A database for publications published by researchers and students at SimulaMet.
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- Journal articles (272)
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- Edited books (3)
- Proceedings, refereed (302)
- Book chapters (13)
- Talks, keynote (22)
- PhD theses (9)
- Proceedings, non-refereed (19)
- Posters (13)
- Technical reports (14)
- Manuals (1)
- Talks, invited (181)
- 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 |
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 |
A logic-based event controller for means-end reasoning in simulation environments
SIMULATION 61 (2023).Status: Published
A logic-based event controller for means-end reasoning in simulation environments
Simulation games are designed to cultivate expertise and rehearse particular skill sets. To yield longitudinal effects, sequences of events must be crafted to yield intended learning outcomes, sometimes by focusing on particularly difficult situations and replaying variants. The present paper develops a logic-based approach for encoding the interrelation between action, events, and objects in a manner that allows the resulting scenario description to immediately be executed in a game development environment. This has the dual effect of decoupling the description of a scenario from the simulation platform itself, as well as supporting iterative and flexible development of learning content. To this end, we provide three interrelated components: First, we develop a scenario description language based on Answer Set Programming. The language is designed to allow an automated reasoner to deduce a schedule of the future events that are caused by an action taken in a given simulation environment. Second, we define a protocol for exchanging actions and computed futures between, respectively, the simulation environment and the external automated reasoner. Finally, as a proof of concept, we develop an Application Programming Interface (API) for the Unity Real-Time Development Platform that implements the protocol and offers a software framework for connecting the computed future events to concrete game objects. This allows the game to evolve coherently from the specification. We argue that the resulting system inherits capabilities for artificial commonsense reasoning from its declarative basis which are useful for reasoning about an evolving emergency incident or training scenario.
Afilliation | Software Engineering |
Project(s) | EDOS: Effective Digitalization of Public Sector |
Publication Type | Journal Article |
Year of Publication | 2023 |
Journal | SIMULATION |
Volume | 61 |
Date Published | 03/2023 |
Publisher | SAGE journals |
ISSN | 0037-5497 |
URL | http://journals.sagepub.com/doi/10.1177/00375497231157384http://journals... |
DOI | 10.1177/00375497231157384 |
Distributed Linear Network Operators via Successive Graph Shift Matrices
IEEE Transactions on Signal and Information Processing over Networks 9 (2023): 315-328.Status: Published
Distributed Linear Network Operators via Successive Graph Shift Matrices
Afilliation | Machine Learning |
Project(s) | Signal and Information Processing for Intelligent Systems |
Publication Type | Journal Article |
Year of Publication | 2023 |
Journal | IEEE Transactions on Signal and Information Processing over Networks |
Volume | 9 |
Pagination | 315-328 |
Date Published | 04/2023 |
Publisher | IEEE Transactions on Signal and Information Processing over Networks |
ISSN | 2373-776X |
Notes | This work is a joint collaboration between SimulaMet and University of Agder. This work was supported by the PETROMAKS Smart-Rig grant 244205 and the IKTPLUSS INDURB grant 270730/O70 from the Research Council of Norway. |
DOI | 10.1109/TSIPN.2023.3271148 |
Characteristics and generative mechanisms of software development productivity distributions
Information and Software Technology (2023).Status: Published
Characteristics and generative mechanisms of software development productivity distributions
Context: There is considerable variation in the productivity of software developers. Better knowledge about this variation may provide valuable inputs for the design of skill tests and recruitment processes. Objective: This paper aims to identify properties of software development productivity distributions and gain insight into mechanisms that potentially explain these productivity differences. Method: Four data sets that contain the results of software developers solving the same programming tasks were collected. The properties of the productivity distributions were analyzed, the fits of different types of distributions to the productivity data were compared, and potential generative mechanisms that would lead to the types of distributions with the best fit to the productivity data were evaluated. Results: The coefficient of variance of the productivity of the software developers was, on average, 0.55, with the top 50% of developers having average productivity that was 2.44 times higher than the bottom 50% of developers. All productivity samples were right-skewed, with an average skew of 1.79. About 30% of the observed productivity variance was explained by non-systematic, i.e., within-developer, variance. The distributions with the best fit to the empirical productivity data were the lognormal and power-law-with-an-exponential-cutoff distributions. The analysis of the mechanisms leading to productivity differences found no support for the "rich-getting-richer" explanation proposed for other disciplines. Instead, it suggests a constant productivity difference with increasing experience. Conclusion: The substantial difference in productivity among software developers solving programming tasks indicates that a thorough evaluation of skill in the recruitment process can be rewarding. In particular, the long tail towards higher productivity values demonstrates the large gains that can be achieved by detecting and recruiting developers with very high productivity. More research is needed to understand the mechanisms leading to the large productivity differences.
Afilliation | Software Engineering |
Project(s) | EDOS: Effective Digitalization of Public Sector |
Publication Type | Journal Article |
Year of Publication | 2023 |
Journal | Information and Software Technology |
Publisher | Elsevier |