A database for publications published by researchers and students at SimulaMet.
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Research area
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- Journal articles (266)
- Books (9)
- Edited books (3)
- Proceedings, refereed (297)
- Book chapters (13)
- Talks, keynote (21)
- PhD theses (9)
- Proceedings, non-refereed (19)
- Posters (13)
- Technical reports (13)
- Manuals (1)
- Talks, invited (178)
- Talks, contributed (30)
- Public outreach (62)
- Miscellaneous (21)
Journal articles
Determining a core view of research quality in empirical software engineering
Computer Standards & Interfaces 84 (2023).Status: Published
Determining a core view of research quality in empirical software engineering
Context:
Research quality is intended to appraise the design and reporting of studies. It comprises a set of standards such as methodological rigor, practical relevance, and conformance to ethical standards. Depending on the perspective, different views of importance are given to the standards for research quality.
Objective:
To investigate the suitability of a conceptual model of research quality to Software Engineering (SE), from the perspective of researchers engaged in Empirical Software Engineering (ESE) research, in order to understand the core value of research quality.
Method:
We conducted a mixed-methods approach with two distinct group perspectives: (i) a research group; and (ii) the empirical SE research community. Our data collection approach comprised a questionnaire survey and a complementary focus group. We carried out a hierarchical voting prioritization to collect relative values for importance of standards for research quality.
Results:
In the context of this research, ‘internally valid’, ‘relevant research idea’, and ‘applicable results’ are perceived as the core standards for research quality in empirical SE. The alignment at the research group level was higher compared to that at the community level.
Conclusion:
The conceptual model was seen to express fairly the standards for research quality in the SE context. It presented limitations regarding its structure and components’ description, which resulted in an updated model.
| Afilliation | Software Engineering |
| Project(s) | EDOS: Effective Digitalization of Public Sector |
| Publication Type | Journal Article |
| Year of Publication | 2023 |
| Journal | Computer Standards & Interfaces |
| Volume | 84 |
| Publisher | Elsevier |
A longitudinal explanatory case study of coordination in a very large development programme: the impact of transitioning from a first- to a second-generation large-scale agile development method
Empirical Software Engineering 28, no. 1 (2023).Status: Published
A longitudinal explanatory case study of coordination in a very large development programme: the impact of transitioning from a first- to a second-generation large-scale agile development method
Large-scale agile development has gained widespread interest in the software industry, but it is a topic with few empirical studies of practice. Development projects at scale introduce a range of new challenges in managing a large number of people and teams, often with high uncertainty about product requirements and technical solutions. The coordination of teams has been identified as one of the main challenges. This study presents a rich longitudinal explanatory case study of a very large software development programme with 10 development teams. We focus on inter-team coordination in two phases: one that applies a first-generation agile development method and another that uses a second-generation one. We identified 27 coordination mechanisms in the first phase, and 14 coordination mechanisms in the second. Based on an analysis of coordination strategies and mechanisms, we develop five propositions on how the transition from a first- to a second-generation method impacts coordination. These propositions have implications for theory and practice.
| Afilliation | Software Engineering |
| Project(s) | EDOS: Effective Digitalization of Public Sector |
| Publication Type | Journal Article |
| Year of Publication | 2023 |
| Journal | Empirical Software Engineering |
| Volume | 28 |
| Issue | 1 |
| Date Published | Jan-01-2023 |
| Publisher | Springer Nature |
| ISSN | 1382-3256 |
| Keywords | coordination mechanisms, inter-team coordination, large-scale agile development, multiteam systems, software development process, Software Engineering |
| URL | https://rdcu.be/c3FQ4 |
| DOI | 10.1007/s10664-022-10230-6 |
Torgeir Dingsøyr is adjunct chief research scientist at the SimulaMet research laboratory. His research has focused on teamwork and learning in software development, as well as development methods for large software projects and programs. He has published in the software engineering, information systems and project management fields. His main position is professor in software engineering – agile at the Department of Computer Science, Norwegian University of Science and Technology.
Finding shortest and nearly shortest path nodes in large substantially incomplete networks by hyperbolic mapping
Nature Communications 14 (2023).Status: Published
Finding shortest and nearly shortest path nodes in large substantially incomplete networks by hyperbolic mapping
<p>Dynamic processes on networks, be it information transfer in the Internet, contagious spreading in a social network, or neural signaling, take place along shortest or nearly shortest paths. Computing shortest paths is a straightforward task when the network of interest is fully known, and there are a plethora of computational algorithms for this purpose. Unfortunately, our maps of most large networks are substantially incomplete due to either the highly dynamic nature of networks, or high cost of network measurements, or both, rendering traditional path finding methods inefficient. We find that shortest paths in large real networks, such as the network of protein-protein interactions and the Internet at the autonomous system level, are not random but are organized according to latent-geometric rules. If nodes of these networks are mapped to points in latent hyperbolic spaces, shortest paths in them align along geodesic curves connecting endpoint nodes. We find that this alignment is sufficiently strong to allow for the identification of shortest path nodes even in the case of substantially incomplete networks, where numbers of missing links exceed those of observable links. We demonstrate the utility of latent-geometric path finding in problems of cellular pathway reconstruction and communication security.</p>
| Afilliation | Communication Systems |
| Project(s) | The Center for Resilient Networks and Applications |
| Publication Type | Journal Article |
| Year of Publication | 2023 |
| Journal | Nature Communications |
| Volume | 14 |
| Number | 186 |
| Publisher | Nature |
Training Performance Indications for Amateur Athletes Based on Nutrition and Activity Lifelogs
Algorithms, no. 1 (2023): 30.Status: Published
Training Performance Indications for Amateur Athletes Based on Nutrition and Activity Lifelogs
| Afilliation | Machine Learning |
| Project(s) | Department of Holistic Systems |
| Publication Type | Journal Article |
| Year of Publication | 2023 |
| Journal | Algorithms |
| Issue | 1 |
| Pagination | 30 |
| Date Published | Jan-01-2023 |
| Publisher | MDPI |
| URL | https://www.mdpi.com/1999-4893/16/1/30 |
| DOI | 10.3390/a16010030 |
MatCoupLy: Learning coupled matrix factorizations with Python
SoftwareX 21, no. 101294 (2023).Status: Published
MatCoupLy: Learning coupled matrix factorizations with Python
| Afilliation | Machine Learning |
| Project(s) | Department of Data Science and Knowledge Discovery |
| Publication Type | Journal Article |
| Year of Publication | 2023 |
| Journal | SoftwareX |
| Volume | 21 |
| Issue | 101294 |
| Date Published | Feb-01-2023 |
| Publisher | Elsevier |
| ISSN | 2352-7110 |
| URL | https://linkinghub.elsevier.com/retrieve/pii/Shttps://www.sciencedirect.... |
| DOI | 10.1016/j.softx.2022.101292 |
A multi-center polyp detection and segmentation dataset for generalisability assessment
Nature Scientific Data 10 (2023).Status: Published
A multi-center polyp detection and segmentation dataset for generalisability assessment
| Afilliation | Machine Learning |
| Project(s) | Department of Holistic Systems |
| Publication Type | Journal Article |
| Year of Publication | 2023 |
| Journal | Nature Scientific Data |
| Volume | 10 |
| Publisher | Nature |
| URL | https://doi.org/10.1038/s41597-023-01981-y |
| DOI | 10.1038/s41597-023-01981-y |
Approximate Bayesian Inference Based on Expected Evaluation
Bayesian Analysis 1, no. 1 (2023).Status: Published
Approximate Bayesian Inference Based on Expected Evaluation
Approximate Bayesian computing (ABC) and Bayesian Synthetic likelihood (BSL) are two popular families of methods to evaluate the posterior distribution when the likelihood function is not available or tractable. For existing variants of ABC and BSL, the focus is usually first put on the simulation algorithm, and after that the form of the resulting approximate posterior distribution comes as a consequence of the algorithm. In this paper we turn this around and firstly define a reasonable approximate posterior distribution by studying the distributional properties of the expected discrepancy, or more generally an expected evaluation, with respect to generated samples from the model. The resulting approximate posterior distribution will be on a simple and interpretable form compared to ABC and BSL.
Secondly a Markov chain Monte Carlo (MCMC) algorithm is developed to simulate from the resulting approximate posterior distribution. The algorithm was evaluated on a synthetic data example and on the Stepping Stone population genetics model, demonstrating that the proposed scheme has real world applicability. The algorithm demonstrates competitive results with the BSL and sequential Monte Carlo ABC algorithms, but is outperformed by the ABC MCMC.
| Afilliation | Communication Systems, Machine Learning |
| Project(s) | Department of Holistic Systems |
| Publication Type | Journal Article |
| Year of Publication | 2023 |
| Journal | Bayesian Analysis |
| Volume | 1 |
| Issue | 1 |
| Date Published | Jan-01-2023 |
| Publisher | Project euclid |
| URL | https://projecteuclid.org/journals/bayesian-analysis/volume--1/issue--1/... |
| DOI | 10.1214/23-BA1368 |
Proceedings, refereed
Detecting human embryo cleavage stages using YOLO v5 object detection algorithm
In Nordic Artificial Intelligence Research and Development. Springer, 2023.Status: Published
Detecting human embryo cleavage stages using YOLO v5 object detection algorithm
| Afilliation | Machine Learning |
| Project(s) | Department of Holistic Systems |
| Publication Type | Proceedings, refereed |
| Year of Publication | 2023 |
| Conference Name | Nordic Artificial Intelligence Research and Development |
| Pagination | 81-93 |
| Publisher | Springer |
On the realization of Cloud-RAN on Mobile Edge Computing
In International Conference on Advanced Information Networking and Applications (AINA-2023). 655th ed. Vol. 3. Lecture Notes in Networks and Systems: Springer, 2023.Status: Published
On the realization of Cloud-RAN on Mobile Edge Computing
| Afilliation | Communication Systems |
| Project(s) | The Center for Resilient Networks and Applications |
| Publication Type | Proceedings, refereed |
| Year of Publication | 2023 |
| Conference Name | International Conference on Advanced Information Networking and Applications (AINA-2023) |
| Volume | 3 |
| Edition | 655 |
| Date Published | 03/2023 |
| Publisher | Springer |
| Place Published | Lecture Notes in Networks and Systems |
| ISBN Number | 978-3-031-28693-3 |
Talks, invited
Extracting Insights from Complex Data: Constrained Multimodal Data Mining using Coupled Matrix and Tensor Factorizations
In IPAM Workshop on Explainable AI for the Sciences: Towards Novel Insights, 2023.Status: Published
Extracting Insights from Complex Data: Constrained Multimodal Data Mining using Coupled Matrix and Tensor Factorizations
| Afilliation | Machine Learning |
| Project(s) | Department of Data Science and Knowledge Discovery , TrACEr: Time-Aware ConstrainEd Multimodal Data Fusion |
| Publication Type | Talks, invited |
| Year of Publication | 2023 |
| Location of Talk | IPAM Workshop on Explainable AI for the Sciences: Towards Novel Insights |
| URL | http://www.ipam.ucla.edu/abstract/?tid=18155&pcode=XAI2023 |
