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Sobre a análise de pontos por função, considere as seguintes afirmativas:
1. É realizada com base na especificação funcional do software.
2. Estabelece uma pontuação para determinadas características do software, de acordo com seu nível de complexidade.
3. O valor resultante da análise de pontos por função é a quantidade de dias de duração do projeto.
4. A análise de pontos por função é restrita a softwares orientados a objetos.
5. Analisa entradas, saídas e consultas dos usuários, além dos dados utilizados pelo sistema.
Assinale a alternativa correta.
Sobre o Rational Unified Process (RUP), identifique como verdadeiras (V) ou falsas (F) as seguintes afirmativas:
( ) Utiliza DFDs (Diagrama de Fluxo de Dados) para definir o comportamento do sistema.
( ) Define um ciclo de vida de quatro fases para o desenvolvimento do software: concepção, elaboração, construção e transição.
( ) Um de seus fluxos (ou workflows) define como fazer o gerenciamento de configuração e mudança.
( ) Em seu fluxo de requisitos, sugere utilizar modelos de engenharia de software para a modelagem do negócio.
( ) Cada iteração do RUP segue uma abordagem semelhante à abordagem em cascata: contém atividades de requisitos e análise, projeto e implementação, integração e teste.
Assinale a alternativa que apresenta a sequência correta, de cima para baixo.
Com relação aos elementos do Scrum, numere a coluna da direita de acordo com sua correspondência com a coluna da esquerda.
1. Sprint.
2. Scrum Diária.
3. Revisão da Sprint.
4. Retrospectiva da Sprint.
( ) Reunião para inspeção das novas funcionalidades implementadas.
( ) Reunião com foco no aprimoramento do processo.
( ) Reunião de 15 minutos para identificação dos impedimentos.
( ) Ciclo completo de desenvolvimento de duração fixa que, ao final, resulta em um incremento de produto.
Assinale a alternativa que apresenta a numeração correta da coluna da direita, de cima para baixo
Considere a história de usuário abaixo:
“Como enfermeira, desejo registrar os dados de pressão arterial de um paciente para que eu possa acompanhar as mudanças na pressão arterial ao longo do dia.”
Sobre a forma como essa história de usuário está descrita e como é utilizada no desenvolvimento de software, considere as seguintes afirmativas:
1. Deve possuir a maior quantidade de detalhes possível no início do projeto, mesmo que não seja imediatamente implementada pela equipe de desenvolvimento.
2. Pode ser utilizada em projetos que adotam o método ágil Scrum.
3. Quando descreve uma funcionalidade maior, com menos detalhamento, é chamada de épico.
4. Idealmente, é especificada pelo Scrum Master em um projeto que adota Scrum.
5. No Scrum, o conjunto de histórias de usuário a serem implementadas em um projeto é chamado de Backlog do Desenvolvimento.
Assinale a alternativa correta.
Computer that reads body language
Researchers at Carnegie Mellon University’s Robotics Institute have enabled a computer to understand body poses and movements of multiple people from video in real time – including, for the first time, the pose of each individual’s hands and fingers.
Carnegie Mellon University researchers have developed methods to detect the body pose, including facial expressions and hand positions, of multiple individuals. This enables computers to not only identify parts of the body, but to understand how they are moving and positioned.
This new method was developed with the help of the Panoptic Studio, a two-story dome embedded with 500 video cameras. The insights gained from experiments in that facility now make it possible to detect the pose of a group of people using a single camera and a laptop computer.
Yaser Sheikh, associate professor of robotics, said these methods for tracking 2-D human form and motion open up new ways for people and machines to interact with each other, and for people to use machines to better understand the world around them. The ability to recognize hand poses, for instance, will make it possible for people to interact with computers in new and more natural ways, such as communicating with computers simply by pointing at things.
Detecting the nuances of nonverbal communication between individuals will allow robots to serve in social spaces, allowing robots to perceive what people around them are doing, what moods they are in and whether they can be interrupted. A self-driving car could get an early warning that a pedestrian is about to step into the street by monitoring body language. In sports analytics, real-time pose detection will make it possible for computers not only to track the position of each player on the field of play, as is now the case, but to also know what players are doing with their arms, legs and heads at each point in time. The methods can be used for live events or applied to existing videos.
“The Panoptic Studio supercharges our research”, Sheikh said. It now is being used to improve body, face and hand detectors by jointly training them. Also, as work progresses to move from the 2-D models of humans to 3-D models, the facility’s ability to automatically generate annotated images will be crucial.
When the Panoptic Studio was built a decade ago with support from the National Science Foundation, it was not clear what impact it would have, Sheikh said.
“Now, we’re able to break through a number of technical barriers primarily as a result of a grant 10 years ago”, he added. “We’re sharing the code, but we’re also sharing all the data captured in the Panoptic Studio”.
(Disponível: <https://www.sciencedaily.com/releases/2017/07/170706143158.htm>
Computer that reads body language
Researchers at Carnegie Mellon University’s Robotics Institute have enabled a computer to understand body poses and movements of multiple people from video in real time – including, for the first time, the pose of each individual’s hands and fingers.
Carnegie Mellon University researchers have developed methods to detect the body pose, including facial expressions and hand positions, of multiple individuals. This enables computers to not only identify parts of the body, but to understand how they are moving and positioned.
This new method was developed with the help of the Panoptic Studio, a two-story dome embedded with 500 video cameras. The insights gained from experiments in that facility now make it possible to detect the pose of a group of people using a single camera and a laptop computer.
Yaser Sheikh, associate professor of robotics, said these methods for tracking 2-D human form and motion open up new ways for people and machines to interact with each other, and for people to use machines to better understand the world around them. The ability to recognize hand poses, for instance, will make it possible for people to interact with computers in new and more natural ways, such as communicating with computers simply by pointing at things.
Detecting the nuances of nonverbal communication between individuals will allow robots to serve in social spaces, allowing robots to perceive what people around them are doing, what moods they are in and whether they can be interrupted. A self-driving car could get an early warning that a pedestrian is about to step into the street by monitoring body language. In sports analytics, real-time pose detection will make it possible for computers not only to track the position of each player on the field of play, as is now the case, but to also know what players are doing with their arms, legs and heads at each point in time. The methods can be used for live events or applied to existing videos.
“The Panoptic Studio supercharges our research”, Sheikh said. It now is being used to improve body, face and hand detectors by jointly training them. Also, as work progresses to move from the 2-D models of humans to 3-D models, the facility’s ability to automatically generate annotated images will be crucial.
When the Panoptic Studio was built a decade ago with support from the National Science Foundation, it was not clear what impact it would have, Sheikh said.
“Now, we’re able to break through a number of technical barriers primarily as a result of a grant 10 years ago”, he added. “We’re sharing the code, but we’re also sharing all the data captured in the Panoptic Studio”.
(Disponível: <https://www.sciencedaily.com/releases/2017/07/170706143158.htm>
Com base no texto, considere as seguintes informações:
1. O nome da instituição que desenvolveu a pesquisa.
2. O local onde está situado o estúdio Panoptic.
3. O número de pessoas que serviram como cobaias no experimento.
4. A época em que o estúdio foi construído.
5. A dificuldade de serem encontrados modelos humanos para interagir com computadores.
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