COURSE DESCRIPTION
This course provides an understanding of automating software testing using program analysis with the goal of intelligently and algorithmically creating tests. The course covers search-based test generation, combinatorial and random testing while highlighting the challenges associated with the use of automatic test generation.
You will learn:
This course deals with model-based testing, a class of technologies shown to be effective and efficient in assessing the quality and correctness of large software systems. Throughout the course the participants will learn how to design and use model-based testing tools, how to create realistic models and how to use these models to automate the testing process in their organisation.
Explore the different tools and software to design, test, and prototype custom robot parts and robust robot behaviour. In recent years, industries around the world have been getting creative when it comes to incorporating robotics into their workflows. This three-week course offers a fascinating introduction to software and tools currently used in robotics. You’ll build basic knowledge of robotics tools and learn how they can be adapted for different industries. Familiarise yourself with Ubuntu operating system and Gazebo framework Gain hands-on experience using 3D robotics models in simulation Learn from the experts at the cutting edge of control engineering, robotics, and AI This course is designed for anyone interested in using robotic solutions in their role and who wants to learn the basics of robotics frameworks. The course will be given in English.
The information and communication technology (ICT) sector is responsible for approx. 1.8-2.8% of the global greenhouse gas (GHG) emissions in 2020, and software is both part of the problems and the solutions. Traditional software engineering principles and techniques do not consider the climate, environment, and sustainability aspects in building and using software for any purpose. We, software engineers, developers, researchers, climate scientists, and various other related stakeholders, need to think about how we can reduce the carbon footprint due to building and using software-intensive systems. Green and sustainable software engineering is an emerging concept that can help reduce the carbon footprint related to software. In this introductory course, we will introduce the concept of green and sustainable software engineering and the engineering process to build green and sustainable software. Topics Sustainable and green computing Sustainable and green software engineering Process Energy efficient computing Sustainability issues in Scientific computing You will learnBy the end of the course, you will be able to: analyze the green and sustainability issues in traditional software engineering, identify and incorporate key elements to be included in the software engineering process to make the software green and sustainable, and use techniques to make your software code energy efficient. Who is the course for?This course is designed for those who are software developers, managers and software related policy makers, or have knowledge about software development, and want to consider the green and sustainability aspects in their everyday life. Also, this course will be useful for computational scientists who build green software and want to know more about these aspects in software engineering. However, this is an introductory course, and it will show a path for life-long learning to build more in-depth knowledge in each concept introduced in this course.
In this course, you will learn how data analysis in virtual production can improve your organization's results! Data analytics in virtual production uses advanced techniques to collect, analyze and present data to improve production. This system is designed to help companies optimize their production and increase efficiency. By learning how to model, do scenario analysis and evaluate using industrial software, identify bottlenecks, and use AI methods and applications, you will get all the tools necessary to succeed with a full production analysis. The course is given with flexible start and study pace, but we recommend a study pace of 20 %, which means that the course takes about 8 calendar weeks.
Virtual commissioning (VC) is a technique used in the field of automation and control engineering to simulate and test a system's control software and hardware in a virtual environment before it is physically implemented. The aim is to identify and correct any issues or errors in the system before deployment, reducing the risk of downtime, safety hazards, and costly rework. The virtual commissioning process typically involves creating a digital twin of the system being developed, which is a virtual representation of the system that mirrors its physical behaviour. The digital twin includes all the necessary models of the system's components, such as sensors, actuators, controllers, and interfaces, as well as the control software that will be running on the real system. Once the digital twin is created, it can be tested and optimized in a virtual environment to ensure that it behaves correctly under various conditions. The benefits of using VC include reduced project costs, shortened development time, improved system quality and reliability, and increased safety for both operators and equipment. By detecting and resolving potential issues in the virtual environment, engineers can avoid costly and time-consuming physical testing and debugging, which can significantly reduce project costs and time to market. The course includes different modules, each with its own specific role in the process. Together, the modules create a comprehensive virtual commissioning process that makes it possible to test and validate control systems and production processes in a simulated environment before implementing them in the real world. Modeling and simulation: This module involves creating a virtual model of the system using simulation software. The model includes all the equipment, control systems, and processes involved in the production process. Control system integration: This module involves integrating the digital twin with the control system, allowing engineers to test and validate the system's performance. Virtual sensors and actuators: This module involves creating virtual sensors and actuators that mimic the behavior of the physical equipment. This allows engineers to test the control system's response to different scenarios and optimize its performance. Scenario testing: This module involves simulating different scenarios, such as equipment failures, power outages, or changes in production requirements, to test the system's response. Data analysis and optimization: This module involves analyzing data from the virtual commissioning process to identify any issues or inefficiencies in the system. Engineers can then optimize the system's performance and ensure that it is safe and reliable. Expected outcomes Describe the use of digital twins for virtual commissioning process. Develop a simulation model of a production system using a systems perspective and make a plan for data collection and analysis. Plan different scenarios for the improvement of a production process. Analyze data from the virtual commissioning process to identify any issues or inefficiencies in the system and then optimize the system's performance. Needs in the industry Example battery production: Battery behaviors are changing over time. To innovate at speed and scale, testing and improving real-world battery phenomena throughout its lifecycle is necessary. Virtual commissioning / modeling-based approaches like digital twin can provide us with accurate real-life battery behaviors and properties, improving energy density, charging speed, lifetime performance and battery safety. Faster innovation (NPI) Lower physical prototypes Shorter manufacturing cycle time Rapid testing of new battery chemistry and materials to reduce physical experiments Thermal performance and safety It’s not just about modelling and simulating the product, but also validating processes from start to finish in a single environment for digital continuity. Suggested target groups Industry personnel Early career engineers involved in commissioning and simulation projects Design engineers (to simulate their designs at an early stage in a virtual environment to reduce errors) New product introduction engineers Data engineers Production engineers Process engineers (mediators between design and commissioning) Simulation engineers Controls engineer System Integration
Kursperiod 1/11 till 19/12 2025 Innehåll Batterivärdekedjan: från processer uppströms till nedströms Åldrande batterier: Hur batterier förändras över tiden och vilka risker det är med. Toxicitet: Fokus på material och deras påverkan på miljö och hälsa. Säkerhetsaspekter: Riskbedömning och hantering av batterier i olika skeden av deras livscykel. Livscykelanalys: Miljö- och hållbarhetsperspektiv. Kursens upplägg Kursen kommer att ske som en synkron onlinekurs (fjärrundervisning) för maximal flexibilitet för deltagarna. Kursen kommer att innehålla onlineföreläsningar, diskussionstillfällen, ett kort individuellt projekt, skriftliga reflektioner. För att slutföra kursen krävs en arbetsinsats på ca 40 h. Du kommer att få kunskap om Kursdeltagaren kommer att lära sig följande: Grunderna för batterisäkerhetsfrågor och toxicitet längs batterivärdekedjan En introduktion till livscykelanalys Kunskaper för hantering av åldrande batterier Vem vänder sig kursen till? Kursen vänder sig till personer inom logistik, automation, energiproduktion och byggsektorn. Främst de som hanterar batterier i fordonsflottor, arbetar med säkerhets- och hållbarhetsfrågor inom fordonsindustrin, arbetar med integration av batterier i lokala och nationella energisystem/infrastruktur. Helst har deltagarna en utbildning inom teknik eller naturvetenskap. Deltagare bör ha vissa förkunskaper om batterier, genom teknisk/naturvetenskaplig universitetsutbildning, eller genom en grundläggande öppen kurs.