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X-WR-CALDESC:Events for Software Center
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DTSTART;TZID=Europe/Stockholm:20210503T120000
DTEND;TZID=Europe/Stockholm:20210503T123000
DTSTAMP:20260526T174301
CREATED:20210302T103411Z
LAST-MODIFIED:20210503T123018Z
UID:2523-1620043200-1620045000@www.software-center.se
SUMMARY:Lunch seminar "Analyzing software code using artificial neural networks"
DESCRIPTION:Title: Analyzing software code using artificial neural networks \nSpeaker: Abu Naser Masud\, Senior Lecturer\, MDH \nDescription: Analyzing software code reveals many important aspects of the software such as bugs\, security vulnerabilities\, API recommendation\, code similarity\, code quality\, etc. The dominant code analysis techniques include static and dynamic program analyses. However\, artificial neural network (ANN) based source code analysis is a rising trend for the analysis of software. In this talk\, I shall present the general methodology of ANN-based source code analysis and discuss the potentials and limitations of this technique. \nLink to the recording of the presentation on YouTube:
URL:https://www.software-center.se/event/lunch-seminar-organized-by-theme-2-2/
LOCATION:MS Teams
CATEGORIES:Lunch seminar
ORGANIZER;CN="Jan Carlson":MAILTO:jan.carlson@mdh.se
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Stockholm:20210511T080000
DTEND;TZID=Europe/Stockholm:20210511T170000
DTSTAMP:20260526T174301
CREATED:20210510T113758Z
LAST-MODIFIED:20210511T154003Z
UID:2690-1620720000-1620752400@www.software-center.se
SUMMARY:Lunch seminar: Understanding Metrics Team-Stakeholder Communication
DESCRIPTION:Software Center lunch seminar organized by Theme 3\, Metrics: \nTitle: Understanding Metrics Team-Stakeholder Communication  \nAbstract: In our study\, we explore challenges in communication between metrics teams and stakeholders in agile metrics service delivery. Drawing on interviews and interactive workshops with team members and stakeholders at two different Swedish software development organizations\, we identify interrelated challenges such as aligning expectations\, prioritizing demands\, providing regular feedback\, and maintaining continuous dialogue\, which impede team-stakeholder interaction\, and negatively influence relationships and performance. In the session we will discuss the importance of understanding communicative hurdles and suggestions for their mitigation. \nSpeakers:\nDr. Nataliya Berbyuk Lindström\, Associate Professor\, University of Gothenburg\nDr. Dina Koutsikouri\, Associate Professor\, University of Gothenburg \nLink to the recorded presentation on YouTube:\nhttps://youtu.be/nVCTxo81wEM \n 
URL:https://www.software-center.se/event/lunch-seminar-understanding-metrics-team-stakeholder-communication/
CATEGORIES:Lunch seminar
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Stockholm:20210517T120000
DTEND;TZID=Europe/Stockholm:20210517T123000
DTSTAMP:20260526T174301
CREATED:20210511T124026Z
LAST-MODIFIED:20210517T145353Z
UID:2683-1621252800-1621254600@www.software-center.se
SUMMARY:Lunch seminar: Collaborative Traceability
DESCRIPTION:’Collaborative Traceability — Nine practices and why they (don’t) work’ \nMost welcome to the next Software Center Brown Bag seminar on May 17th. It is hosted by theme 4 (‘Customer Data and Ecosystem Driven Development’) and our speaker is Jan-Philipp Steghöfer\, Chalmers/University of Gothenburg. \nAbstract:\nTraceability information connects the artifacts created in a development process and allows\, i.a.\, analysing the impact of changes\, showing that all requirements are tested\, and creating safety cases. However\, traceability is elusive as it is\, and treating it as a collaborative issue increases the complexity. \nWe have\, together with practitioners\, identified nine crucial collaborative traceability practices that support an organisation in implementing traceability in their development processes. These practices range from the practical\, e.g.\, traceability dashboard\, to the organisational\, e.g.\, to have specific training for traceability. What is still unclear is why these practices are not always implemented\, how to select the ones that are most promising for an organisation\, and how organisations can adapt them to their own circumstances. \nIn this talk\, we are going to discuss the challenges of collaborative traceability and which role the nine practices for collaborative traceability play to address them. We will dive into one of them\, a cross-organisational traceability information model\, to show some of the challenges we see in practice. The presentation will leave ample room for discussion and allow you\, the audience\, to help shape our understanding of this elusive\, yet important topic. \nLink to the recorded presentation on YouTube:\nhttps://youtu.be/AjfsRo8plvA \n 
URL:https://www.software-center.se/event/lunch-seminar-collaborative-traceability/
LOCATION:Virtual event\, Sweden
CATEGORIES:Lunch seminar
ORGANIZER;CN="Helena Holmstr%C3%B6m Olsson":MAILTO:helena.holmstrom.olsson@mau.se
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Stockholm:20210518T130000
DTEND;TZID=Europe/Stockholm:20210518T153000
DTSTAMP:20260526T174301
CREATED:20210425T173745Z
LAST-MODIFIED:20210425T174017Z
UID:2657-1621342800-1621351800@www.software-center.se
SUMMARY:workshop on Business Agility 2.0
DESCRIPTION:This is an invite for a follow-up workshop on ‘Business Agility 2.0: The system architecture and platform dimensions’. \nThe reason for a ‘follow-up’ workshop\, is an agreement made during the workshop we organized on April 21st on the similar topics. The workshop received great attendance we had very good and interesting presentations and discussions. However\, we were not able to cover all the items on the agenda. The request from the group was to have more time for discussing the system architecture and platform dimensions as well as to find a slot for the R&D ways-of-working dimension that we didn’t cover. \nWith this invite\, we propose to continue our discussions on system architecture and platforms (as well as give space for the presentations we were not able to accommodate April 21st). \nAlso\, and if there is time for the third topic (R&D ways-of-working)\, we include this as well. If there is not time for this discussion\, we find a new slot for a workshop in which we focus on only the R&D ways-of-working (in the end of May). \nWe hope this finds you well and that those of you who are interested in continuing the April 21st discussions have the opportunity to join this follow-up workshop. Also\, we hope for those who could not make yesterday’s workshop to be able to join this opportunity. Finally\, we especially invite those companies who were not able to present yesterday due to time limitations\, as well as companies that didn’t attend yesterday but that would be interested in presenting. \nThe questions we shared as the basis for presentations and discussions were the following: \n\nSystem architecture: How do we design decoupling interfaces between the different technologies in the system (mechanics – electronics – software – data – AI) in order to allow for independent evolution on both sides of the interface?\nPlatform: How do we manage and/or reduce the number of variants derived from the platform in order to support continuous evolution of the system?\nR&D ways-of-working: How do we align the R&D ways-of-working with the transition we currently experience in business models (where we are moving from transactional to more continuous monetization)? For example\, to be able to experiment with new business models\, the R&D ways-of-working need to support/enable this. Similarly\, if complementing transactional models with more continuous models for monetization\, R&D needs to align with this transition.\n\nIdeally\, we ask you to prepare 1 – 2 slides that can be shared with everyone during the meeting (we look for short presentations of 8 – 10 minutes/company). Please note that what we look for are your current ways-of-working and your current practices with regard to the three questions. It can also be the challenges you experience and how you typically deal with these. The main intention is to have everyone share and involve in a discussion where the result is to learn\, to get ideas and to together identify common best practices for improving overall business agility. \nMost welcome – and please help us share this within your organizations as we are eager to offer this opportunity to everyone who attended already and to people who might be interested but didn’t yet attend.
URL:https://www.software-center.se/event/workshop-on-business-agility-2-0/
ORGANIZER;CN="Helena Holmstr%C3%B6m Olsson":MAILTO:helena.holmstrom.olsson@mau.se
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Stockholm:20210524T090000
DTEND;TZID=Europe/Stockholm:20210524T100000
DTSTAMP:20260526T174301
CREATED:20201214T085732Z
LAST-MODIFIED:20201214T085747Z
UID:2397-1621846800-1621850400@www.software-center.se
SUMMARY:Coordination team meeting
DESCRIPTION:
URL:https://www.software-center.se/event/coordination-team-meeting-43/
LOCATION:Virtual event\, Sweden
ORGANIZER;CN="Jan Bosch":MAILTO:jan.bosch@chalmers.se
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Stockholm:20210526T130000
DTEND;TZID=Europe/Stockholm:20210526T150000
DTSTAMP:20260526T174301
CREATED:20210425T173440Z
LAST-MODIFIED:20210426T060831Z
UID:2655-1622034000-1622041200@www.software-center.se
SUMMARY:Lic seminar: Data management and Data Pipelines
DESCRIPTION:Data management and Data Pipelines: An empirical investigation in the embedded systems domain \nCandidate: Aiswarya Raj Munappy \nContext: Companies are increasingly collecting data from all possible sources to extract insights that help in data-driven decision-making. Increased data volume\, variety\, and velocity and the impact of poor quality data on the development of data products are leading companies to look for an improved data management approach that can accelerate the development of high-quality data products. Further\, AI is being applied in a growing number of fields and thus it is evolving as a horizontal technology. Consequently\, AI components are increasingly been integrated into embedded systems along with electronics and software. We refer to these systems as AI-enhanced embedded systems. Given the strong dependence of AI on data\, this expansion also creates a new space for applying data management techniques. \nObjective: The overall goal of this thesis is to empirically identify the data management challenges encountered during the development and maintenance of AI-enhanced embedded systems\, propose an improved data management approach and empirically validate the proposed approach. \nMethod: To achieve the goal\, we conducted this research in close collaboration with Software Center companies using a combination of different empirical research methods: case studies\, literature reviews\, and action research. \nResults and conclusions: This research provides five main results. First\, it identifies key data management challenges specific to Deep Learning models developed at embedded system companies. Second\, it examines the practices such as DataOps and data pipelines that help to address data management challenges. We observed that DataOps is the best data management practice that improves the data quality and reduces the time to develop data products. The data pipeline is the critical component of DataOps that manages the data life cycle activities. The study also provides the potential faults at each step of the data pipeline and the corresponding mitigation strategies. Finally\, the data pipeline model is realized in a small piece of data pipeline and calculated the percentage of saved data dumps through the implementation. \nFuture work: As future work\, we plan to realize the conceptual data pipeline model so that companies can build customized robust data pipelines. We also plan to analyse the impact and value of data pipelines in cross-domain AI systems and data applications. We also plan to develop AI-based fault detection and mitigation system suitable for data pipelines. \nhttps://chalmers.zoom.us/j/69864251037
URL:https://www.software-center.se/event/lic-seminar-data-management-and-data-pipelines/
LOCATION:Virtual event\, Sweden
CATEGORIES:Event
ORGANIZER;CN="Helena Holmstr%C3%B6m Olsson":MAILTO:helena.holmstrom.olsson@mau.se
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Stockholm:20210530T080000
DTEND;TZID=Europe/Stockholm:20210531T170000
DTSTAMP:20260526T174301
CREATED:20210415T181240Z
LAST-MODIFIED:20210415T181240Z
UID:2640-1622361600-1622480400@www.software-center.se
SUMMARY:WAIN'21: 1st Workshop on AI Engineering
DESCRIPTION:WAIN’21 – 1st Workshop on AI Engineering – Software Engineering for AI\nThe aim of the workshop is to bring together researchers and practitioners in software engineering\, in data-science and AI\, and to build up a community that will target the new challenges emerging in Software Engineering that AI/data-science engineers and software engineers are facing in development of AI-based systems. The workshop will be highly interactive: In addition to the invited keynotes and short paper presentations\, there will be several discussion sessions. We plan to combine local and remote participation. \nhttps://conf.researchr.org/home/icse-2021/wain-2021
URL:https://www.software-center.se/event/wain21-1st-workshop-on-ai-engineering/
LOCATION:Virtual event\, Sweden
CATEGORIES:Event
ORGANIZER;CN="Jan Bosch":MAILTO:jan.bosch@chalmers.se
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Stockholm:20210531T120000
DTEND;TZID=Europe/Stockholm:20210531T123000
DTSTAMP:20260526T174301
CREATED:20210517T160629Z
LAST-MODIFIED:20210525T205244Z
UID:2701-1622462400-1622464200@www.software-center.se
SUMMARY:Lunch seminar: Are you using the MNIST dataset to compare the algorithms?
DESCRIPTION:Presenter: David Issa Mattos (PhD student\, Chalmers) \nOne of the most common tasks when developing a new tool is to benchmark it against competing tools. Both researchers and practitioners often look at the results of these benchmarks before selecting the appropriate tool. However\, the quality of the benchmark greatly influences the results. In this presentation\, we discuss how to evaluate if your benchmark has the appropriate difficulty level and is capable of differentiating the competing tools. We make an analogy with education and illustrate the assessment of benchmarks with two cases\, one in datasets for automated labeling algorithms and the other in optimization algorithms. In both cases\, the benchmarks are either too easy or too difficult and cannot be used to differentiate the tools. \n________________________________________________ \nMicrosoft Teams meeting \nJoin on your computer or mobile app \nClick here to join the meeting \nLearn More | Meeting options \n________________________________________________Make sure you and your colleagues registered on the SC_BB mailing list. You can do so at the following link: https://lists.chalmers.se/mailman/listinfo/sc_bb \n 
URL:https://www.software-center.se/event/lunch-seminar-3/
LOCATION:Virtual event\, Sweden
ORGANIZER;CN="Jan Bosch":MAILTO:jan.bosch@chalmers.se
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