehicles Software

Silverio Martínez-Fernández, Michael Kläs, Lisa Jöckel, 2019, 2019 IEEE 19th International Conference on Software Quality, Reliability and Security Companion (QRS-C).

Architectural patterns for handling runtime uncertainty of data-driven models in safety-critical perception

Jan Reich, Michael Kläs, Roman Gansch, 2022, International Conference on Computer Safety, Reliability, and Security.

Timeseries-aware Uncertainty Wrappers for Uncertainty Quantification of Information-Fusion-Enhanced AI Models based on Machine Learning

Michael Kläs, Lisa Jöckel, Janek Groß, 2023, 2023 53rd Annual IEEE/IFIP International Conference on Dependable Systems and Networks Workshops (DSN-W).

A Study on Mitigating Hard Boundaries of Decision-Tree-based Uncertainty Estimates for AI Models

Michael Kläs, Lisa Jöckel, Pascal Gerber, 2022, SafeAI@AAAI.

A Framework for Building Uncertainty Wrappers for AI/ML-Based Data-Driven Components

Michael Kläs, Lisa Jöckel, Michael Kläs, 2020, SAFECOMP Workshops.

Beyond Herding Cats: Aligning Quantitative Technology Evaluation in Large-Scale Research Projects

Thomas Bauer, Michael Kläs, Ubaldo Tiberi, 2013, PROFES.

Operationalised product quality models and assessment: The Quamoco approach

Reinhold Plösch, Jonathan Streit, Andreas Seidl, 2014, Inf. Softw. Technol..

Early Validation of Software Quality Models with respect to Mini- mality and Completeness: An Empirical Analysis

Michael Kläs, Constanza Lampasona, Alois Mayr, 2013 .

Model-based Product Quality Evaluation with Multi-Criteria Decision Analysis pdf

Jürgen Münch, Adam Trendowicz, Michael Kläs, 2014, ArXiv.