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 |
Coverage and Deployment Analysis of Narrowband Internet of Things in the Wild
IEEE Communications Magazine (2020).Status: Accepted
Coverage and Deployment Analysis of Narrowband Internet of Things in the Wild
Narrowband Internet of Things (NB-IoT) is gaining momentum as a promising technology for massive Machine Type Communication (mMTC). Given that its deployment is rapidly progressing worldwide, measurement campaigns and performance analyses are needed to better understand the system and move toward its enhancement. With this aim, this paper presents a large scale measurement campaign and empirical analysis of NB-IoT on operational networks, and discloses valuable insights in terms of deployment strategies and radio coverage performance. The reported results also serve as examples showing the potential usage of the collected dataset, which we make open- source along with a lightweight data visualization platform.
| Afilliation | Communication Systems |
| Project(s) | Department of Mobile Systems and Analytics |
| Publication Type | Journal Article |
| Year of Publication | 2020 |
| Journal | IEEE Communications Magazine |
| Publisher | IEEE |
| Notes | Preprint available here: https://arxiv.org/abs/2005.02341 |
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 |