Agile software development is one of the most important development paradigms these days. However, there are still some challenges to consider to reduce problems during the documentation process. Some assistive methods have been created to support developers in their documentation activities. In this regard, Natural Language Processing (NLP) can be used to create various related tools (such as assistants) to help with the documentation process. This paper presents the current state-of-the-art NLP techniques used in the agile development documentation process. A mapping review was done to complete the objective, the search strategy is used to obtain relevant studies from ScienceDirect, IEEE Xplore, ACM Digital Library, SpringerLink, and Willey. The search results after inclusion and exclusion criteria application left 47 relevant papers identified. These papers were analyzed to obtain the most used NLP techniques and NLP toolkits. The toolkits were also classified by the kind of techniques that are available in each of them. In addition, the behavior of the research area over time was analyzed using the relevant paper found by year. We found that performance measuring methods are not standardized, and, in consequence, the works are not easily comparable. In general, the number of related works and its distribution per year shows a growing trend of the works related to this topic in recent years; this indicates that the adoption of NLP techniques to improve agile methodologies is increasing.

Organizations frequently report problems finding skillful people to cover their most knowledge intensive vacancies. Being software engineering positions some of the such kind of jobs, there is a considerable gap between job postings and hiring skillful engineers in many software engineering organizations. In this paper, we will introduce the prototype of a web application that helps identifying Technical Knowledge (TK) in software development, to serve as a tool in the hiring process of software engineering positions, and in talent management. The purpose of this tool is to do an initial screening when opening a job position. All this is accomplished using Natural Language Processing (NLP) and Text Mining (TM) to analyze unstructured text in resumes and curriculum. We propose a way to use NLP and TM to identify knowledge profiles for Software Engineering Positions.

In the teaching-learning process under the competency-based educational model, the instructor is a facilitator and seeks to generate a flexible and adaptable environment for student learning. One of the first tasks of the facilitator is the structuring of didactic planning. Didactic planning includes strategies for teaching and learning, evidence gathering, and choice of evaluation instruments. In this paper, we propose a framework based on natural language processing techniques with the support of an ontology grounded in the experience of instructors and university level course plans in the information systems area. We employ Bloom’s taxonomy in the ontology design, producing an ascending structure for didactic planning, which allows the student to learn gradually. The developed framework can analyze the key elements that a didactic plan must contain and identify inter-related areas. Evaluation results with Cohen’s kappa coefficient between expert judgement and our framework show that is possible to assist instructors in structuring their didactic planning. Out of the nine processes analyzed with the framework, an almost perfect kappa level was achieved in five processes, a substantial level in three processes, and a moderate level for one process.