tag:blogger.com,1999:blog-10883866549011141132024-03-13T08:41:29.770-03:00Lógica de Programaçãoedu.classhttp://www.blogger.com/profile/07852022298031914548noreply@blogger.comBlogger23125tag:blogger.com,1999:blog-1088386654901114113.post-2059423142041300582014-12-08T23:15:00.000-02:002014-12-08T23:15:06.320-02:0018 - AleatórioPrimeiramente muito obrigado a todos que curtiram a pagina/blog/videos.<br />
<br />
Lamento por não conseguir dar vazão a todos os pedidos.<br />
<br />
Resolvi resolver este por ser mais simples e rápido.<br />
<br />
<br />
Nessa aula iremos resolver este exercício:<br />
<br />
Dado os 4 valores inteiros: 10 - 20 - 30 - 40<br />
Faça um algoritmo para escolher aleatoriamente um desses valores e o escreva na tela.<br />
<br />
<span style="background-color: yellow;"><a href="https://www.facebook.com/LogicaDeProgramacao">https://www.facebook.com/LogicaDeProgramacao</a></span><br />
<br />
Um abraço!<br />
<br />
Uma possível solução<br />
<br />
<div class="separator" style="clear: both; text-align: center;">
<object width="320" height="266" class="BLOGGER-youtube-video" classid="clsid:D27CDB6E-AE6D-11cf-96B8-444553540000" codebase="http://download.macromedia.com/pub/shockwave/cabs/flash/swflash.cab#version=6,0,40,0" data-thumbnail-src="https://i.ytimg.com/vi/06QPfkso7_g/0.jpg"><param name="movie" value="https://www.youtube.com/v/06QPfkso7_g?version=3&f=user_uploads&c=google-webdrive-0&app=youtube_gdata" /><param name="bgcolor" value="#FFFFFF" /><param name="allowFullScreen" value="true" /><embed width="320" height="266" src="https://www.youtube.com/v/06QPfkso7_g?version=3&f=user_uploads&c=google-webdrive-0&app=youtube_gdata" type="application/x-shockwave-flash" allowfullscreen="true"></embed></object></div>
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<br />edu.classhttp://www.blogger.com/profile/07852022298031914548noreply@blogger.com4tag:blogger.com,1999:blog-1088386654901114113.post-6581558342260686242013-11-21T00:05:00.001-02:002013-11-21T00:05:50.371-02:0017 - Levantamento do estoque de camisetas(Porcentagem)Nessa aula iremos resolver este exercício:<br />
<br />
Construa o programa que permita fazer o levantamento do estoque<br />
de camisetas de uma serigrafia. A loja possui um estoque de camisetas<br />
nas cores: branca, preta, vermelha, azul e verde;<br />
E nos tamanhos “P”, “M”, “G” e “GG”.<br />
Especifique a quantidade de camisetas de cada cor e cada tamanho,<br />
a quantidade e porcentagem de cada tamanho de uma mesma cor<br />
e a porcentagem de cada cor em relação ao total.<br />
quantidade de camisetas é desconhecida. O usuário digitará “S” para sair<br />
<br />
Quem acompanha o blog, por favor dar um like na página do face abaixo:<br />
<br />
<a href="https://www.facebook.com/LogicaDeProgramacao" style="background-color: yellow;">https://www.facebook.com/LogicaDeProgramacao</a><br />
<br />
Um abraço!<br />
<br />
Uma possível solução<br />
<br />
<div class="separator" style="clear: both; text-align: center;">
<iframe allowfullscreen='allowfullscreen' webkitallowfullscreen='webkitallowfullscreen' mozallowfullscreen='mozallowfullscreen' width='320' height='266' src='https://www.youtube.com/embed/yuJHlESmnGE?feature=player_embedded' frameborder='0'></iframe></div>
edu.classhttp://www.blogger.com/profile/07852022298031914548noreply@blogger.com2tag:blogger.com,1999:blog-1088386654901114113.post-3382494837959098652013-11-20T13:20:00.001-02:002013-11-20T13:20:51.317-02:0016 - Soma dos elementos de uma matrizNessa aula iremos resolver este exercicio:<br />
<br />
Escrever um algoritmo que leia uma matriz M(6,6) e calcule as somas das partes hachuradas e escreva a matriz M e as somas calculadas.<br />
<br />
Quem acompanha o blog, por favor dar um like na página do face abaixo:<br />
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<br />
Um abraço!<br />
<br />
uma possível solução<br />
<br />
<div class="separator" style="clear: both; text-align: center;">
<iframe allowfullscreen='allowfullscreen' webkitallowfullscreen='webkitallowfullscreen' mozallowfullscreen='mozallowfullscreen' width='320' height='266' src='https://www.youtube.com/embed/ClNdm1KqoSI?feature=player_embedded' frameborder='0'></iframe></div>
<br />edu.classhttp://www.blogger.com/profile/07852022298031914548noreply@blogger.com2tag:blogger.com,1999:blog-1088386654901114113.post-52636246219100935522013-10-31T00:05:00.001-02:002013-10-31T00:05:47.643-02:0015 - Calculo de RaizesNessa aula, iremos calcular a raiz quadrada ou cubica ou qualquer uma... de um número passado.<br />
<br />
Quem acompanha o blog, por favor dar um like na página do face abaixo:<br />
<br />
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<br />
Como costumo dizer, temos aqui uma possível solução<br />
<br />
Espero que ajude a quem precisar.<br />
<br />
<div class="separator" style="clear: both; text-align: center;">
<iframe allowfullscreen='allowfullscreen' webkitallowfullscreen='webkitallowfullscreen' mozallowfullscreen='mozallowfullscreen' width='320' height='266' src='https://www.youtube.com/embed/20uOWqqflFE?feature=player_embedded' frameborder='0'></iframe></div>
<br />edu.classhttp://www.blogger.com/profile/07852022298031914548noreply@blogger.com1tag:blogger.com,1999:blog-1088386654901114113.post-26445728588805169502013-09-23T23:06:00.000-03:002013-09-23T23:12:05.402-03:0014 - Número PerfeitoNeste exercício iremos solucionar o exercício abaixo, muito parecido com o anterior do quadrado perfeito:<br />
<br />
Dado um numero, identificar se ele é um número perfeito ou não.<br />
<br />
Quem acompanha o blog, por favor dar um like na página do face abaixo:<br />
<br />
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<br />
Como costumo dizer, temos aqui uma possível solução<br />
Espero que ajude a quem precisar.<br />
<br />
<div class="separator" style="clear: both; text-align: center;">
<iframe allowfullscreen='allowfullscreen' webkitallowfullscreen='webkitallowfullscreen' mozallowfullscreen='mozallowfullscreen' width='320' height='266' src='https://www.youtube.com/embed/Q6syl06UXRE?feature=player_embedded' frameborder='0'></iframe></div>
<br />edu.classhttp://www.blogger.com/profile/07852022298031914548noreply@blogger.com1tag:blogger.com,1999:blog-1088386654901114113.post-41038386371030825912013-09-02T20:44:00.001-03:002013-09-23T23:00:55.860-03:0013 - Quadrado Perfeito Nesse exercício iremos elaborar um algoritmo para verificar se o número lido é um quadrado perfeito ou não.<br />
<div>
<br /></div>
<div>
Quem acompanha o blog, por favor dar um like na página do face abaixo:</div>
<div>
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<div>
<b style="font-family: Arial, Tahoma, Helvetica, FreeSans, sans-serif; font-size: 13px; line-height: 18px; text-decoration: none;"><span style="background-color: yellow; font-size: medium;"><span style="color: red;"><a href="https://www.facebook.com/LogicaDeProgramacao" style="font-family: Arial, Tahoma, Helvetica, FreeSans, sans-serif; font-size: 13px; line-height: 18px; text-decoration: none;">https://www.facebook.com/LogicaDeProgramacao</a> </span></span></b></div>
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<b style="font-family: Arial, Tahoma, Helvetica, FreeSans, sans-serif; font-size: 13px; line-height: 18px; text-decoration: none;"><span style="background-color: yellow; font-size: medium;"><span style="color: red;"><br /></span></span></b></div>
<div>
<span style="background-color: #141414; color: white; font-family: Arial, Tahoma, Helvetica, FreeSans, sans-serif; font-size: 13px; line-height: 18px;">Como costumo dizer, temos aqui uma possível solução</span><br />
<span style="background-color: #141414; color: white; font-family: Arial, Tahoma, Helvetica, FreeSans, sans-serif; font-size: 13px; line-height: 18px;">Espero que ajude a quem precisar.</span></div>
<div>
<b style="background-color: #141414; color: #444444; font-family: Arial, Tahoma, Helvetica, FreeSans, sans-serif; font-size: 13px; line-height: 18px; text-decoration: none;"><span style="background-color: yellow; font-size: medium;"><br /></span></b></div>
<div class="separator" style="clear: both; text-align: center;">
<iframe allowfullscreen='allowfullscreen' webkitallowfullscreen='webkitallowfullscreen' mozallowfullscreen='mozallowfullscreen' width='320' height='266' src='https://www.youtube.com/embed/GEk-VfZIPXU?feature=player_embedded' frameborder='0'></iframe></div>
<div>
<b style="background-color: #141414; color: #444444; font-family: Arial, Tahoma, Helvetica, FreeSans, sans-serif; font-size: 13px; line-height: 18px; text-decoration: none;"><span style="background-color: yellow; font-size: medium;"><br /></span></b></div>
edu.classhttp://www.blogger.com/profile/07852022298031914548noreply@blogger.com0tag:blogger.com,1999:blog-1088386654901114113.post-63269972417667421942013-08-21T22:14:00.000-03:002013-08-21T22:14:57.672-03:0012 - Desenhando MATRIZPrimeiramente gostaria de informar que criei uma pagina para o blog no facebook, minha ideia e centralizar quaisquer discussões se um dia tiver.<br />
<br />
Quem acompanha o blog passa la e da um like =)<br />
<br />
<a href="https://www.facebook.com/LogicaDeProgramacao"><b><span style="background-color: yellow; font-size: large;">https://www.facebook.com/LogicaDeProgramacao</span></b></a><br />
<br />
Nesse exercício iremos aprender como gerar a matriz abaixo:<br />
<br />
<div class="separator" style="clear: both; text-align: center;">
<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgTrKzYS5kM1wSoI-cGLz5t0XNlLkng5vAVqea8b5RcFY5cQL64ZVgoKcixSPFguzMUh3n-nm6j9CZo6Nf9k11zc21-b9wgDSfphtig-nDNr7yfLqNp3V6Jl6sJGFxTdBNFYl6XeIMIgg2Q/s1600/MATRIZ.jpg" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" height="196" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgTrKzYS5kM1wSoI-cGLz5t0XNlLkng5vAVqea8b5RcFY5cQL64ZVgoKcixSPFguzMUh3n-nm6j9CZo6Nf9k11zc21-b9wgDSfphtig-nDNr7yfLqNp3V6Jl6sJGFxTdBNFYl6XeIMIgg2Q/s200/MATRIZ.jpg" width="200" /></a></div>
<br />
Como costumo dizer, temos aqui uma possível solução<br />
Espero que ajude a quem precisar.<br />
um abraço.<br />
<br />
<div class="separator" style="clear: both; text-align: center;">
<iframe allowfullscreen='allowfullscreen' webkitallowfullscreen='webkitallowfullscreen' mozallowfullscreen='mozallowfullscreen' width='320' height='266' src='https://www.youtube.com/embed/4Cc6bHfVbSs?feature=player_embedded' frameborder='0'></iframe></div>
<br />edu.classhttp://www.blogger.com/profile/07852022298031914548noreply@blogger.com0tag:blogger.com,1999:blog-1088386654901114113.post-7572897226969534032013-07-16T01:43:00.002-03:002013-07-16T01:47:48.802-03:0011 - Algoritmos - Visualg - Soma dos elementos de uma matriz 3x3Depois de um longo tempo sem nada, venho aqui trazer mais uma aula, mais um algoritmo resolvido, como sempre costumo dizer "uma das possíveis soluções".<br />
<br />
Exercício:<br />
<br />
Ler uma matriz de 3x3 e dizer a quantidade de valores lidos, a quantidade números pares lidos e a quantidade de números impares lidos:<br />
<br />
<br />
Abaixo uma possível solução<br />
<br />
<br />
<br />
<div class="separator" style="clear: both; text-align: center;">
<iframe allowfullscreen='allowfullscreen' webkitallowfullscreen='webkitallowfullscreen' mozallowfullscreen='mozallowfullscreen' width='320' height='266' src='https://www.youtube.com/embed/GsJdc9TTQL4?feature=player_embedded' frameborder='0'></iframe></div>
<br />
Código da aula:<br />
<br />
algoritmo "semnome"<br />
<br />
var<br />
matriz:vetor[0..2,0..2] de inteiro<br />
somaPar,somaImpar,somaTodos, linha, coluna:inteiro<br />
<br />
inicio<br />
<br />
somaPar <-0<br />
somaImpar <-0<br />
somaTodos <-0<br />
<br />
para linha de 0 ate 2 faca<br />
para coluna de 0 ate 2 faca<br />
<span style="color: red;">leia(matriz[linha,coluna])</span><br />
<span style="color: red;"> somaTodos <- somaTodos + 1</span><br />
<span style="color: red;"> se (matriz[linha,coluna] % 2) = 0 entao</span><br />
<span style="color: red;"> somaPar <- somaPar + 1</span><br />
<span style="color: red;"> senao</span><br />
<span style="color: red;"> somaImpar <- somaImpar +1</span><br />
<span style="color: red;"> fimse</span><br />
fimpara<br />
fimpara<br />
<br />
escreval("escrevendo a matriz")<br />
para linha de 0 ate 2 faca<br />
para coluna de 0 ate 2 faca<br />
escreval(matriz[linha,coluna])<br />
fimpara<br />
fimpara<br />
<br />
escreval("quantidade de numeros lidos ", <span style="color: red;">somaTodos</span>)<br />
escreval("quantidade de numeros impares lidos ", <span style="color: red;">somaImpar</span>)<br />
escreval("quantidade de numeros pares lidos ", <span style="color: red;">somaPar</span>)<br />
<br />
<br />
<br />
fimalgoritmo<br />
<div>
<br /></div>
edu.classhttp://www.blogger.com/profile/07852022298031914548noreply@blogger.com1tag:blogger.com,1999:blog-1088386654901114113.post-55820588602051855432013-07-02T00:33:00.000-03:002013-07-02T00:40:01.478-03:0010 - funçoes e procedimentosDepois de um longo tempo sem nada, venho aqui trazer mais uma aula, mais um algoritmo resolvido, como sempre costumo dizer "uma das possíveis soluções".<br />
<div>
<br /></div>
<div>
Hoje resolvi fazer um vídeo sobre um tema não abordado aqui antes, <b>procedimentos e funções</b><br />
<b><br /></b>
Nesse vídeo criamos um programa que le por um procedimento dois números e chama uma função para a somatória dos mesmos.<br />
<br />
Vídeo:<br />
<br />
<div class="separator" style="clear: both; text-align: center;">
<iframe allowfullscreen='allowfullscreen' webkitallowfullscreen='webkitallowfullscreen' mozallowfullscreen='mozallowfullscreen' width='320' height='266' src='https://www.youtube.com/embed/-mAAbMBUZJk?feature=player_embedded' frameborder='0'></iframe></div>
<br />
Código da aula:<br />
<br />
algoritmo "<span style="color: red;">10 - funçoes e procedimentos</span>"<br />
<br />
var<br />
<br />
<span style="color: #0b5394;">funcao somarNumeros (num1, num2 : inteiro):inteiro</span><br />
var soma:inteiro<br />
inicio<br />
soma <- (num1 + num2)<br />
retorne soma<br />
fimfuncao<br />
<br />
<span style="color: #0b5394;">procedimento lerNumeros()</span><br />
var x,y:inteiro<br />
inicio<br />
leia(x)<br />
escreval()<br />
leia(y)<br />
escreval()<br />
<span style="color: #38761d;">//chamar a funcao que retorna somatoria</span><br />
escreval(somarNumeros(x,y))<br />
<br />
fimprocedimento<br />
<br />
inicio<br />
<span style="color: #38761d;">//chamar procedimento que le os dois numeros</span><br />
lerNumeros()<br />
fimalgoritmo<br />
<!-----><!-----><!-----></div>
edu.classhttp://www.blogger.com/profile/07852022298031914548noreply@blogger.com0tag:blogger.com,1999:blog-1088386654901114113.post-75795714905319970122012-12-05T01:50:00.002-02:002012-12-05T02:09:08.526-02:00Correção - EX. 04 - Maior Número Nesse video, irei mostrar uma correção sugerida por um anonimo..<br />
<br />
Link do exercicio:<br />
<br />
http://www.logicasdeprogramacao.blogspot.com.br/2011/06/ex-04-maior-numero.html <br />
<br />
segue:<br />
<br />
<div class="separator" style="clear: both; text-align: center;">
<iframe allowfullscreen='allowfullscreen' webkitallowfullscreen='webkitallowfullscreen' mozallowfullscreen='mozallowfullscreen' width='320' height='266' src='https://www.youtube.com/embed/nF7fUkTYkSw?feature=player_embedded' frameborder='0'></iframe></div>
<br />
Espero que de alguma forma ajude a quem interessar.<br />
<br />
Att,<br />
<br />
Eduardo V. de Souza<br />
<br />edu.classhttp://www.blogger.com/profile/07852022298031914548noreply@blogger.com1tag:blogger.com,1999:blog-1088386654901114113.post-85539613868914277462012-11-30T00:32:00.003-02:002012-12-03T08:56:52.035-02:00Pedido 1 - Ordenação de Vetor<a href="http://www.blogger.com/blogger.g?blogID=1088386654901114113" imageanchor="1" style="clear: right; float: right; margin-bottom: 1em; margin-left: 1em;"></a>Pessoal,<br />
<br />
<a href="http://www.blogger.com/blogger.g?blogID=1088386654901114113" imageanchor="1" style="clear: right; float: right; margin-bottom: 1em; margin-left: 1em;"></a>Depois de muito tempo sem postar nada, motivado pela frequente visita de estudantes, resolvi fazer uma video aula ( primeira ).<br />
<br />
A qualidade nao está das melhores, assistam em tela cheia para melhor visualizar, nos proximos farei testes antes de gravar.<br />
<br />
Errei ao narrar alguns numeros, e algumas mensagens do meu micro apareceram, resovi nao editar nada, e é isso. <br />
<br />
<div class="separator" style="clear: both; text-align: center;">
</div>
O pedido foi feito por um anonimo:<br />
<br />
<br />
<div class="comment-header" id="bc_0_5M" kind="m">
<cite class="user">Anônimo</cite><span class="icon user"></span><span class="datetime secondary-text"><a href="http://logicasdeprogramacao.blogspot.com/2011/06/ex08-numeros-pares-e-impares-de-um.html?showComment=1353012407803#c17017954474264000" rel="nofollow">15 de novembro de 2012 18:46</a></span></div>
<div class="comment-content" id="bc_0_5MC">
Tem como me ajudar com esse aqui? <br />
<br />
"Escreva um algoritmo que leia um vetor de 100 posições e mostre-o ordenado em ordem crescente."</div>
<div class="comment-content" id="bc_0_5MC">
<br /></div>
<div class="comment-content" id="bc_0_5MC">
segue o video de uma possível resposta:</div>
<br />
<br />
<div class="separator" style="clear: both; text-align: center;">
<object class="BLOGGER-youtube-video" classid="clsid:D27CDB6E-AE6D-11cf-96B8-444553540000" codebase="http://download.macromedia.com/pub/shockwave/cabs/flash/swflash.cab#version=6,0,40,0" data-thumbnail-src="http://i.ytimg.com/vi/HXFmTzJ_xLw/0.jpg" height="266" width="320"><param name="movie" value="http://www.youtube.com/v/HXFmTzJ_xLw?version=3&f=user_uploads&c=google-webdrive-0&app=youtube_gdata" /><param name="bgcolor" value="#FFFFFF" /><param name="allowFullScreen" value="true" /><embed width="320" height="266" src="http://www.youtube.com/v/HXFmTzJ_xLw?version=3&f=user_uploads&c=google-webdrive-0&app=youtube_gdata" type="application/x-shockwave-flash" allowfullscreen="true"></embed></object></div>
<br />
<div class="comment-content" id="bc_0_5MC">
<br /></div>
<div class="comment-content" id="bc_0_5MC">
<br /></div>
<div class="comment-content" id="bc_0_5MC">
Abaixo, codigo gerado na video aula.</div>
<div class="comment-content" id="bc_0_5MC">
<br /></div>
<div class="comment-content" id="bc_0_5MC">
algoritmo "Ordenação de vetores"<br />
<br />
var<br />
<span style="color: red;"> vet : vetor[1..5] de inteiro</span><br />
<span style="color: red;"><br /></span>
<span style="color: red;">i,x,aux: inteiro</span><br />
inicio<br />
<br />
para i de 1 ate 5 faca<br />
leia(vet[i])<br />
fimpara<br />
<br />
para i de 1 ate 4 faca<br />
para x de i ate 5 faca<br />
se vet[x] < vet[i] entao<br />
aux <- br="br" vet="vet" x="x"> vet[x] <- br="br" i="i" vet="vet"> vet[i] <- aux="aux" br="br"> fimse<br /> fimpara<br />fimpara<br /><br />para i de 1 ate 5 faca<br /> escreval(vet[i])<br />fimpara<br /><br /><br />fimalgoritmo<!-----><!-----><!-----><!-----><!-----><!-----></-></-></-></div>
<div class="comment-content" id="bc_0_5MC">
<br /></div>
<div class="comment-content" id="bc_0_5MC">
Att,</div>
<div class="comment-content" id="bc_0_5MC">
<br /></div>
<div class="comment-content" id="bc_0_5MC">
Eduardo</div>
<br />
<br />
<br />
<br />
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<br />edu.classhttp://www.blogger.com/profile/07852022298031914548noreply@blogger.com0tag:blogger.com,1999:blog-1088386654901114113.post-31278351628068948352011-07-22T01:24:00.003-03:002011-07-22T01:31:44.912-03:00Ex. 09 -<br /><br />Elaborar um algoritmo que lê um conjunto de 30 valores e os coloca em 2 vetores conforme forem<br />pares ou ímpares. O tamanho do vetor é de 5 posições. Se algum vetor estiver cheio, escrevê-lo.<br />Terminada a leitura escrever o conteúdo dos dois vetores. Cada vetor pode ser preenchido tantas vezes quantas for necessário.<br /><br />Entendendo...<br /><br />O entendimento está nos comentários... muito sono *--*<br /><br />Uma possível Solução:<br /><br />algoritmo "Vetores"<br /><br /><span style="color: rgb(0, 153, 0);">// Autor : Eduardo V. de Souza</span><br /><span style="color: rgb(0, 153, 0);">// Data : 27/07/2011</span><br /><br /><span style="color: rgb(0, 153, 0);">//Declarando variáveis</span><br /><span style="color: rgb(0, 153, 0);">// dois vetores com cino posições cada</span><br /><span style="color: rgb(204, 0, 0);">var v:vetor[1..5]de inteiro</span><br /><span style="color: rgb(204, 0, 0);"> vr:vetor[1..5]de inteiro</span><br /><span style="color: rgb(0, 153, 0);">// uma variavel de leitura, uma variável para o laço, dois contadores</span><br /><span style="color: rgb(204, 0, 0);"> i,x,cont_p,cont_i:inteiro</span><br /><br />inicio<br /><br /><span style="color: rgb(0, 153, 0);">//como precisamos ler 30 valores um laça com 30 incrementos</span><br />para i de 1 ate 30 faca<br /> <span style="color: rgb(0, 153, 0);">//lendo a variavel x</span><br /> leia(x)<br /><span style="color: rgb(0, 153, 0);"> //Validando se o valor lido é par ou ímpar.</span><br /> se(x%2)=0 entao<br /> <span style="color: rgb(0, 153, 0);"> //se sim o contares de par é incrementado</span><br /> cont_p<-cont_p+1<br /><span style="color: rgb(0, 153, 0);">// e o vetor de numeros pares recebe na posição do contador o valor lido</span><br /> v[cont_p]<-x<br /><span style="color: rgb(0, 153, 0);">//se o contador chegar a 5 então o vetor é exibido.</span><br /> se cont_p=5 entao<br /> escreval("Vetor par")<br /> para i de 1 ate 5 faca<br /> escreval(v[i])<br /> fimpara<br /> escreval<br /><span style="color: rgb(0, 153, 0);">//zerando o contador para ser usado novamente</span><br /> cont_p<-0<br /> fimse<br /> senao<br /><span style="color: rgb(0, 153, 0);">//caso não seja par ele é impar XD</span><br /><span style="color: rgb(0, 153, 0);">//e o mesmo é feito para os números ímpares</span><br /> cont_i<-cont_i+1<br /> vr[cont_i]<-x<br /> se cont_i=5 entao<br /> escreval("Vertor Impar")<br /> para i de 1 ate 5 faca<br /> escreval(vr[i])<br /> fimpara<br /> cont_i<-0<br /> escreval<br /> fimse<br /> fimse<br />fimpara<br /><br /><span style="color: rgb(0, 153, 0);">//como o exercicio pede que é pra mostrar</span><br /><span style="color: rgb(0, 153, 0);">// o que restou de cada vetor e se restou</span><br /><span style="color: rgb(0, 153, 0);">// iniciamo um laço até o contador de cada vetor</span><br /><span style="color: rgb(0, 153, 0);">//e exibimos cada elemento que restou.</span><br />escreval("Vetor par")<br />para i de 1 ate cont_p faca<br /> escreval(v[i])<br />fimpara<br />escreval("vetor impar")<br />para i de 1 ate cont_i faca<br /> escreval(vr[i])<br />fimpara<br />fimalgoritmo<br /><br />Em Execução:<br /><br /><img src="data:image/png;base64,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" 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" 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" alt="" />edu.classhttp://www.blogger.com/profile/07852022298031914548noreply@blogger.com5tag:blogger.com,1999:blog-1088386654901114113.post-11619107217142771012011-06-28T23:17:00.003-03:002011-06-28T23:53:49.187-03:00Ex.08 - Números pares e ímpares de um vetorEscreva um algoritmo que leia e mostre um vetor de 20 elementos inteiros. a seguir, conte quantos<br />valores pares e ímpares existem no vetor.<br /><br />Entendendo...<br /><br />Vamos criar um vetor com 20 posições e ler cada uma delas, e depois mostrar na tela, sem novidades =)<br /><br />Teremos uma condição onde validaresmo os números pares e impares, pegaremos o resto da divisão do número lido, se for = zero será par senao impar.<br /><br />Muito Semelhante ao Ex. 05.<br /><br />Uma possível solução:<br /><br />algoritmo "Ex.08 - Números pares e ímpares de um vetor"<br /><br /><span style="color: rgb(0, 153, 0);">// Autor :Eduardo V. de Souza</span><br /><span style="color: rgb(0, 153, 0);">// Data : 28/06/2011</span><br /><br />var<br /><br /><span style="color: rgb(0, 153, 0);">//Declaração das variáveis</span><br /><span style="color: rgb(204, 0, 0);">vet:vetor[1..20] de inteiro</span><br /><span style="color: rgb(204, 0, 0);">i,cont_par,cont_imp:inteiro</span><br /><br />inicio<br /><br />//inicializando os contadores<br />cont_imp<-0<br />cont_par<-0<br /><br />escreval("Digite todos os números")<br /><br />para i de 1 ate 20 faca<br /> <span style="color: rgb(0, 153, 0);">//lendo cada elemento do vetor</span><br /> leia(vet[i])<br /> <span style="color: rgb(0, 153, 0);">//aqui todo o calculo, se nao existir resto na divisao = par</span><br /><span style="color: rgb(0, 153, 0);"> //senao impar</span><br /> se (vet[i]%2) = 0 entao<br /> <span style="color: rgb(0, 153, 0);">//se par, o contador recebe seu valor + 1</span><br /> cont_par<-cont_par+1<br /> senao<br /> <span style="color: rgb(0, 153, 0);">//se par, o contador recebe seu valor + 1</span><br /> cont_imp<-cont_imp+1<br /> fimse<br />fimpara<br /><br /><span style="color: rgb(0, 153, 0);">// eu sei que bagunça mas estou mostrando na tela todos os lidos</span><br />para i de 1 ate 20 faca<br /> escreval("Elemento nº ",i," do vetor = ",vet[i])<br />fimpara<br /><br /><span style="color: rgb(0, 153, 0);">// e finalmente mostrando o resultado</span><br />escreval("O total de números pares lidos foi ",cont_par)<br />escreval("O total de números ímpares lidos foi ",cont_imp)<br /><br />fimalgoritmo<br /><br />Em execução:<br /><br /><img src="data:image/png;base64,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" 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" alt="" />edu.classhttp://www.blogger.com/profile/07852022298031914548noreply@blogger.com22tag:blogger.com,1999:blog-1088386654901114113.post-72198764138968091322011-06-27T21:56:00.002-03:002011-06-28T00:40:11.878-03:00Ex. 07 - Multiplicação entre VetoresEscreva um algoritmo que leia dois vetores de 5 posições e faça a multiplicação dos elementos de mesmo índice, colocando o resultado em um terceiro vetor. Mostre o vetor resultante.<br /><br />Entendendo...<br /><br />Vamos criar 3 vetores, cada um com 5 posições, dois deles vamos preencher com valores inteiros.<br />O terceiro sera preenchido com a multiplicação dos outros dois. Como?<br /><br />vetor1 x vetor2? Sim isso mesmo!<br /><br />vetor1 na posição(1) x vetor2 na posição(1) preencherá o valor do vetor3 na posição(1) e assim por diante.<br /><br />Uma possível solução:<br /><br />algoritmo "Multiplicação entre vetores"<br /><br /><span style="color: rgb(0, 153, 0);">// Autor : Eduardo V. de Souza</span><br /><span style="color: rgb(0, 153, 0);">// Data : 27/06/2011</span><br /><br /><span style="color: rgb(204, 0, 0);">var vet_1:vetor[1..5]de inteiro</span><br /><span style="color: rgb(204, 0, 0);"> vet_2:vetor[1..5]de inteiro</span><br /><span style="color: rgb(204, 0, 0);"> vet_3:vetor[1..5]de inteiro</span><br /><span style="color: rgb(204, 0, 0);"> i:inteiro</span><br /><br />inicio<br /><br />aleatorio 1,10 <span style="color: rgb(0, 153, 0);">// ativa opção aleatoria do visualg</span><br /><br /><br /><span style="color: rgb(0, 153, 0);">// nesse bloco criamos e preenchemos com valores</span><br /><span style="color: rgb(0, 153, 0);">//randomicos o primeiro vetor</span><br />para i de 1 ate 5 faca<br /> escreval("Preenchendo o ",i, "º campo do primeiro vetor")<br /> leia(vet_1[i])<br />fimpara<br /><span style="color: rgb(0, 153, 0);">// nesse bloco criamos e preenchemos com valores</span><br /><span style="color: rgb(0, 153, 0);">//randomicos o segundo vetor</span><br />para i de 1 ate 5 faca<br /> escreval("Preenchendo o ",i, "º campo do segundo vetor")<br /> leia(vet_2[i])<br />fimpara<br /><br /><span style="color: rgb(0, 153, 0);">// nesse ultimo eu preencho o terceiro vetor com</span><br /><span style="color: rgb(0, 153, 0);">//a multiplicação do 1º com o 2º e logo em seguida</span><br /><span style="color: rgb(0, 153, 0);">//efetuo a leitura do mesmo mostrando na tela o resultado</span><br /><br />para i de 1 ate 5 faca<br /> escreval("mult do 1º com o 2º na pos",i, "º campo do 3º vetor")<br /> <span style="color: rgb(0, 153, 0);">//preenchendo o terceiro vetor</span><br /> vet_3[i]<- vet_1[i] * vet_2[i]<br /> escreval(vet_3[i])<br />fimpara<br />fimalgoritmo<br /><br />Em execução:<br /><br /><img src="data:image/png;base64,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" 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" alt="" />edu.classhttp://www.blogger.com/profile/07852022298031914548noreply@blogger.com3tag:blogger.com,1999:blog-1088386654901114113.post-12793920381986843972011-06-25T20:16:00.004-03:002011-06-25T20:37:15.231-03:00Ex. 06 - FatorialDado um número, calcule seu fatorial.<br /><br />Entendendo:<br /><br />Teremos que ler um número e encontrar seu fatorial, faremos isso entendendo um pouco mais sobre fatorial, ou seja a soma da multiplicação de um número (n) vezes, onde n é o número lido.<br /><br />Uma possível Solução:<br /><br />algoritmo "Fatorial"<br /><br /><span style="color: rgb(0, 153, 0);">//Autor: Eduardo V. Souza</span><br /><span style="color: rgb(0, 153, 0);">// Data : 25/06/2011</span><br /><br />var<br /><br />fat,x,i:inteiro<br /><span style="color: rgb(0, 153, 0);">// declarando as variáveis.</span><br /><span style="color: rgb(0, 153, 0);">// aqui temos 3 variaveis, uma para o indice do laço</span><br /><span style="color: rgb(0, 153, 0);">//outra para leitura do número e uma para calcular o fat.</span><br />inicio<br /><br />escreval("Digite um número")<br />leia(x)<br /><br /><span style="color: rgb(0, 153, 0);">// como vamos multiplicar precisamos inciar o valor de fat com 1</span><br />fat<-1<br /><br /><span style="color: rgb(0, 153, 0);">// nesse bloco é calculado o fatorial</span><br /><span style="color: rgb(0, 153, 0);">//para i que incia de 2 até o núemro lido (x)</span><br />para i de 2 ate x faca<br /><br /><span style="color: rgb(51, 204, 0);"> <span style="color: rgb(0, 153, 0);">//fat que tem o valor de 1 recebe a soma dele mesmo multiplicado</span></span><br /><span style="color: rgb(0, 153, 0);"> // por i que começa em 2 dentro do laço de repetição</span><br />fat<-fat*i<br />fimpara<br /><span style="color: rgb(51, 204, 0);"><span style="color: rgb(0, 153, 0);">//escreve o fatoria</span>l</span><br />escreval("fatorial =",fat)<br /><br />fimalgoritmo<br /><br />Em Execução:<br /><br /><img src="data:image/png;base64,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" alt="" />edu.classhttp://www.blogger.com/profile/07852022298031914548noreply@blogger.com1tag:blogger.com,1999:blog-1088386654901114113.post-69849294991501466572011-06-24T22:06:00.003-03:002011-06-25T10:36:50.515-03:00Ex. 05 - Número é par ou ímpar, e se é positivo ou negativoFaça um algoritmo que leia um nº inteiro e mostre uma mensagem indicando se este número é par ou ímpar, e se é positivo ou negativo.<br /><br />Entendendo...<br /><br />Aqui teremos que ler um número e verificar se ele e maior ou menor que zero, e depois verificar se ele e par ou impar, verificaremos se ele e par ou impar pegando o resto da divisão por 2 (mod), se o resultado for zero então ele é par, senao é impar.<br /><br />Uma possível Solução:<br /><br />algoritmo "Número é par ou ímpar, e se é positivo ou negativo"<br /><br /><span style="color: rgb(0, 153, 0);">// Autor : Eduardo V. de Souza</span><br /><span style="color: rgb(0, 153, 0);">// Data : 24/06/2011</span><br /><br />var<br /><br /><span style="color: rgb(204, 0, 0);">num: inteiro</span><br /><br />inicio<br /><br />escreval("Digite o número")<br /> leia(num)<span style="color: rgb(0, 153, 0);">//Lendo a variável</span><br /><br /><br /><span style="color: rgb(0, 153, 0);"> //verificando o resto da divisão por 2, se = 0 par senao impar</span><br />se (num % 2) = 0 entao<br /> escreval("O número é par")<br />senao<br /> escreval("O número é impar")<br />fimse<br /><br /><span style="color: rgb(0, 153, 0);">//verificando se é maior ou = 0</span><br /><span style="color: rgb(0, 153, 0);">// vou considerar aqui zero como numero positivo</span><br />se (num >= 0) entao<br /> escreval("O número é positivo")<br />senao<br /> escreval("O número é negativo")<br />fimse<br /><br />fimalgoritmo<br /><br />Em execução:<br /><br /><img src="data:image/png;base64,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" 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" 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" 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" alt="" />edu.classhttp://www.blogger.com/profile/07852022298031914548noreply@blogger.com27tag:blogger.com,1999:blog-1088386654901114113.post-57233907579416268492011-06-24T11:47:00.004-03:002011-06-24T13:06:16.702-03:00EX. 04 - Maior NúmeroEscreva um algoritmo que leia 3 números inteiros e mostre o maior deles.<br /><br />Entendendo...<br /><br />Teremos que ler uma variável e verificar se a mesma foi a maior digitada, para isso usarei condição SE e um Loop (para) e uma variável que ira armazenar o maior número digitado.<br />Isso é claro supondo que o usuário seja bomzinho e não digite nenhum número negativo ou zero.<br /><br />Uma Possível Solução.<br /><br />algoritmo "Maior Numero"<br /><br />// Autor : Eduardo V. de Souza<br />// Data : 24/06/2011<br /><br />var<br /><br />//declarando as variáveis, importante declarar a variavel do loop<br /><span style="color: rgb(255, 0, 0);">num,maior_num,i : inteiro</span><br /><br />inicio<br /><br /><span style="color: rgb(0, 153, 0);">//para comparar os numeros digitados com a varivel maior_num</span><br /><span style="color: rgb(0, 153, 0);">//eu iniciei ela com 0</span><br />maior_num <-0<br /><br />para i de 1 ate 3 faca <span style="color: rgb(0, 153, 0);">//como é preciso digitar 3 numeros, um laço até 3</span><br /> <span style="color: rgb(0, 153, 0);">//aqui uma concatenação para trazer o numero de incremento do laço</span><br /><span style="color: rgb(0, 153, 0);"> //para ficar mais interessante o código</span><br /> escreval("Digite o ",i,"º Número")<br /> leia(num)<br /><span style="color: rgb(0, 153, 0);">//validação principal, se a variavel maior_num que é = 0 for menor que</span><br /><span style="color: rgb(0, 153, 0);">//o numero digitado, ela recebera o valor desse numero.</span><br /> se maior_num < num entao<br /> maior_num<-num<br /> fimse<br />fimpara<br /><br /><span style="color: rgb(0, 153, 0);">//mostra na tela o valor do maior número</span><br />escreval("O maior número digitado foi ",maior_num)<br /><br />fimalgoritmo<br /><br />Em execução:<br /><br /><img src="data:image/png;base64,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" alt="" />edu.classhttp://www.blogger.com/profile/07852022298031914548noreply@blogger.com4tag:blogger.com,1999:blog-1088386654901114113.post-74051054627552107512011-06-23T03:45:00.003-03:002011-06-23T04:00:19.772-03:00EX. 03 - Calculo de Média<p face="Calibri" size="11.0pt" style="margin:0in;">Calcule a média aritmética das 3 notas de um aluno e mostre, além do valor da média, uma mensagem</p> <p face="Calibri" size="11pt" style="margin: 0in; ">de "Aprovado", caso a média seja igual ou superior a 6, ou a mensagem "reprovado", caso contrário.</p><p face="Calibri" size="11pt" style="margin: 0in; "><br /></p><p face="Calibri" size="11pt" style="margin: 0in; ">Entendendo...</p><p style="margin: 0in; font-family: Calibri; font-size: 11pt;"><br /></p><p style="margin: 0in; font-family: Calibri; font-size: 11pt;">Iremos ler três variáveis, equivalentes as 3 notas.</p><p style="margin: 0in; font-family: Calibri; font-size: 11pt;">Deveremos ter uma variável para guardar a média aritimética.</p><p style="margin: 0in; font-family: Calibri; font-size: 11pt;">Teremos que ter um bloco condicional (Se) para validar o valor da média, e exibir mensagens de acordo com o resultado.</p><p style="margin: 0in; font-family: Calibri; font-size: 11pt;"><br /></p><p style="margin: 0in; font-family: Calibri; font-size: 11pt;">Uma possível solução.</p><p style="margin: 0in; font-family: Calibri; font-size: 11pt;"><br /></p><p style="margin: 0in; font-family: Calibri; font-size: 11pt;">algoritmo "Claculo de Média"<br />// Autor : Eduardo V. Souza<br />// Data : 23/06/2011<br /><br />var<br />nota_1, nota_2, nota_3, media : real<br /><br />inicio<br /><span style="color: rgb(0, 153, 0);">// Inicia a Leitura das Notas</span><br />escreval ("Digite a 1ª Nota")<br /> leia (nota_1)<br />escreval ("Digite a 2ª Nota")<br /> leia (nota_2)<br />escreval ("Digite a 3ª Nota")<br /> leia (nota_3)<br /><br /><span style="color: rgb(0, 153, 0);">// aqui atribuimos para variável "media" a soma das</span><br /><span style="color: rgb(0, 153, 0);">// três notas lidas e é claro dividido por 3.</span><br />media <- (nota_1 + nota_2 +nota_3)/3<br /><br /><span style="color: rgb(0, 153, 0);">// primeiro bloco condicional</span><br /><span style="color: rgb(0, 153, 0);">//verifica se a média for maior ou igual 6, se sim</span><br /><span style="color: rgb(0, 153, 0);">// mostra mensagem de aprovado, senao reprovado</span><br /><span style="font-weight: bold;">se media >=6 entao</span><br /><span style="font-weight: bold;"> escreval ("Aluno Aprovado média = ", media)</span><br /><span style="font-weight: bold;">senao</span><br /><span style="font-weight: bold;"> escreval ("Aluno Reprovado média = ",media)</span><br /><span style="font-weight: bold;">fimse</span><br />fimalgoritmo</p><p style="margin: 0in; font-family: Calibri; font-size: 11pt;"><br /></p><p style="margin: 0in; font-family: Calibri; font-size: 11pt;">Em Execução.</p><p style="margin: 0in; font-family: Calibri; font-size: 11pt;"><br /></p><p style="margin: 0in; font-family: Calibri; font-size: 11pt;"><span style="font-weight: bold;">media >=6 entao</span></p><p style="margin: 0in; font-family: Calibri; font-size: 11pt;"><img 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" 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" alt="" /><br /><span style="font-weight: bold;"></span></p><p style="margin:0in;font-family:Calibri;font-size:11.0pt"><span style="font-weight: bold;"><br /></span></p> <p style="margin:0in;font-family:Calibri;font-size:11.0pt"> </p>edu.classhttp://www.blogger.com/profile/07852022298031914548noreply@blogger.com4tag:blogger.com,1999:blog-1088386654901114113.post-72964539817699244802011-06-23T03:36:00.002-03:002011-06-23T03:41:03.180-03:00Pedidos de exercíciosUsaremos este espaço para fazer os pedidos de exercicios.<br /><br />Os exercícios serão analisados, qualquer semelhança com qualquer outro exemplo ja resolvido, irei indicar o link com o exemplo.<br /><br />Att,<br /><br />Eduardo V. Souzaedu.classhttp://www.blogger.com/profile/07852022298031914548noreply@blogger.com4tag:blogger.com,1999:blog-1088386654901114113.post-87283209942153658522009-12-30T11:46:00.007-02:002011-06-23T03:43:16.402-03:00Ex. 02 - Calculo de idade em dias (02)Ex. 02:<br /><br /><span style="font-weight: bold;"></span>Faça um algoritmo que leia a idade de uma pessoa expressa em dias<br />e mostre-a expressa em anos, meses e dias<span style="font-weight: bold;">.<br /><br /></span><span style="font-weight: bold;">Entendendo...</span><br /><br />1° - Teremos apenas uma entrada de dados, idade em dias.<br />2° - Teremos que ter funcão que calcule todos os possíveis anos, meses e dias.<br />3° - Exibir na tela quantos anos, meses e dias são correspondentes ao número lido.<br /><br /><span style="font-size:78%;"><span style="font-size:130%;"><span style="font-weight: bold;">Uma Possível solução:</span></span></span><br /><br /><span style="font-size:85%;"><span style="font-weight: bold;">Código:</span></span><br /><br />algoritmo "calculo da idade em dias"<br /><span style="color: rgb(0, 153, 0);">// Autor : Eduardo V. Souza</span> <span style="color: rgb(0, 153, 0);"><br />// Data : 27/12/2009</span><br /><br />var<br />idade_anos, idade_meses, idade_dias, total_dias:inteiro<br />inicio<br /><br /><span style="color: rgb(0, 153, 0);">// Efetua a leitura da idade em dias</span><br />escreval("Digite a quantidade de dias:")<br />leia(total_dias)<br /><br /><span style="color: rgb(0, 153, 0);">// Efetua a conversao do total de dias para anos</span><br /><span style="color: rgb(0, 153, 0);">// dividindo o total lido por 365(ano)</span><br />idade_anos <- total_dias\365 <span style="color: rgb(0, 153, 0);">// atualiza a quantidade de dias lidos</span><br /><span style="color: rgb(0, 153, 0);">// menos a quantidade de anos convertidos</span><br /><span style="color: rgb(0, 153, 0);">// como? pegando o resto da divisão da quantidade</span><br /><span style="color: rgb(0, 153, 0);">// de dias lidos por 365</span><br />total_dias <- total_dias%365 <span style="color: rgb(0, 153, 0);"><br />// Efetua a conversao do total de dias para meses</span> <span style="color: rgb(0, 153, 0);"><br />// dividindo o total lido por 30(mes)</span><br />idade_meses <- total_dias\30 <span style="color: rgb(0, 153, 0);">// atualiza a quantidade de dias lidos</span><br /><span style="color: rgb(0, 153, 0);">// menos a quantidade de anos convertidos</span><br /><span style="color: rgb(0, 153, 0);">// como? pegando o resto da divisão da quantidade</span><br /><span style="color: rgb(0, 153, 0);">// de dias lidos por 30</span><br />total_dias <- total_dias%30 <span style="color: rgb(0, 153, 0);">//aqui simplesmente colocamos o total de dias atualizado</span><br /><span style="color: rgb(0, 153, 0);">// na variavel usada para salvar idade em dias ("idade_dias")</span><br />idade_dias <- total_dias <span style="color: rgb(0, 153, 0);">// aqui mostramos na tela o valores dos anos meses e dias</span><br />escreval("A idade é ",idade_anos)<br />escreval("A quantidade de meses é ", idade_meses)<br />escreval("A quantidade de dias é ", idade_dias )<br /><br />fimalgoritmo<br /><br /><span style="font-weight: bold;">Fluxo:</span><br /><br /><a onblur="try {parent.deselectBloggerImageGracefully();} catch(e) {}" href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjWzZF-Z4NR1zoB8eHBIatjuh9mQJsGNHICelRMQhpCgzfZNUZUdLbnzxSeG0qlvD8cn8-LbR-vGownzyRzzst7Ed-H-W9O5OmfBLF8lgASfVqW9W2WCB1Ur8MMuXi0Mb0uq2gOtD1PhnZN/s1600-h/ex+-+02.jpg"><img style="margin: 0pt 10px 10px 0pt; float: left; cursor: pointer; width: 328px; height: 400px;" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjWzZF-Z4NR1zoB8eHBIatjuh9mQJsGNHICelRMQhpCgzfZNUZUdLbnzxSeG0qlvD8cn8-LbR-vGownzyRzzst7Ed-H-W9O5OmfBLF8lgASfVqW9W2WCB1Ur8MMuXi0Mb0uq2gOtD1PhnZN/s400/ex+-+02.jpg" alt="" id="BLOGGER_PHOTO_ID_5421029466909030514" border="0" /></a><br /><br /><br /><br /><br /><br /><br /><br /><br /><br /><br /><br /><br /><br /><br /><br /><br /><br /><br /><br /><br /><br /><br /><span style="font-weight: bold;">Em execução:<br /><br /></span><a onblur="try {parent.deselectBloggerImageGracefully();} catch(e) {}" href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiiwmD_-gtoPth7UBk0kh-ruRspMwjunckrljnvmjNb6uRET7-Y9mLXMkOlPCr7hIHc7OYQ6QIAW2k3xCGzxOddzrLrNhu7Om4vrVJ071JTLG-zo8z7Uch67VBx3XJ98BA047ojMxxDWUIp/s1600-h/print_execu%C3%A7%C3%A3o_ex_02.jpg"><img style="cursor: pointer; width: 400px; height: 210px;" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiiwmD_-gtoPth7UBk0kh-ruRspMwjunckrljnvmjNb6uRET7-Y9mLXMkOlPCr7hIHc7OYQ6QIAW2k3xCGzxOddzrLrNhu7Om4vrVJ071JTLG-zo8z7Uch67VBx3XJ98BA047ojMxxDWUIp/s400/print_execu%C3%A7%C3%A3o_ex_02.jpg" alt="" id="BLOGGER_PHOTO_ID_5421030283508271922" border="0" /></a><br /><br />Fim.edu.classhttp://www.blogger.com/profile/07852022298031914548noreply@blogger.com4tag:blogger.com,1999:blog-1088386654901114113.post-90206592472329727042009-12-18T23:06:00.005-02:002011-06-23T03:43:36.604-03:00Ex. 01 - Calculo de idade em dias<span style="font-weight: bold;">Ex. 01:</span><br /><br />Faça um algoritmo que leia a idade de uma pessoa expressa em anos, meses e dias e mostre-a expressa apenas em dias.<br /><br /><span style="font-weight: bold;">Entendendo...</span><br /><br />1° - Teremos 3 entradas de dados, idade em anos, depois meses e por fim em dias.<br />2° - Teremos que ter funcão que converta anos em dia e meses em dias.<br />3° - Efetuar a soma de todas as conversões.<br />4° - Exibir na tela o resultado.<br /><br /><span style="font-size:130%;"><span style="font-weight: bold;">Uma Possível solução:</span></span><br /><br /><span style="font-weight: bold;">Código:</span><br /><br />algoritmo "calculo da idade em dias" <span style="color: rgb(0, 153, 0);">// Inicio do Programa</span><br /><span style="color: rgb(0, 153, 0);">// Autor : Eduardo V. Souza</span> <span style="color: rgb(0, 153, 0);"><br />// Data : 08/12/2009</span><br /><br />var<br /><span style="color: rgb(0, 153, 0);">// declaração de variáveis,<br />//uma para cada entrada de dados e uma para o total.</span><br /><span style="color: rgb(204, 0, 0);">idade_anos</span><span style="color: rgb(204, 0, 0);">: inteiro </span><span style="color: rgb(0, 153, 0);"></span><br /><span style="color: rgb(204, 0, 0);"> idade_meses</span><span style="color: rgb(204, 0, 0);">: inteiro </span><span style="color: rgb(0, 153, 0);"></span><br /><span style="color: rgb(204, 0, 0);"> idade_dias: inteiro </span><span style="color: rgb(0, 153, 0);"> </span><br /><span style="color: rgb(204, 0, 0);"> total_dias : inteiro </span><span style="color: rgb(0, 153, 0);"></span><br /><br />inicio<br /><br />escreval("Digite Sua Idade:")<br />leia(idade_anos) <span style="color: rgb(0, 153, 0);">// Efetua a leitura da idade</span><br />escreval("Digite quantos meses:")<br />leia(idade_meses) <span style="color: rgb(0, 153, 0);">// Efetua a leitura dos meses</span><br />escreval("Digite quantos dias:")<br />leia(idade_dias) <span style="color: rgb(0, 153, 0);"> // Efetua a leitura dos dias</span><br /><br /><span style="color: rgb(0, 153, 0);">// Converte anos em Dias</span><br />total_dias <- total_dias + (idade_anos*365) <span style="color: rgb(0, 153, 0);"><br />// Converte meses em dias</span><br />total_dias <- total_dias + (idade_meses*30) <span style="color: rgb(0, 153, 0);">// Converte anos em Dias</span><span style="color: rgb(0, 153, 0);"> na tela<br /></span>total_dias <- total_dias + idade_dias<span style="color: rgb(0, 153, 0);"></span><br /><span style="color: rgb(0, 153, 0);">// Visualizando</span><span style="color: rgb(0, 153, 0);"><br /></span>escreval("O total de dias é = ",total_dias)<br /><span style="color: rgb(0, 153, 0);"><br />// Finaliza o programa.</span><br />fimalgoritmo<br /><br /><span style="font-weight: bold;">Fluxo:<br /><br /></span><a onblur="try {parent.deselectBloggerImageGracefully();} catch(e) {}" href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgS_sZCSf4uKxCoGqw6-D794nAbN7JDrS1MlG0mYxkzL_0h36yZ12Jnwr_3LRyvhgpxoP14tveSaik1NLHFu0gT-vrH7J6idqZXW6Hb7Baxu3ASIbsWHLmWdtj-fizBy3KoveoffTTSinMU/s1600-h/ex+-+01+-+fluxo.jpg"><img style="cursor: pointer; width: 326px; height: 400px;" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgS_sZCSf4uKxCoGqw6-D794nAbN7JDrS1MlG0mYxkzL_0h36yZ12Jnwr_3LRyvhgpxoP14tveSaik1NLHFu0gT-vrH7J6idqZXW6Hb7Baxu3ASIbsWHLmWdtj-fizBy3KoveoffTTSinMU/s400/ex+-+01+-+fluxo.jpg" alt="" id="BLOGGER_PHOTO_ID_5416763742705013138" border="0" /></a><br /><br /><span style="font-weight: bold;">Em execução:</span><br /><br /><a onblur="try {parent.deselectBloggerImageGracefully();} catch(e) {}" href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhdoXZ2jW_G9v2J3i1lvbe7WlsgFOQlQpoTPuZX-wUMgOsv4DCkVN5sDiCuFSsbC3dIqGAAykj9zvbZ9gSfdOht8yZBi4coveLLsCtxy5hGCDrpnF_pizWNX3TbOg4uCFJ3gnIoMCCwjmri/s1600-h/print_execu%C3%A7%C3%A3o_ex_01.jpg"><img style="margin: 0pt 10px 10px 0pt; float: left; cursor: pointer; width: 400px; height: 203px;" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhdoXZ2jW_G9v2J3i1lvbe7WlsgFOQlQpoTPuZX-wUMgOsv4DCkVN5sDiCuFSsbC3dIqGAAykj9zvbZ9gSfdOht8yZBi4coveLLsCtxy5hGCDrpnF_pizWNX3TbOg4uCFJ3gnIoMCCwjmri/s400/print_execu%C3%A7%C3%A3o_ex_01.jpg" alt="" id="BLOGGER_PHOTO_ID_5416765142070951682" border="0" /></a><br /><div style="text-align: left;"><br /></div><br /><br /><br /><img src="file:///C:/Users/edu/AppData/Local/Temp/moz-screenshot-1.png" alt="" /><br /><br /><br /><span style="font-weight: bold;"><br /><br /></span><span><span style="font-weight: bold;"><br /><br /></span>Fim.</span><span style="font-weight: bold;"><br /></span><span style="color: rgb(0, 153, 0);"><br /><br /></span>edu.classhttp://www.blogger.com/profile/07852022298031914548noreply@blogger.com16tag:blogger.com,1999:blog-1088386654901114113.post-10012767117148611082009-12-16T23:49:00.002-02:002011-06-23T03:43:52.500-03:00<span style="font-weight: bold;font-size:130%;" >Download do Visualg:<br /><br /></span> Programa usado nas resoluções dos exercícios.<br /><br />Tela Inicial:<br /><br /><a onblur="try {parent.deselectBloggerImageGracefully();} catch(e) {}" href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgkGOV-MRid-xUIJd622gzgoWtwBdiSO08k2sTBYfseOEF3AhYF1lgHIjVBj5Vy2UWGV3jhblxtilbQBatDAl4Ppt3mP1arun_vM5m6Z41GF4Wv4BeAbzshgQmZ0i9crp0SB4n7Xp5Ltqvh/s1600-h/print_visualg_inicial.jpg"><img style="cursor: pointer; width: 400px; height: 300px;" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgkGOV-MRid-xUIJd622gzgoWtwBdiSO08k2sTBYfseOEF3AhYF1lgHIjVBj5Vy2UWGV3jhblxtilbQBatDAl4Ppt3mP1arun_vM5m6Z41GF4Wv4BeAbzshgQmZ0i9crp0SB4n7Xp5Ltqvh/s400/print_visualg_inicial.jpg" alt="" id="BLOGGER_PHOTO_ID_5416759731495731218" border="0" /></a><br /><br /><br />Tela de execução:<br /><br /><a onblur="try {parent.deselectBloggerImageGracefully();} catch(e) {}" href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEh82zO5jji9gJz5hOgLf_O20Dovtgmw5BELcJpp-CW1mwpBzs6T4Z92e8rnHDObc99r8lkJ8YTPRps6JXv7L24oiINySAY2JxX5DfisejNXtEIwpfMLJl4PcQRUeqjY7FWBln-XjjxAtHQN/s1600-h/print_visualg_execu%C3%A7%C3%A3o.jpg"><img style="cursor: pointer; width: 400px; height: 300px;" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEh82zO5jji9gJz5hOgLf_O20Dovtgmw5BELcJpp-CW1mwpBzs6T4Z92e8rnHDObc99r8lkJ8YTPRps6JXv7L24oiINySAY2JxX5DfisejNXtEIwpfMLJl4PcQRUeqjY7FWBln-XjjxAtHQN/s400/print_visualg_execu%C3%A7%C3%A3o.jpg" alt="" id="BLOGGER_PHOTO_ID_5416759952762878322" border="0" /></a><br /><br />Lembrando que não é objetivo ensinar a manipular a ferramenta, no entanto é muito facil de aprender.<br /><br /><span style="color: rgb(51, 51, 255);">http://www.baixaki.com.br/download/visualg.htm<br /><br /><br /></span>edu.classhttp://www.blogger.com/profile/07852022298031914548noreply@blogger.com1tag:blogger.com,1999:blog-1088386654901114113.post-35247115635196656722009-12-14T22:00:00.004-02:002010-01-08T21:19:57.436-02:00Introdução<span style="font-weight: bold;font-size:130%;" ><br /></span><span style="font-weight: bold;font-size:130%;" >Objetivo:</span><br />Resolver o maior número de exercicos possíveis, aprimorando o algoritmo deixando-o mais complexo.<br /><br /><span style="font-weight: bold;font-size:130%;" >Pré-Requisito:<br /></span>Ter noção de lógica de programação e estar familiarizado com tipos de dados e expressões.<br /><br /><span style="font-weight: bold;font-size:130%;" >Ferramentas:</span><br />Usaremos português estruturado compilável pelo VISUALG, e demosntrativos dos algoritmos via fluxograma para melhor entendimento.<br /><br />Link para download do programa;<br />http://www.baixaki.com.br/download/visualg.htm<span style="font-weight: bold;font-size:130%;" ><br /><br /></span><span style="font-weight: bold;"></span><br /><span style="font-weight: bold;font-size:130%;" ><br /><br />Breve introdução:</span><br /><span style="font-weight: bold;font-size:130%;" >O que é um algoritmo?</span><br /><br />Um algoritmo é uma seqüência de instruções finita e ordenada de forma lógica para a<br />resolução de uma determinada tarefa ou problema. São exemplos de algoritmos instruções de<br />montagem, receitas, manuais de uso, etc<br /><br />exemplo:<br /><br /><div style="text-align: left;"><a onblur="try {parent.deselectBloggerImageGracefully();} catch(e) {}" href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEihwnzIdFl7XZI2rb5l7x5t3B0bOibicCsCrIKOZHDIjkG2J_bBBk4qKfm1gbQCTl_AebiPLxZZMwV9Zw0RaOCAiq-HgWiGAZ4CsMmNbz8fTNcIWz1OXfPr1ad6Mm2iSQRFuc3XReFJyUVz/s1600-h/fluxo++-+1.png"><img style="cursor: pointer; width: 400px; height: 196px;" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEihwnzIdFl7XZI2rb5l7x5t3B0bOibicCsCrIKOZHDIjkG2J_bBBk4qKfm1gbQCTl_AebiPLxZZMwV9Zw0RaOCAiq-HgWiGAZ4CsMmNbz8fTNcIWz1OXfPr1ad6Mm2iSQRFuc3XReFJyUVz/s400/fluxo++-+1.png" alt="" id="BLOGGER_PHOTO_ID_5415230475243495426" border="0" /></a><br /><br />Exempço 2 :<br /><br /><span style="font-weight: bold;">Algoritmo para fritar um ovo</span>:<br /><br /><span>1.</span> Colocar um ovo na frigideira<br /><span>2</span>. Esperar o ovo ficar frito<br /><span>3</span>. Remover o ovo da frigideira<br /><br /><br />O algoritmo acima, no entanto, poderia ser mais detalhado e completo. Uma versão<br />mais aceitável seria:<br /><br /><br />1. Retirar um ovo da geladeira<br />2. Colocar a frigideira no fogo<br />3. Colocar óleo<br />4. Esperar até o óleo ficar quente<br />5. Quebrar o ovo separando a casca<br />6. Colocar o conteúdo do ovo na frigideira<br />7. Esperar um minuto<br />8. Retirar o ovo da frigideira<br />9. Apagar o fogo<br /><span style="font-weight: bold;font-size:130%;" ><br />Algoritmos Computacionais</span><br /><br />O computador, a princípio, não executa nada. Para que ele faça uma determinada tarefa -<br />calcular uma folha de pagamento, por exemplo -, é necessário que ele execute um programa.<br />Um programa é um conjunto de milhares de instruções que indicam ao computador, passo a<br />passo, o que ele tem que fazer. Logo, um programa nada mais é do que um algoritmo<br />computacional descrito em uma linguagem de programação. Uma linguagem de programação<br />contém os comandos que fazem o computador escrever algo na tela, realizar cálculos<br />aritméticos, receber uma entrada de dados via teclado, e milhares de outras coisas, mas estes<br />comandos precisam estar em uma ordem lógica.<br /><br /><span style="font-size:80%;"><span style="font-style: italic; color: rgb(51, 0, 153); font-weight: bold;font-size:78%;" >Material retirado do NAPRO :. NÚCLEO DE APOIO APRENDIZAGEM DE PROGRAMAÇÃO - da universidade Caxias do Sul</span><br /></span><br /></div><br /><br /><br /><img src="file:///C:/Users/edu/AppData/Local/Temp/moz-screenshot.png" alt="" />edu.classhttp://www.blogger.com/profile/07852022298031914548noreply@blogger.com1