The purpose of this study was to evaluate the usability perception of seniors on video game use with different control devices. Twenty-four seniors participated in the study (12 women, 12 men, 69 years old in average) and eight children (8 years old in average). The setting included the use of two Kinect motion sensors, three computers, three projectors, three video cameras, two audio devices, the Angry Birds and Happy Sky videogames, one Xbox 360 console, a Nintendo Wii device and a Touchscreen configured so that participants could play the games in senior–child pairs. Data were collected according to user friendliness, experience and social interaction. This study suggests that video game control devices for seniors should be adapted to compensate for their function, sensor and cognitive limitations.

Software Development is a complex process, in which every software product is a knowledge representation of all the involved people. In agile software development, knowledge is prone to vaporise, because documentation is not a priority as indicated in the agile manifesto. This condition generates problems such as poor understanding of the requirements, knowledge transfer deficiency among developers, time wasted by developers while searching for knowledge. The objective of this work is to reduce architectural knowledge vaporisation by means of knowledge condensation to support expertise location (high‐level knowledge at a given time). This through an ontology that will condensate the knowledge in the code phase. This study presents the description of an ontology development process following the Methontology Framework. Results show that the proposed ontology does not present incongruence or inconsistency and answers the competency questions correctly. The main contribution of this study is the ontology which brings several benefits such as a shared concept of the knowledge in the code phase and a way to link the artefacts (resources used by developers in the project) and the experts (artefacts provider).

To develop software to stimulate cognitive functions of attention, memory, reasoning, planning, language, and perception in Mexican older adults, and to evaluate the usability of software based on system utility, information quality, and interface quality. For the development of the cognitive stimulation software, an inductive-deductive methodology was used in three stages: Analysis (system requirements), design and coding (cognitive stimulation software), evaluation (usability results). The usability of the software was assessed in 89 older adults between the ages of 60 and 84 years, through a usability questionnaire with evidence of reliability and validity. Eight exercises about attention, seven on memory, three on reasoning, one about planning and language, and two on perception were developed. We evaluated the usability of the developed software using the Computer System Usability Questionnaire, obtaining medium-high usability in 76.2% of the participants regarding the system utility, in 77.7% concerning the information quality and, in 84.2% in the interface quality. The software was developed considering aspects of usability and based on changes and losses associated with aging, as well as on the stimulation of cognitive functions related to instrumental activities of daily living, including exercises based on traditional pencil-paper exercises.

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.

Nowadays, Agile and Global Software Development (AGSD) has brought benefits and new challenges to the software industry. Among the main challenges is Architecture Knowledge Management (AKM), due to the following reasons: (i) in Agile Software Development team members prefer to convey knowledge in a face‐to‐face manner, over transmitting it through formal documents; and (ii) an efficient AKM in Global Software Development involves managing explicit knowledge. These opposite paradigms turn AKM into an unsolved issue in AGSD. In this study, the authors present a systematic mapping review about AKM in AGSD. From this review, they identified nine approaches that AGSD companies use to overcome the AKM challenge, which are grouped in three areas: (i) documentation artefact‐based, (ii) communication‐based, and (iii) methodological‐based. Also, they found that the selected papers evenly support the three phases of the integrated knowledge management cycle (creation/capture, sharing/dissemination and acquisition/application), although only 7% of them support the capture of architectural knowledge in a formalised way. Finally, they conclude proposing critical points to consider in the implementation of AKM solutions in AGSD, and presenting their directions of future work.

Estimating during the early stages is crucial for determining the feasibility and conducting the budgeting and planning of agile software development (ASD) projects. However, due to the characteristics of ASD and limited initial information, these estimates are often complicated and inaccurate. This study aims to systematically map the literature to identify the most used estimation techniques; the reasons for their selection; the input artifacts, predictors, and metrics associated with these techniques; as well as research gaps in early-stage estimations in ASD. This study was based on the guidelines proposed by Kitchenham for systematic literature reviews in software engineering; a review protocol was defined with research questions and criteria for the selection of empirical studies. Results show that data-driven techniques are preferred to reduce biases and inconsistencies of expert-driven techniques. Most selected studies do not mention input artifacts, and software size is the most commonly used predictor. Machine learning-based techniques use publicly available data but often contain records of old projects from before the agile movement. The study highlights the need for tools supporting estimation activities and identifies key areas for future research, such as evaluating hybrid approaches and creating datasets of recent projects with sufficient contextual information and standardized metrics.