Arturo Alessandri Palma . Arturo Alessandri Palma . . Era época donde la gra . n mayoría del país no . as muje . L . res no tenían derecho a voto. . n mayoría del país no era ciudadano y muy pocos participaban del proceso electoral. . 25 de junio de 1920, fue la última a Presidente de la República con el sistema de electores, en el Congreso Nacional . extendiéndose hasta finales de la década del 30 del siglo pasado, y en algunos países latinoamericanos, incluso hasta los años 40. . 1929 . a de convulsión política y económica no sólo en el país sino también a nivel mundial . entre diciembre de 1920 a noviembre de 1958, nuestro país tuvo un total de 29 Presidentes de la República o vicepresidentes, es decir, un Mandatario cada año y 3 meses como término medio. Fue una époc . Arturo Alessandri Palma . Arturo . Las mujeres no tenían derecho a voto. . En Chile, la elección Presidencial del 25 de junio de 1920, fue la última a Presidente de la República con el sistema de electores, en el Congreso Nacional. . época de convulsión política y económica no sólo en el país sino también a nivel mundial . epública o vicepresidentes . total de 29 Presidentes de la R . n 38 años . En 38 años

1920-1958: un período de la historia de Chile marcado por las crisis y las pugnas de poder | ELPINGUINO.COM

(116) Resaltar texto en la Web - YouTube

Color Balance – Ripple Training

The surprising part was that this description was said to be mathematically precise: An algorithm written in TLA+ could in principle be proven correct. In practice, it allowed you to create a realistic model of your problem and test it not just thoroughly . Still, most software, even in the safety-obsessed world of aviation, is made the old-fashioned way, with engineers writing their requirements in prose and programmers coding them up in a programming language like C . You’re free to tweak your blueprint without fear of introducing new bugs. Your code is, in FAA parlance, “correct by construction. . Much of the benefit of the model-based approach comes from being able to add requirements on the fly while still ensuring that existing ones are met; with every change, the computer can verify that your program still works. . As Bantégnie explains, the beauty of having a computer turn your requirements into code, rather than a human, is that you can be sure—in fact you can mathematically prove—that the generated code actually satisfies those requirements . Nearly all safety-critical code on the Airbus A380, including the system controlling the plane’s flight surfaces, was generated with ANSYS SCADE products. . ANSYS SCADE product family (for “safety-critical application development environment”) is used to generate code by companies in the aerospace and defense industries, in nuclear power plants, transit systems, heavy industry, and medical device . That was the promise of the model-based approach: Instead of writing normal programming code, you created a model of the system’s behavior—in this case, a model focused on how individual events should be handled, how to prioritize events, which event . The idea behind Esterel was that while traditional programming languages might be good for describing simple procedures that happened in a predetermined order—like a recipe—if you tried to use them in systems where lots of events could happen at nearl . Of course, for this approach to succeed, much of the work has to be done well before the project even begins. Someone first has to build a tool for developing models that are natural for people . So that’s what you spend your time thinking about. It’s a way of focusing less on the machine and more on the problem you’re trying to get it to solv . In the model-based approach, all you have is the rules . In traditional programming, your task is to take complex rules and translate them into code; most of your energy is spent doing the translating, rather than thinking about the rules themselves . Just by looking, you can see that the only way to get the elevator moving is to close the door, or that the only way to get the door open is to stop. . The diagrams make the system’s rules obvious . you’d represent this rule with a small diagram, as though drawing the logic out on a whiteboard, made of boxes that represent different states—like “door open,” “moving,” and “door closed”—and lines that define how you can get from one . Bantégnie’s company is one of the pioneers in the industrial use of model-based design, in which you no longer write code directly. Instead, you create a kind of flowchart that describes the rules your program should follow (the “model”), and the c . Like Victor, Bantégnie doesn’t think engineers should develop large systems by typing millions of lines of code into an IDE . In his mind, a software developer’s proper role was to create tools that removed the need for software developers . ictor suggested that the same trick could be pulled for nearly every problem where code was being written today. “I’m not sure that programming has to exist at all,” he told me. “Or at least software developers.” . visual representation of dynamic behavior . “In an environment that is truly responsive,” Resig wrote about the approach, “you can completely change the model of how a student learns ... [They] can now immediately see the result and intuit how underlying systems inherently work without ever f . With the right interface, it was almost as if you weren’t working with code at all; you were manipulating the game’s behavior directly. . The whole problem had been reduced to playing with different parameters, as if adjusting levels on a stereo receiver, until you got Mario to thread the needle . Game programmers were used to solving this kind of problem in two stages: First, you stared at your code—the code controlling how high Mario jumped, how fast he ran, how bouncy the turtle’s back was—and made some changes to it in your text editor, . The one that captured everyone’s imagination was, ironically enough, the one that on its face was the most trivial. It showed a split screen with a game that looked like Mario on one side and the code that controlled it on the other. As Victor changed t . proper job of programmers to ensure that someday they wouldn’t have to. . The document thereby came to feel like something real, something you could poke and prod at. Just by looking you could tell if you’d done something wrong. Control of a sophisticated system—the document’s layout and formatting engine—was made acce . There is an analogy to word processing. It used to be that all you could see in a program for writing documents was the text itself, and to change the layout or font or margins, you had to write special “control codes,” or commands that would tell the . That’s why software systems were so hard to think about, and so rife with bugs: The programmer, staring at a page of text, was abstracted from whatever it was they were actually making. . The principle was this: “Creators need an immediate connection to what they’re creating.” The problem with programming was that it violated the principle . When I want to make a thing, especially when I want to create something in software, there’s this initial layer of disgust that I have to push through, where I’m not manipulating the thing that I want to make, I’m writing a bunch of text into a text . trying to keep track of every intermediate calculatio . hinking the way a computer would . So the students who did well—in fact the only ones who survived at all—were those who could step through that text one instruction at a time in their head . Why was it so hard to learn to program? The essential problem seemed to be that code was so abstract . Programmers were like chess players trying to play with a blindfold on—so much of their mental energy is spent just trying to picture where the pieces are that there’s hardly any left over to think about the game itself . from it was that basically people are playing computer inside their head.” . . . Visual Studio is one of the single largest pieces of software in the world,” he said. “It’s over 55 million lines of code. And one of the things that I found out in this study is more than 98 percent of it is completely irrelevant . Since the 1980s, the way programmers work and the tools they use have changed remarkably little . The problem is that programmers are having a hard time keeping up with their own creations . You have software watching the software . But these systems have become so complicated that hardly anyone can keep them straight in their head. “There’s 100 million lines of code in cars now . The reason is that they’re too wrapped up in getting their code to work . The problem is that software engineers don’t understand the problem they’re trying to solve, and don’t care to . the fact that the programmer didn’t work on a problem directly, but rather spent their days writing out instructions for a machine . alienated the programmer was from the actual problems they were trying to solv . What made programming so difficult was that it required you to think like a computer . Software has enabled us to make the most intricate machines that have ever existed. And yet we have hardly noticed, because all of that complexity is packed into tiny silicon chips as millions and millions of lines of code. But just because we can’t see . Technological progress used to change the way the world looked—you could watch the roads getting paved; you could see the skylines rise. Today you can hardly tell when something is remade, because so often it is remade by code.
Page: 3973 3972 3971 3970 3969 3968 previous