## 2 Background and Related Work
### Related Works  
[PERSON] et al. [7] conducted a Systematic Mapping Study (SMS) in 2015 focused on domain ontologies in the context of RE. The goal of their work was to identify and get a detailed insight into the usage of domain ontologies in RE activities. Their search strategy included only an automated search in electronic databases and was run on June 2014. They selected and analyzed 67 primary studies to answer four research questions. Their key findings were: (1) in the context of RE, ontologies are related to requirements elicitation, analysis and verification, conflict identification and analysis, and unification among requirements formalisms; (2) the majority of the studies (59%) were found to be related to requirements elicitation and analysis; (3) there is a lack of evaluation studies on the usage of ontologies in RE; (4) most of the selected studies (80.6%) reported about general purpose software applications. In 2016, [PERSON] et al. [8] conducted an SLR focused on the applications of ontologies in RE. The main goal of their work was to get a more profound and better understanding of the support that ontologies bring to RE phases. The authors used the classification of RE process proposed by [PERSON] and [PERSON] [6]. Automated search in databases was the only search strategy used and covered the period from January 2007 to October 2013. In their work, they analyzed the requirements modelling styles, the type of supported requirements and the ontology languages that have been used. Data were extracted from 67 selected primary studies to answer a set of seven research questions. The main findings of their study were: (1) the most frequently reported benefits from using ontologies in RE were reducing ambiguity, incompleteness and inconsistency of requirements (57% of the studies), followed by requirements management and evolution (36%) and domain knowledge representation (27%); (2) ontologies support a great diversity of RE modelling styles, mainly textual requirements and UML; (3) studies addressed only functional requirements (52%) or a combination of functional and non-functional (45%), only 3% of the studies reported just non-functional requirements; (4) although a great variety of ontologies were found, none of them have been widely adopted by the research community. These findings are limited by the context of selected papers (78% academic and 22% industrial setting). The work from [PERSON] et al. shows a very high level of quality and a sound research method. [PERSON] et al. [9] conducted an SLR study to identify, analyze and classify possible reasons of human errors that occur during requirements engineering and their impact on software quality. They only used an automated search strategy in electronic databases, conducted from 2006 to October 2014. The data were extracted from 38 selected primary studies. The authors developed a Human Error Taxonomy (HET), based on their results and by extending a previous Requirement Error Taxonomy [32]. The HET is based on [PERSON]'s taxonomy that comprised of slips, lapses, and mistakes. The mapping of the HET to all phases of RE revealed that there is a lack of evidence about errors for requirements verification and management phases. Their main contributions were: (1) introducing and applying the human error research to a novel software quality improvement domain via interaction between RE experts and cognitive psychology researchers; (2) identifying and classifying the human errors, facilitating a systematic way to comprehend and avoid those that arise during human-centric activities of requirements engineering. An SLR focused on the Requirements Change Management (RCM) process was conducted by [PERSON] et al. [10] in 2018. Their study aimed to investigate the causes of requirements changes, processes and techniques used for RCM and how the organizations deal with decision making during RCM process. They ran an automated search in six electronic databases but did not report the search date or the covered period. Data were extracted from 184 primary studies.