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Developing new ideas and algorithms or comparing new findings in the field of requirements engineering and management implies a dataset to work with. Collecting the required data is time consuming, tedious, and may involve unforeseen difficulties. The need for datasets often forces re-searchers to collect data themselves in order to evaluate their findings. However, comparing results with other publications...
Existing work on identifying security requirements relies on training binary classification models using domain-specific data sets to achieve a high accuracy. Considering that domain-specific data sets are often not readily available, we propose a domain-independent model for classifying security requirements based on two key ideas. First, we train our model on the description of weaknesses from the...
Software datasets play a crucial role in advancing automated software traceability research. They can be used by researchers in different ways to develop or validate new automated approaches. The diversity and quality of the datasets within a research community have a significant impact on the accuracy, generalizability, and reproducibility of the results and consequently on the usefulness and practicality...
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