Filetype
Software development is a complex activity that needs a lot of tool assistance. Over the years there has been a lot of effort put into development of automated assistance to help with activities such as detection of issues via program analysis, or refactoring of code. Recently, the landscape of developer tool assistance is being disrupted with the entry of AI tools, such as Copilot and ChatGPT, po
We propose and study a weakly convergent variant of the forward-backward algorithm for solving structured monotone inclusion problems. Our algorithm features a per-iteration deviation vector, providing additional degrees of freedom. The only requirement on the deviation vector to guarantee convergence is that its norm is bounded by a quantity that can be computed online. This approach offers great
Cyber-physical Systems (CPSs) are often safety-critical and deployed in uncertain environments. Identifying scenarios where CPSs do not comply with requirements is fundamental but difficult due to the multidisciplinary nature of CPSs. We investigate the testing of control-based CPSs, where control and software engineers develop the software collaboratively. Control engineers make design assumption
In order to keep up with the constant demand for higher data rates, the fifth generation of mobile communication (5G) introduced the use of mm-wave carrier frequencies from 24 to 71 GHz. Plenty of new frequency spectrum then became available, which has allowed for channel bandwidths of several hundreds of MHz. 6G is projected to continue this trend with even higher carrier frequencies and wider ba
This study develops a deep learning method for fast auditory attention decoding (AAD) using electroencephalography (EEG) from listeners with hearing impairment. It addresses three classification tasks: differentiating noise from speech-in-noise, classifying the direction of attended speech (left vs. right) and identifying the activation status of hearing aid noise reduction (NR) algorithms (OFF vs
Variability in composite manufacture and the limitations in positional accuracy of common industrial robots have hampered automation of assembly tasks within aircraft manufacturing. One way to handle geometry variations and robot compliancy is to use force control. Force control technology utilizes a sensor mounted on the robot to feedback force data to the controller system so instead of being po
New robot applications increasingly require external sensing to accomplish robustness and performance despite the variations and uncertainties that come with the increasing demands on flexibility for manufacturing of customized products. The demands on productivity then require high performance, which for well known feedback-control reasons means short response times from external process event to
High motion performance, stiffness, and accuracy are crucial for industrial robot applications, but these requirements are in practice contradictory. Using a novel type of robot, the so called Gantry Tau, new combinations of stiffness and accuracy are in principle possible, except for the backlash in the drive-trains of each joint. Existing techniques for backlash reduction are either mechanicall
Supervising a student can be compared to teaching someone to drive a car. The student is in the driver’s seat while the supervisor provides structure and guidance, and can intervene in risky and unsafe situations. It is a learning process in which the student gradually gains experience and sufficient skill to obtain a driving license, and to drive without an instructor. Similarly, a student attend
Background. Test automation is a widely used technique to increase the efficiency of software testing. However, executing more test cases increases the effort required to analyze test results. At Qlik, automated tests run nightly for up to 20 development branches, each containing thousands of test cases, resulting in information overload. Aim. We therefore develop a tool that supports the analysis
We study intervention design problems for general finite non-binary super-modular games. The considered interventions consist in constraining or incentivizing the players to play actions above designed lower bounds, with a cost for the system planner that is a separable increasing function of such bounds. We study the intervention of minimum cost for which a best response learning algorithm leads
We are currently witnessing the second wave of cloud services that go beyond web storefronts and IT systems, aiming for digitalization of industrial systems. Automation and time-sensitive systems are now taking their first steps toward the cloud. The AORTA project aims to facilitate this transition by providing key technology components needed for real-time services running in the cloud. The ambit
While Weighted Lasso sparse regression has appealing statistical guarantees that would entail a major real-world impact in finance, genomics, and brain imaging applications, it is typically scarcely adopted due to its complex high-dimensional space composed by thousands of hyperparameters. On the other hand, the latest progress with high-dimensional hyperparameter optimization (HD-HPO) methods for
In embedded computing domains, including the automotive industry, complex functionalities are split across multiple tasks that form task chains. These tasks are functionally dependent and communicate partial computations through shared memory slots based on the Logical Execution Time (LET) paradigm. This paper introduces a model that captures the behavior of a producer-consumer pair of tasks in a
The nonlinear, or warped, resolvent recently explored by Giselsson and Bùi-Combettes has been used to model a large set of existing and new monotone inclusion algorithms. To establish convergent algorithms based on these resolvents, corrective projection steps are utilized in both works. We present a different way of ensuring convergence by means of a nonlinear momentum term, which in many cases l
Conflict analysis has been successfully generalized from Boolean satisfiability (SAT) solving to mixed integer programming (MIP) solvers, but although MIP solvers operate with general linear inequalities, the conflict analysis in MIP has been limited to reasoning with the more restricted class of clausal constraint. This is in contrast to how conflict analysis is performed in so-called pseudo-Bool
Mutation testing is the state-of-the-art technique for assessing the fault detection capacity of a test suite. Unfortunately, a full mutation analysis is often prohibitively expensive. The CppCheck project for instance, demands a build time of 5.8 min and a test execution time of 17 s on our desktop computer. An unoptimised mutation analysis, for 55,000 generated mutants took 11.8 days in total, o
Automated fault diagnosis can facilitate diagnostics assistance, speedier troubleshooting, and better-organised logistics. Currently, most AI-based prognostics and health management in the automotive industry ignore textual descriptions of the experienced problems or symptoms. With this study, however, we propose an ML-assisted workflow for automotive fault nowcasting that improves on current indu
