A database for publications published by researchers and students at SimulaMet.
Status
Research area
Journal articles
Relations Between Effort Estimates, Skill Indicators, and Measured Programming Skill
Transactions on Software Engineering (2020).Status: Accepted
Relations Between Effort Estimates, Skill Indicators, and Measured Programming Skill
There are large skill differences among software developers, and clients and managers will benefit from being able to identify those with better skill. This study examines the relations between low effort estimates, and other commonly used skill indicators, and measured programming skill. One hundred and four professional software developers were recruited. After skill-related information was collected, they were asked to estimate the effort for four larger and five smaller programming tasks. Finally, they completed a programming skill test. The lowest and most over-optimistic effort estimates for the larger tasks were given by those with the lowest programming skill, which is in accordance with the well-known Dunning-Kruger effect. For the smaller tasks, however, those with the lowest programming skill had the highest and most over-pessimistic estimates. The other programming skill indicators, such as length of experience, company assessed skill and self-assessed skill, were only moderately correlated with measured skill and not particularly useful in guiding developer skill identification. A practical implication is that for larger and more complex tasks, the use of low effort estimates and commonly used skill indicators as selection criteria leads to a substantial risk of selecting among the least skilled developers.
| Afilliation | Software Engineering |
| Project(s) | Department of IT Management |
| Publication Type | Journal Article |
| Year of Publication | 2020 |
| Journal | Transactions on Software Engineering |
| Publisher | IEEE |
Sequence effects in the estimation of software development effort
Journal of Systems and Software (2020).Status: Accepted
Sequence effects in the estimation of software development effort
Currently, little is known about how much the sequence in which software development tasks or projects are estimated affects judgment-based effort estimates. To gain more knowledge, we examined estimation sequence effects in two experiments. In the first experiment, 362 software professionals estimated the effort of three large tasks of similar sizes, whereas in the second experiment 104 software professionals estimated the effort of four large and five small tasks. The sequence of the tasks was randomised in both experiments. The first experiment, with tasks of similar size, showed a mean increase of 10% from the first to the second and a 3% increase from the second to the third estimate. The second experiment showed that estimating a larger task after a smaller one led to a mean decrease in the estimate of 24%, and that estimating a smaller task after a larger one led to a mean increase of 25%. There was no statistically significant reduction in the sequence effect with higher competence. We conclude that more awareness about how the estimation sequence affects the estimates may reduce potentially harmful estimation biases. In particular, it may reduce the likelihood of a bias towards too low effort estimates.
| Afilliation | Software Engineering |
| Project(s) | Department of IT Management |
| Publication Type | Journal Article |
| Year of Publication | 2020 |
| Journal | Journal of Systems and Software |
| Publisher | Elsevier |
Estimating an Additive Path Cost with Explicit Congestion Notification
IEEE Transactions on Control of Network Systems (2020).Status: Accepted
Estimating an Additive Path Cost with Explicit Congestion Notification
Network Utility Maximization (NUM) is a well accepted theoretical framework that describes how congestion controls cooperate to achieve an ideal sending rate allocation, for given utility functions of senders and constraints of the network. These network constraints are expressed as a "cost'' in the framework. In practice, most congestion control mechanisms obtain feedback that is different from the framework's "cost''. This paper focuses on Explicit Congestion Notification (ECN), which has been shown to be advantageous when it is available, e.g. with the popular Datacenter TCP (DCTCP) mechanism. However, different from the framework's cost, ECN marks are not additive. We present a practical solution to this problem. Our solution changes how end hosts interpret the ECN signal, while for the router side, a special configuration of RED is used.
| Afilliation | Communication Systems |
| Project(s) | Department of Mobile Systems and Analytics |
| Publication Type | Journal Article |
| Year of Publication | 2020 |
| Journal | IEEE Transactions on Control of Network Systems |
| Publisher | IEEE |
Proceedings, refereed
The Influence of Players Strategy on the perceived delay
In 2020 Twelfth International Conference on Quality of Multimedia Experience (QoMEX), 2020.Status: Accepted
The Influence of Players Strategy on the perceived delay
| Afilliation | Machine Learning |
| Project(s) | Department of Holistic Systems |
| Publication Type | Proceedings, refereed |
| Year of Publication | 2020 |
| Conference Name | 2020 Twelfth International Conference on Quality of Multimedia Experience (QoMEX) |
Quality Estimation Models for Gaming Video Streaming Services Using Perceptual Video Quality Dimensions
In ACM Multimedia Systems Conference 2020 (MMSys 2020), 2020.Status: Accepted
Quality Estimation Models for Gaming Video Streaming Services Using Perceptual Video Quality Dimensions
| Afilliation | Machine Learning |
| Project(s) | Department of Holistic Systems |
| Publication Type | Proceedings, refereed |
| Year of Publication | 2020 |
| Conference Name | ACM Multimedia Systems Conference 2020 (MMSys 2020) |
A Latency Compensation Technique Based on Game Characteristics to Mitigate the Influence of Delay on Cloud Gaming Quality of Experience
In ACM Multimedia Systems Conference 2020 (MMSys 2020), 2020.Status: Accepted
A Latency Compensation Technique Based on Game Characteristics to Mitigate the Influence of Delay on Cloud Gaming Quality of Experience
| Afilliation | Machine Learning |
| Project(s) | Department of Holistic Systems |
| Publication Type | Proceedings, refereed |
| Year of Publication | 2020 |
| Conference Name | ACM Multimedia Systems Conference 2020 (MMSys 2020) |
Assessing Interactive Gaming Quality of Experience Using a Crowdsourcing Approach
In 2020 Twelfth International Conference on Quality of Multimedia Experience (QoMEX), 2020.Status: Accepted
Assessing Interactive Gaming Quality of Experience Using a Crowdsourcing Approach
| Afilliation | Machine Learning |
| Project(s) | Department of Holistic Systems |
| Publication Type | Proceedings, refereed |
| Year of Publication | 2020 |
| Conference Name | 2020 Twelfth International Conference on Quality of Multimedia Experience (QoMEX) |
Delay Sensitivity Classification of Cloud Gaming Content
In International Workshop on Immersive Mixed and Virtual Environment Systems (MMVE'20), 2020.Status: Accepted
Delay Sensitivity Classification of Cloud Gaming Content
| Afilliation | Machine Learning |
| Project(s) | Department of Holistic Systems |
| Publication Type | Proceedings, refereed |
| Year of Publication | 2020 |
| Conference Name | International Workshop on Immersive Mixed and Virtual Environment Systems (MMVE'20) |
Optical Fibre as a Sensor for Network Anomaly Detection
In ACM SIGCOMM 2020 Workshop on Optical Systems Design, 2020.Status: Accepted
Optical Fibre as a Sensor for Network Anomaly Detection
Optical fibres are the backbone of modern Information Technology infrastructure connecting billions of users through high-speed networks. With a drastic increase in the number of internet users, vulnerability and security issues in the optical fibre network become increasingly important. In this paper, we propose a detection method for early warning of anomalies in optical networks. The method is based on monitoring and analyzing changes in the state of polarization of the optical signal targeting differentiating between different physical impacts and movements of the fibre caused by e.g. eavesdropping, cut by digging and thunderstorms.
| Afilliation | Communication Systems |
| Project(s) | GAIA |
| Publication Type | Proceedings, refereed |
| Year of Publication | 2020 |
| Conference Name | ACM SIGCOMM 2020 Workshop on Optical Systems Design |
Proceedings, refereed
Predicting Sperm Motility and Morphology using Deep Learning and Handcrafted Features
In MediaEval, 2019.Status: Accepted
Predicting Sperm Motility and Morphology using Deep Learning and Handcrafted Features
This paper presents the approach proposed by the organizer team (SimulaMet) for MediaEval 2019 Multimedia for Medicine: The Medico Task. The approach uses a data preparation method which is based on global features extracted from multiple frames within each video and then combines this with information about the patient in order to create a compressed representation of each video. The goal is to create a less hardware expensive data representation that still retains the temporal information of the video and related patient data. Overall, the results need some improvement before being a viable option for clinical use.
| Afilliation | Machine Learning |
| Project(s) | Department of Holistic Systems |
| Publication Type | Proceedings, refereed |
| Year of Publication | 2019 |
| Conference Name | MediaEval |