
This dataset contains anonymized information about the software architecture and the dependencies of a software system for Transmission Electron Microscopy (TEM) developed by Thermo Fisher Scientific. A TEM microscope is a software-intensive system composed of various complex instruments such as detectors, sample handling, vacuum, electromagnetic and electrostatic devices, which work together through coordinated software. Each type of device is managed by its own software subsystem, capturing the specific device functionalities. This creates a complex multi-level and multi-technology software ecosystem. The most basic of these levels is the component level. A component can contain one or more software projects contributing to an executable or a library. Related components are grouped in subsystems, which can be clustered in subsystem groups. The files in this dataset contain information about the actual dependencies between the components in the system and their containment in subsystems and subsystem groups. The dataset can be used for dependency analysis, impact assessment, visualization, and optimization of the software architecture.
Industrial dataset, Software Architecture, Software dependencies
Industrial dataset, Software Architecture, Software dependencies
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 1 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
