b'Markus Borg'

research

∙ 04/23/2023

U Owns the Code That Changes and How Marginal Owners Resolve Issues Slower in Low-Quality Source Code

[Context] Accurate time estimation is a critical aspect of predictable s...

0 Markus Borg, et al. ∙

research

∙ 03/10/2023

Automotive Perception Software Development: An Empirical Investigation into Data, Annotation, and Ecosystem Challenges

Software that contains machine learning algorithms is an integral part o...

0 Hans-Martin Heyn, et al. ∙

research

∙ 02/23/2023

Requirements Engineering for Automotive Perception Systems: an Interview Study

Background: Driving automation systems (DAS), including autonomous drivi...

0 Khan Mohammad Habibullah, et al. ∙

research

∙ 10/31/2022

Mutation Testing Optimisations using the Clang Front-end

Mutation testing is the state-of-the-art technique for assessing the fau...

0 Sten Vercammen, et al. ∙

research

∙ 10/13/2022

Automotive Multilingual Fault Diagnosis

Automated fault diagnosis can facilitate diagnostics assistance, speedie...

0 John Pavlopoulos, et al. ∙

research

∙ 09/19/2022

Adopting Automated Bug Assignment in Practice: A Longitudinal Case Study at Ericsson

The continuous inflow of bug reports is a considerable challenge in larg...

0 Markus Borg, et al. ∙

research

∙ 04/26/2022

Performance Analysis of Out-of-Distribution Detection on Trained Neural Networks

Several areas have been improved with Deep Learning during the past year...

0 Jens Henriksson, et al. ∙

research

∙ 04/16/2022

Ergo, SMIRK is Safe: A Safety Case for a Machine Learning Component in a Pedestrian Automatic Emergency Brake System

Integration of Machine Learning (ML) components in critical applications...

8 Markus Borg, et al. ∙

research

∙ 03/30/2022

Exploring ML testing in practice – Lessons learned from an interactive rapid review with Axis Communications

There is a growing interest in industry and academia in machine learning...

0 Qunying Song, et al. ∙

research

∙ 03/29/2022

Quality Assurance of Generative Dialog Models in an Evolving Conversational Agent Used for Swedish Language Practice

Due to the migration megatrend, efficient and effective second-language ...

0 Markus Borg, et al. ∙

research

∙ 03/22/2022

Machine Learning Testing in an ADAS Case Study Using Simulation-Integrated Bio-Inspired Search-Based Testing

This paper presents an extended version of Deeper, a search-based simula...

0 Mahshid Helali Moghadam, et al. ∙

research

∙ 03/08/2022

Code Red: The Business Impact of Code Quality – A Quantitative Study of 39 Proprietary Production Codebases

Code quality remains an abstract concept that fails to get traction at t...

0 Adam Tornhill, et al. ∙

research

∙ 11/28/2021

Agility in Software 2.0 – Notebook Interfaces and MLOps with Buttresses and Rebars

Artificial intelligence through machine learning is increasingly used in...

0 Markus Borg, et al. ∙

research

∙ 11/16/2021

Machine Learning-Assisted Analysis of Small Angle X-ray Scattering

Small angle X-ray scattering (SAXS) is extensively used in materials sci...

0 Piotr Tomaszewski, et al. ∙

research

∙ 09/28/2021

Adopting Automated Bug Assignment in Practice – A Registered Report of an Industrial Case Study

[Background/Context] The continuous inflow of bug reports is a considera...

0 Markus Borg, et al. ∙

research

∙ 09/16/2021

Efficient and Effective Generation of Test Cases for Pedestrian Detection – Search-based Software Testing of Baidu Apollo in SVL

With the growing capabilities of autonomous vehicles, there is a higher ...

0 Hamid Ebadi, et al. ∙

research

∙ 04/28/2021

Challenges of Adopting SAFe in the Banking Industry – A Study Two Years after its Introduction

The Scaled Agile Framework (SAFe) is a framework for scaling agile metho...

0 Sara Nilsson Tengstrand, et al. ∙

research

∙ 04/26/2021

Performance Testing Using a Smart Reinforcement Learning-Driven Test Agent

Performance testing with the aim of generating an efficient and effectiv...

0 Mahshid Helali Moghadam, et al. ∙

research

∙ 03/29/2021

Performance Analysis of Out-of-Distribution Detection on Various Trained Neural Networks

Several areas have been improved with Deep Learning during the past year...

0 Jens Henriksson, et al. ∙

research

∙ 03/02/2021

Test Automation with Grad-CAM Heatmaps – A Future Pipe Segment in MLOps for Vision AI?

Machine Learning (ML) is a fundamental part of modern perception systems...

0 Markus Borg, et al. ∙

research

∙ 12/12/2020

Digital Twins Are Not Monozygotic – Cross-Replicating ADAS Testing in Two Industry-Grade Automotive Simulators

The increasing levels of software- and data-intensive driving automation...

0 Markus Borg, et al. ∙

research

∙ 09/11/2020

Enabling Image Recognition on Constrained Devices Using Neural Network Pruning and a CycleGAN

Smart cameras are increasingly used in surveillance solutions in public ...

29 August Lidfelt, et al. ∙

research

∙ 09/11/2020

The AIQ Meta-Testbed: Pragmatically Bridging Academic AI Testing and Industrial Q Needs

AI solutions seem to appear in any and all application domains. As AI be...

0 Markus Borg, et al. ∙

research

∙ 05/27/2020

Making Lab Sessions Mandatory – On Student Work Distribution in a Gamified Project Course on Market-Driven Software Engineering

Unfair work distribution in student teams is a common issue in project-b...

0 Markus Borg, et al. ∙

research

∙ 05/26/2020

Illuminating a Blind Spot in Digitalization – Software Development in Sweden's Private and Public Sector

As Netscape co-founder Marc Andreessen famously remarked in 2011, softwa...

0 Markus Borg, et al. ∙

research

∙ 08/19/2019

An Autonomous Performance Testing Framework using Self-Adaptive Fuzzy Reinforcement Learning

Test automation can result in reduction in cost and human effort. If the...

0 Mahshid Helali Moghadam, et al. ∙

research

∙ 08/13/2019

Requirements Engineering for Machine Learning: Perspectives from Data Scientists

Machine learning (ML) is used increasingly in real-world applications. I...

0 Andreas Vogelsang, et al. ∙

research

∙ 06/11/2019

Sharing of vulnerability information among companies -- a survey of Swedish companies

Software products are rarely developed from scratch and vulnerabilities ...

0 Thomas Olsson, et al. ∙

research

∙ 03/31/2019

Video Game Development in a Rush: A Survey of the Global Game Jam Participants

Video game development is a complex endeavor, often involving complex so...

0 Markus Borg, et al. ∙

research

∙ 03/05/2019

SZZ Unleashed: An Open Implementation of the SZZ Algorithm - Featuring Example Usage in a Study of Just-in-Time Bug Prediction for the Jenkins Project

Numerous empirical software engineering studies rely on detailed informa...

0 Markus Borg, et al. ∙

research

∙ 03/04/2019

Towards Structured Evaluation of Deep Neural Network Supervisors

Deep Neural Networks (DNN) have improved the quality of several non-safe...

0 Jens Henriksson, et al. ∙

research

∙ 12/13/2018

Safely Entering the Deep: A Review of Verification and Validation for Machine Learning and a Challenge Elicitation in the Automotive Industry

Deep Neural Networks (DNN) will emerge as a cornerstone in automotive so...

0 Markus Borg, et al. ∙

research

∙ 12/04/2018

Cut to the chase: Revisiting the relevance of software engineering research

Software engineering (SE) research should be relevant to industrial prac...

0 Vahid Garousi, et al. ∙

research

∙ 08/29/2018

Enabling Visual Design Verification Analytics - From Prototype Visualizations to an Analytics Tool using the Unity Game Engine

The ever-increasing architectural complexity in contemporary ASIC projec...

0 Markus Borg, et al. ∙

research

∙ 07/28/2018

Goal-oriented Mutation Testing with Focal Methods

Mutation testing is the state-of-the-art technique for assessing the fau...

0 Sten Vercammen, et al. ∙

research

∙ 02/01/2018

Digitalization of Swedish Government Agencies - A Perspective Through the Lens of a Software Development Census

Software engineering is at the core of the digitalization of society. Il...

0 Markus Borg, et al. ∙

research

∙ 04/26/2017

On Using Active Learning and Self-Training when Mining Performance Discussions on Stack Overflow

Abundant data is the key to successful machine learning. However, superv...

0 Markus Borg, et al. ∙

Markus Borg

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