An Introduction to Data Analytics for Software Security

AuthorBen Othmane, L.; Brucker, A.D.; Dashevskyi, S.; Tsalovski, P.
TypeBook Article
AbstractExtracting knowledge from data using data analytical techniques requires identifying the research goal, collecting data, preparing the data, exploring the data, developing analytical models, and analyzing the developed models. The knowledge could be acquired by testing theoretical models using empirical research methods such as data analytics. Testing theoretical models using data analytical techniques requires expressing the problem to be investigated as a question, which may be divided into subquestions. The main challenge in data analytics is the availability of data. Often, the researcher needs to collect artifacts that could be used for testing theoretical models. Data collection is iterative. At the beginning, the researcher may start with an initial dataset that has a limited set of attributes. Such dataset may be provided by the entity that has an interest in the research results or was identified by the researcher. Collected datasets have often data attributes where their values are frequently missing.
PartBen Othmane, L.: Empirical Research for Software Security: Foundations and Experience. Boca Raton, Fla.: CRC Press, 2017. (CRC Series in security, privacy and trust), pp. 69-94
PartnISBN : 9781498776424