Extraction of Useful Information from Unstructured Data in Software Engineering: A Systematic Mapping
Published in Ibero-American Conference on Software Engineering, 2020
Context: A large number of information is generated and manipulated in Software Engineering (SE) projects. The technology surrounding this domain is constantly evolving. To keep up with such evolution , developers share their knowledge and seek help from other developers by means of interactive and collaborative environments. Understanding and extracting knowledge from these environments can enable developers to identify useful information for the project. Objective: This work aims to identify the main textual analysis approaches to extract useful information in the SE. Method: To achieve the proposed objective, we conducted a Systematic Mapping (SM). Results: We analyzed 69 relevant primary studies addressing approaches to extract useful information in the SE. Conclusion: Among the main conclusions of this study, we can infer that discussion forums attracted a significantly attention in SE context and it becomes one of the main textual databases investigated to extract useful information.
Recommended citation: SILVA, P. R.; SANTOS, V.; SOUZA, E. F.; FELIZARDO, K. R.; VIJAYKUMAR, N. L. (2020). "Extraction of Useful Information from Unstructured Data in Software Engineering: A Systematic Mapping." In: Ibero-American Conference on Software Engineering , Curitiba, Proceedings of Ibero-American Conference on Software Engineering , 2020.
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