Vol 9, No 3 (2021): Special issue - XVI Ibero-American Conference on Software Engineering and Knowledge Engineering - JIISIC 2021

Objective: This work aimed to build a SMS (Systematic Mapping Study) for the identification and classification of problems and causes in testing in the MSA (Micro-Service Architecture). Methodology: This SMS adopted established practices in evidence-based software engineering. The SMS considered articles published since 2016 in databases such as ACM, IEEE Xplore, Science Direct, WoS, Springer, and Scopus. In addition, the search strategy included four snowball iterations. Results: The SMS started with 842 studies and ended with 32 selected studies, identifying nine problems and eight causes related to software testing in MSA. Finally, the studies were classified by problems and causes. Conclusions: The SMS allowed deducing that High Complexity in MSA testing is the most representative problem. Likewise, the most outstanding causes are the High Number of Services, the Lack of Research, and the proliferation of each service version (Service Versioning).

Objective: Describe the structuring of an architecture based on cybersecurity to mitigate malicious network traffic in IoT devices. Methodology: For this, a methodology based on 4 phases was used, of which, it begins with the identification and selection of emerging technologies that have the greatest impact on IoT cybersecurity, followed by the identification of the artificial intelligence algorithm that presents The characteristics that best adapt to the proposed structure, later on the appropriate monitoring technique was determined to capture and monitor in real time the traffic that circulates through these IoT devices, to finally make the determination of the architecture. Results: In this way, an architecture designed under three layers was obtained, where each layer contains the previous selection made in the respective phases. Conclusions: Obtaining a design that allows real-time monitoring of the traffic that circulates through IoT devices, considering data storage, which is subsequently processed under the AI ​​(Artificial Intelligence) algorithm and will determine the creation of new rules to notify possible anomalies.

Objective: This paper aims to develop a sentiment and text analysis study, to evaluate the perception of the attendees to a virtual entrepreneurship fair, which was designed and adapted to remote attendance with the support of ICT within the "Entrepreneurship" course of the Chemical Engineering Program of the University of Cartagena. Methodology: For the development of this work, four methodological phases were defined, namely: design and organization of the fair, preparation, and adaptation of the data from the perception surveys, text analysis and finally sentiment analysis on the results of the qualitative questions. Results: The sentiment analysis study showed that the polarities with the greatest contribution from the evaluators and participants were neutral and positive, who highlighted creativity in the organization and use of ICTs. Conclusions: It was concluded that the proposal designed for the development of the virtual entrepreneurship fair had a positive impact and can be considered as a reference for its extrapolation in the development of different academic events during the pandemic. Likewise, it was concluded that sentiment analysis techniques can be adequate for the analysis of perception questionnaires in different application contexts.

Objective: To build the first prototype of a smart ecological point that assists the user in the correct classification of solid waste at the point of origin using Deep Learning, providing new technologies focused on mitigating climate impact caused by poor solid waste management. Methodology: to conduct the research, the Toyota LEAN methodology and the Solid Works tool were implemented to design a prototype according to the needs of an ecological point, including a structural analysis and weight tests in order to measure its resistance capacity. The agile methodology applied for the development of the artificial intelligence and the conformation of the set of images was extreme programming. Results and conclusions: a dataset of three classes was built according to resolution 2184 of 2019 of Colombia, containing a total of 400 samples taken from the prototype. The sorting model using a low computational cost architecture - MobileNet - obtained an accuracy of 97.91% in the validation and a kappa coefficient of 0.95. The trained model runs on a Raspberry Pi in order to minimize production costs. The research presents a test of acceptance and usability of the prototype.

Objective: To identify research works focused on MOOCs K-12 or STEAM, focused on the potential of education environments, reshaping the current educational framework in secondary education. Methodology: Equations were defined to search for articles published in conferences and journals using bibliographic databases, which allowed subtracting the articles to build the corpus of references. Subsequently, the most significant investigations for the development of the systematic review are analyzed and synthesized. Results: This review will identify trends, challenges, and opportunities on MOOC K-12 or STEAM, identifying the implementations of courses in computer science or computational thinking in education. This type of initiative has obtained favorable results since the number of students who select computer programming as a fundamental axis in the national exam for higher education has increased. Conclusions: Most of the research has focused on incorporating programming with complementary courses offered optionally in secondary education, with a combined approach, that is, traditional classes are carried out with the support of MOOCs. Most MOOCs for secondary education have explicitly been implemented to meet the needs of secondary education teachers and students to enhance and support the curriculum and motivate students as future active members in creating technology.

Objective: To evaluate a software product, the result of the research project entitled Methodology for the development of immersive virtual reality applications that comply with the principles of universal design, in order to validate the inclusion and accessibility of the experience for users with different abilities. Methodology: Virtual reality is a technology that allows the user to simulate experiences in a 3D virtual world created by humans through software and that requires an additional device such as glasses or a helmet. However, its use is limited for people with disabilities. The process of developing accessible virtual reality applications is bound to include all people. The applied RVI-A methodology is based on the accessibility requirements for visually and hearing impaired people. Results: To assess the quality of the software from the perspective of users with hearing and visual disabilities, user-centred usability tests were conducted using heuristic methods with experts, and empirical methods with real users, to determine whether the software met the criteria of understanding, learning, operability, attractiveness and conformity of use. Conclusions: The work allowed us to conclude through the usability results that the software met the user requirements and the expected quality, while the user experience was positive, managing to include visually and hearing impaired people, decreasing the technological gap that exists between the real world and the virtual world, improving this type of applications.

Objective: This research aims to study the state of the art of software reuse, focused on success factors and adoption barriers. Methodology: To reach the objective, a literature review was conducted in which we adopted some elements from a Systematic Mapping Study (SMS). This literature review was divided into five stages: (i) definition of research questions, (ii) definition of the search strategy, (iii) definition of the inclusion and exclusion criteria, (iv) search conduction, and finally, (v) resolution of the research questions. Results: The paper compiles 26 factors that influence software reuse and common adoption barriers found in the literature. These factors are generally classified into four perspectives: organizational factors, business factors, technological factors, and process factors. Conclusions: The resulting factors could be used to introduce software reuse practices and understand the state of the art of software reuse in companies. In addition, resulting factors could be used in the software industry to know its current state of the practice.

Objective: Determine and characterize the current state of the knowledge about the location criteria of data processing, using computational intelligence techniques in an Intelligent Objects Ecosystem of Web of Things. Methodology: The systematic review presented below is based on the studies carried out by Petersen and Kitchenham, four research questions were proposed, the PICOC method was applied to identify the keywords, a search chain and four search engines were proposed, the inclusion and exclusion criteria of primary studies were proposed, as well as the quality evaluation criteria, the data extraction strategy and the synthesis method. Results: It was possible to answer the four research questions proposed, finding that most of the studies lack an implementation in the three analyzed locations and a single study compares the performance obtained by a computational intelligence algorithm when processing information in different locations of the ecosystem. Conclusions: The need to continue carrying out studies in the area of the localization of processing in intelligent ecosystems was demonstrated using computational intelligence techniques for processing in different locations. In addition, there is evidence of a need to place greater emphasis on comparing the performance obtained when carrying out implementations taking into account different computational intelligence techniques.