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Flashcard 1428268125452

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#algebra-baldor
Question
Los signos de agrupación son: el paréntesis ordinario ( ) el parénte sis angular o corchete [ ], [...] y la barra o vínculo.

Estos signos indican que la operación colocada entre ellos debe efectuarse primero.
Answer
las llaves { }

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Los signos de agrupación son: el paréntesis ordinario ( ) el parénte sis angular o corchete [ ], las llaves { } y la barra o vínculo. Estos signos indican que la operación colocada entre ellos debe efectuarse primero. Así, (a + b)c indica que el resultado de la suma de a y b debe multi

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Flashcard 1430468037900

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#cfa #cfa-level-1 #economics #microeconomics #reading-13-demand-and-supply-analysis-introduction #study-session-4
Question
In effect, any impediment in the dissemination of information about buyers’ and sellers’ willingness to exchange goods can cause an [...].
Answer
imbalance in demand and supply

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In effect, any impediment in the dissemination of information about buyers’ and sellers’ willingness to exchange goods can cause an imbalance in demand and supply. So anything that improves that information flow can add value. In that sense, advertising can add value to the extent that it informs potential buyers of the availability of goods and

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3.13. Market Interference: The Negative Impact on Total Surplus
provide value in the transaction, and for that value they are able to charge a brokerage fee. Although the brokerage fee could certainly be viewed as a transactions cost, it is really a price charged for the service of reducing search costs. <span>In effect, any impediment in the dissemination of information about buyers’ and sellers’ willingness to exchange goods can cause an imbalance in demand and supply. So anything that improves that information flow can add value. In that sense, advertising can add value to the extent that it informs potential buyers of the availability of goods and services. <span><body><html>







Flashcard 1438154362124

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#analyst-notes #cfa-level-1 #corporate-finance #introduction #reading-35-capital-budgeting
Question
The post-audit is a [...] of [...] decisions.

Answer
follow-up of capital budgeting decisions

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osals (forecasting cash flows, evaluating profitability, etc.). Planning the capital budget. How does the project fit within the company's overall strategies? What's the timeline and priority? Monitoring and post-auditing. The post-audit is a <span>follow-up of capital budgeting decisions. It is a key element of capital budgeting. By comparing actual results with predicted results and then determining why differences occurred, decision-makers can: Im

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Subject 1. Capital Budgeting: Introduction
include in the capital budget. "Capital" refers to long-term assets. The "budget" is a plan which details projected cash inflows and outflows during a future period. <span>The typical steps in the capital budgeting process: Generating good investment ideas to consider. Analyzing individual proposals (forecasting cash flows, evaluating profitability, etc.). Planning the capital budget. How does the project fit within the company's overall strategies? What's the timeline and priority? Monitoring and post-auditing. The post-audit is a follow-up of capital budgeting decisions. It is a key element of capital budgeting. By comparing actual results with predicted results and then determining why differences occurred, decision-makers can: Improve forecasts (based on which good capital budgeting decisions can be made). Otherwise, you will have the GIGO (garbage in, garbage out) problem. Improve operations, thus making capital decisions well-implemented. Project classifications: Replacement projects. There are two types of replacement d







Flashcard 1438438788364

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#analyst-notes #cfa-level-1 #corporate-finance #reading-35-capital-budgeting #study-session-10
Question
The post-audit process is difficult because forecasts may be "wrong" due to circumstances that could not [...]

Answer
have been anticipated at the time they were made;

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Independent versus mutually exclusive projects. Mutually exclusive projects are investments that compete in some way for a company's resources - a firm can select one or another but not both. Independent projects, on the other hand, do not compete for the firm's resources. A company can select one or the other or both, so long

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Subject 2. Basic Principles of Capital Budgeting
In a non-conventional cash flow pattern, the initial outflow can be followed by inflows and/or outflows. <span>Some project interactions: Independent versus mutually exclusive projects. Mutually exclusive projects are investments that compete in some way for a company's resources - a firm can select one or another but not both. Independent projects, on the other hand, do not compete for the firm's resources. A company can select one or the other or both, so long as minimum profitability thresholds are met. Project sequencing. How does one sequence multiple projects over time, since investing in project B may depend on the result of investing in project A? Unlimited funds versus capital rationing. Capital rationing occurs when management places a constraint on the size of the firm's capital budget during a particular period. In such situations, capital is scarce and should be allocated to the projects most likely to maximize the firm's aggregate NPV. The firm's capital budget and cost of capital must be determined simultaneously to best allocate the firm's capital. On the other hand, a firm can raise the funds it wants for all profitable projects simply by paying the required rate of return. Learning Outcome Statements b. describe the basic principles of capital budgeting; c. explain how the evaluat







Flashcard 1443169438988

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#financial #vocabulary
Question
net out.
Answer
To be or produce a particular amount of money after tax and other costs have been paid:

The facility showed a gross loss of $3m, which, when set against investors' deposits of £1.5m, netted out at $1.5m.

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Flashcard 1633271549196

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#reading-7-discounted-cashflows-applications
Question

Money market yield formula

rmm = [...]

Answer
\(r_{mm} = {360*BDY \over 360-(t*BDY)}\)

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Subject 4. Different Yield Measures of a U.S. Treasury Bill
se price, not face value. It is not an annualized yield. The effective annual yield is the annualized HPY on the basis of a 365-day year. It incorporates the effect of compounding interest. <span>Money market yield (also known as CD equivalent yield) is the annualized HPY on the basis of a 360-day year using simple interest. Example An investor buys a $1,000 face-value T-bill due in 60 days at a price of $990. Bank discount yield: (1000 - 990







Flashcard 1644576247052

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#reading-8-statistical-concepts-and-market-returns
Question

Sample Skewness Formula.

\(Sk = {n \over (n-1)(n-2)}\) [...]

Answer
\( {\Sigma(Xi-\bar{X})^3 \over s^3}\)

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Flashcard 1690037521676

Question
Early collections of invective lampoon poetry are usually not called kitab al-hijāʾ but, for instance...
Answer
kitab al-mathalib ("occasions for blame")

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#2017 #cgo #computer-science
OPPROX operates in four conceptual steps. First, OPPROX identifies different computation phases. Second, OPPROX models the speedup and error generated due to different levels of approximation in the individual ABs and in different com- putation phases using representative inputs. Third, OPPROX compares the benefits of various approximation settings in dif- ferent phases and splits the overall error budget e b into phase- specific error budgets in proportion to the predicted benefits. Finally, OPPROX formulates phase-specific trade-off space exploration as a numerical optimization problem and finds the most profitable approximation settings for each phase using the phase-specific error budgets as the constraints. We show that for many applications, both the approxima- tion level and the phase in which approximation is performed, have significant contributions towards the final error. Hence, phase-specific optimal approximation settings can provide good speedup (which we express here using the number of instructions executed) even under constrained error budget. When compared to an oracle but phase-agnostic version from prior works[ 43 , 44 ], our approach on average provides 42% speedup compared to 37% from the oracle version for an error budget of 20% and for a small error budget of 5% provides on average 14% speedup compared to only 2% achieved by the phase-agnostic oracle version.
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#science_informatics_compilers_engineering-a-compiler_chapter1
Compiler a computer program that translates other computer programs
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#science_informatics_compilers_engineering-a-compiler_chapter1
programming language—a formal language designed for expressing com- putation.
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#science_informatics_compilers_engineering-a-compiler_chapter1
Instruction set The set of operations supported by a processor; the overall design of an instruction set is often called an instruction set architecture or ISA
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#science_informatics_compilers_engineering-a-compiler_chapter1
Virtual machine A virtual machine is a simulator for some processor. It is an interpreter for that machine’s instruction set.
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#science_informatics_compilers_engineering-a-compiler_chapter1
Compilers that tar- get programming languages rather than the instruction set of a computer are often called source-to-source translators
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#science_informatics_compilers_engineering-a-compiler_chapter1
compiler that executes at runtime, sometimes called a just-in-time compiler, or jit, that translates heavily used bytecode sequences into native code for the underlying computer.
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#science_informatics_compilers_engineering-a-compiler_chapter1
The first principle is inviolable: The compiler must preserve the meaning of the program being compiled
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#science_informatics_compilers_engineering-a-compiler_chapter1
The second principle that a compiler must observe is practical: The compiler must improve the input program in some discernible way
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#has-images #science_informatics_compilers_engineering-a-compiler_chapter1
Some text here
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#science_informatics_compilers_engineering-a-compiler_chapter1
IR A compiler uses some set of data structures to represent the code that it processes. That form is called an intermediate representation, or IR.
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Retargeting The task of changing the compiler to generate code for a new processor is often called retargeting the compiler.
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#science_informatics_compilers_engineering-a-compiler_chapter1
Optimizer The middle section of a compiler, called an optimizer, analyzes and transforms the IR to improve it
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#has-images #science_informatics_compilers_engineering-a-compiler_chapter1
This leads to the following compiler structure, termed a three-phase compiler.
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#science_informatics_compilers_engineering-a-compiler_chapter1
The optimizer is an ir-to-ir transformer that tries to improve the ir program in some way.
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#has-images #science_informatics_compilers_engineering-a-compiler_chapter1
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#science_informatics_compilers_engineering-a-compiler_chapter1
Scanner the compiler pass that converts a string of characters into a stream of words
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#science_informatics_compilers_engineering-a-compiler
By inspection, we can discover the following derivation for our example sentence:
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#science_informatics_compilers_engineering-a-compiler_chapter1
The derivation starts with the syntactic variable Sentence.
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#science_informatics_compilers_engineering-a-compiler_chapter1
Parser the compiler pass that determines if the input stream is a sentence in the source language
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Flashcard 1710316981516

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#reading-1-ethics-and-trust-in-the-investment-profession
Question

Beliefs are assumptions or thoughts we [...]

Answer
hold to be true.

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Flashcard 1710318816524

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#reading-1-ethics-and-trust-in-the-investment-profession
Question

[...] are assumptions or thoughts we hold to be true.

Answer
Beliefs

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Flashcard 1710320651532

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#reading-1-ethics-and-trust-in-the-investment-profession
Question

Our beliefs form our [...]

Answer
values

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Flashcard 1710323272972

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#reading-1-ethics-and-trust-in-the-investment-profession
Question

Values are [...]

Answer
things we consider to have worth.

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Flashcard 1710325107980

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#reading-1-ethics-and-trust-in-the-investment-profession
Question

Ethos means [...]

Answer
character

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Moral vs Ethics
#reading-1-ethics-and-trust-in-the-investment-profession
Moral principles or ethical principles are beliefs regarding what is good, acceptable, or obligatory behavior and what is bad, unacceptable, or forbidden behavior.
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Moral vs Ethics
#reading-1-ethics-and-trust-in-the-investment-profession
Ethical principles may refer to beliefs regarding behavior that an individual expects of himself, as well as shared beliefs regarding behavior expected by a community or societal group.
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Flashcard 1710335593740

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#six-tips-for-working-with-the-brain
Question
[...] are the key to moving conceptual learning into memory.
Answer
Retrievals

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Although retrievals are the key to moving conceptual learning into memory, repetition is the key for habit design.

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as links to TED Talks, articles, and assignments to further hone their skills. This blended approach allows me to create three retrievals spaced with sleep, and it also starts to build the habits of the behaviors I am trying to cultivate. <span>Tip #6: Be a habit designer Ultimately, the goal of most learning activities is behavior change. No matter the topic, we are trying to elicit new and better behaviors in the learner. Charles Duhigg's The Power of Habit changed the way I see my work. He shares the science of how the basal ganglia in the brain builds habit loops that include a cue or trigger, the routine of behavior, and the reward for completing that routine. Over time, habits become well-grooved neural pathways that almost happen on autopilot, for example how you currently log in to your computer or how you get to work. When we are trying to create behavior change, we need to think about the habits that are currently in place and how to design new, better habits that will be more compelling than the comfort of the current ones. I now think of myself as a habit designer. All of my learning design starts with identifying the habit loop I hope to instill, and I work backward from there. Although retrievals are the key to moving conceptual learning into memory, repetition is the key for habit design. The more we fire neurons together, the stronger that neural pathway becomes, to the point that researchers can measure the neurons growing thicker. As talent development professionals, we are in the business of cultivating potential. Your organization as a whole—as well as every person in it—have unrealized ability, and your job is to cultivate that potential through the learning experiences you create. Work with the natural processes of the brain and nervous system to maximize the impact of your great work. Brain Science Resources Brain science is a burgeoning field and, within it, you will find a wide range of defined specialties from neurology to psychology to biology. This is a lis







#science_informatics_compilers_engineering-a-compiler_chapter1
Data-flow analysis a form of compile-time reasoning about the runtime flow of values
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#science_informatics_compilers_engineering-a-compiler_chapter1
Virtual register a symbolic register name that the compiler uses to indicate that a value can be stored in a register
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History of programming languages - Wikipedia
ained it a reputation of being difficult. Niklaus Wirth actually walked out of the design committee to create the simpler Pascal language. [imagelink] Fortran Some notable languages that were developed in this period include: <span>1951 – Regional Assembly Language 1952 – Autocode 1954 – IPL (forerunner to LISP) 1955 – FLOW-MATIC (led to COBOL) 1957 – FORTRAN (First compiler) 1957 – COMTRAN (precursor to COBOL) 1958 – LISP 1958 – ALGOL 58 1959 – FACT (forerunner to COBOL) 1959 – COBOL 1959 – RPG 1962 – APL 1962 – Simula 1962 – SNOBOL 1963 – CPL (forerunner to C) 1964 – Speakeasy (computational environment) 1964 – BASIC 1964 – PL/I 1966 – JOSS 1967 – BCPL (forerunner to C) Establishing fundamental paradigms[edit] [imagelink] Smalltalk [imagelink] Scheme The period from the late 1960s to the late 1970s brought a major flowering




Before computer programming languages were made, paper tapes and punch cards which held complicated weaving patterns for the loom Tabulating Machine Company Looms by Jacquard in 1710
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History of programming languages - Wikipedia
nguages are a fairly new field, since the first high-level languages were written in the 1950s, around the time computers were invented. The earliest computers were programmed in binary so the set of instructions was just a series of 0 and 1. <span>Before computer programming languages were made, paper tapes and punch cards which held complicated weaving patterns for the loom Tabulating Machine Company Looms by Jacquard in 1710. A century later, Charles Babbage started building a computing and the analytical Machine. In the 20th century, Herman Hollerith founded the Tabulating Machine. His machine tabulators w




Charles Babbage started building a computing and the analytical Machine
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History of programming languages - Wikipedia
nstructions was just a series of 0 and 1. Before computer programming languages were made, paper tapes and punch cards which held complicated weaving patterns for the loom Tabulating Machine Company Looms by Jacquard in 1710. A century later, <span>Charles Babbage started building a computing and the analytical Machine. In the 20th century, Herman Hollerith founded the Tabulating Machine. His machine tabulators were used to speed up the counting and sorting of punch cards. In the early 1940s J. Prespe




In the 20th century, Herman Hollerith founded the Tabulating Machine. His machine tabulators were used to speed up the counting and sorting of punch cards.
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History of programming languages - Wikipedia
guages were made, paper tapes and punch cards which held complicated weaving patterns for the loom Tabulating Machine Company Looms by Jacquard in 1710. A century later, Charles Babbage started building a computing and the analytical Machine. <span>In the 20th century, Herman Hollerith founded the Tabulating Machine. His machine tabulators were used to speed up the counting and sorting of punch cards. In the early 1940s J. Presper Eckert and John W. Mauchly started building the ENIAC (Electronic Numerical Integrator and Calculator), which was completed by 1946. The very first high-




In the early 1940s J. Presper Eckert and John W. Mauchly started building the ENIAC (Electronic Numerical Integrator and Calculator), which was completed by 1946.
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History of programming languages - Wikipedia
entury later, Charles Babbage started building a computing and the analytical Machine. In the 20th century, Herman Hollerith founded the Tabulating Machine. His machine tabulators were used to speed up the counting and sorting of punch cards. <span>In the early 1940s J. Presper Eckert and John W. Mauchly started building the ENIAC (Electronic Numerical Integrator and Calculator), which was completed by 1946. The very first high-level programming language was FORTRAN, which stands for FORmula TRANslation. It was developed in 1956 (first manual appeared in 1956, but first developed in 1954)




FORTRAN, which stands for FORmula TRANslation
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History of programming languages - Wikipedia
nd sorting of punch cards. In the early 1940s J. Presper Eckert and John W. Mauchly started building the ENIAC (Electronic Numerical Integrator and Calculator), which was completed by 1946. The very first high-level programming language was <span>FORTRAN, which stands for FORmula TRANslation. It was developed in 1956 (first manual appeared in 1956, but first developed in 1954) by John Backus, a worker at IBM. FORTRAN's goal was to ease the pain of writing in assembly langua




During a nine-month period in 1842–1843, Ada Lovelace translated the memoir of Italian mathematician Luigi Menabrea about Charles Babbage's newest proposed machine, the analytical engine. With the article she appended a set of notes which specified in complete detail a method for calculating Bernoulli numbers with the engine, recognized by some historians as the world's first computer program.[1]
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History of programming languages - Wikipedia
not as easy to use as it should be. The development of the fast string processing makes FORTRAN more of a general-purpose language than it used to be, but it is still described as a mathematical or scientific language. Early history[edit] <span>During a nine-month period in 1842–1843, Ada Lovelace translated the memoir of Italian mathematician Luigi Menabrea about Charles Babbage's newest proposed machine, the analytical engine. With the article she appended a set of notes which specified in complete detail a method for calculating Bernoulli numbers with the engine, recognized by some historians as the world's first computer program. [1] Herman Hollerith realized that he could encode information on punch cards when he observed that train conductors encode the appearance of the ticket holders on the train tickets using




Herman Hollerith realized that he could encode information on punch cards when he observed that train conductors encode the appearance of the ticket holders on the train tickets using the position of punched holes on the tickets[2]. Hollerith then encoded the 1890 American census data on punch cards.
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History of programming languages - Wikipedia
ine, the analytical engine. With the article she appended a set of notes which specified in complete detail a method for calculating Bernoulli numbers with the engine, recognized by some historians as the world's first computer program. [1] <span>Herman Hollerith realized that he could encode information on punch cards when he observed that train conductors encode the appearance of the ticket holders on the train tickets using the position of punched holes on the tickets [2] . Hollerith then encoded the 1890 American census data on punch cards. The first computer codes were specialized for their applications. In the first decades of the 20th century, numerical calculations were based on decimal numbers. Eventually it was rea




Jacquard Looms and Charles Babbage's Difference Engine both had simple, extremely limited languages for describing the actions that these machines should perform. One can even regard the punch holes on a player piano scroll as a limited domain-specific language, albeit not designed for human consumption.
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History of programming languages - Wikipedia
um. Thus the programs were more hardware-dependent. To some people, what was the first modern programming language depends on how much power and human-readability is required before the status of "programming language" is granted. <span>Jacquard Looms and Charles Babbage's Difference Engine both had simple, extremely limited languages for describing the actions that these machines should perform. One can even regard the punch holes on a player piano scroll as a limited domain-specific language, albeit not designed for human consumption. First programming languages[edit] In the 1940s, the first recognizably modern electrically powered computers were created. The limited speed and memory capacity forced programmers t




An early high-level programming language to be designed for a computer was Plankalkül, developed by the Germans for Z1 by Konrad Zuse between 1943 and 1945. However, it was not implemented until 1998 and 2000.[3]
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History of programming languages - Wikipedia
language programs. It was eventually realized that programming in assembly language required a great deal of intellectual effort. The first programming languages designed to communicate instructions to a computer were written in the 1950s. <span>An early high-level programming language to be designed for a computer was Plankalkül, developed by the Germans for Z1 by Konrad Zuse between 1943 and 1945. However, it was not implemented until 1998 and 2000. [3] John Mauchly's Short Code, proposed in 1949, was one of the first high-level languages ever developed for an electronic computer. [4] Unlike machine code, Short Code statements repre




John Mauchly's Short Code, proposed in 1949, was one of the first high-level languages ever developed for an electronic computer.[4] Unlike machine code, Short Code statements represented mathematical expressions in understandable form. However, the program had to be translated into machine code every time it ran, making the process much slower than running the equivalent machine code.
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History of programming languages - Wikipedia
were written in the 1950s. An early high-level programming language to be designed for a computer was Plankalkül, developed by the Germans for Z1 by Konrad Zuse between 1943 and 1945. However, it was not implemented until 1998 and 2000. [3] <span>John Mauchly's Short Code, proposed in 1949, was one of the first high-level languages ever developed for an electronic computer. [4] Unlike machine code, Short Code statements represented mathematical expressions in understandable form. However, the program had to be translated into machine code every time it ran, making the process much slower than running the equivalent machine code. At the University of Manchester, Alick Glennie developed Autocode in the early 1950s. A programming language, it used a compiler to automatically convert the language into machine cod




At the University of Manchester, Alick Glennie developed Autocode in the early 1950s. A programming language, it used a compiler to automatically convert the language into machine code. The first code and compiler was developed in 1952 for the Mark 1 computer at the University of Manchester and is considered to be the first compiled high-level programming language.[5][6]
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code, Short Code statements represented mathematical expressions in understandable form. However, the program had to be translated into machine code every time it ran, making the process much slower than running the equivalent machine code. <span>At the University of Manchester, Alick Glennie developed Autocode in the early 1950s. A programming language, it used a compiler to automatically convert the language into machine code. The first code and compiler was developed in 1952 for the Mark 1 computer at the University of Manchester and is considered to be the first compiled high-level programming language. [5] [6] The second autocode was developed for the Mark 1 by R. A. Brooker in 1954 and was called the "Mark 1 Autocode". Brooker also developed an autocode for the Ferranti Mercury i




The second autocode was developed for the Mark 1 by R. A. Brooker in 1954 and was called the "Mark 1 Autocode". Brooker also developed an autocode for the Ferranti Mercury in the 1950s in conjunction with the University of Manchester. The version for the EDSAC 2 was devised by D. F. Hartley of University of Cambridge Mathematical Laboratory in 1961. Known as EDSAC 2 Autocode, it was a straight development from Mercury Autocode adapted for local circumstances, and was noted for its object code optimisation and source-language diagnostics which were advanced for the time. A contemporary but separate thread of development, Atlas Autocode was developed for the University of Manchester Atlas 1 machine.
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omatically convert the language into machine code. The first code and compiler was developed in 1952 for the Mark 1 computer at the University of Manchester and is considered to be the first compiled high-level programming language. [5] [6] <span>The second autocode was developed for the Mark 1 by R. A. Brooker in 1954 and was called the "Mark 1 Autocode". Brooker also developed an autocode for the Ferranti Mercury in the 1950s in conjunction with the University of Manchester. The version for the EDSAC 2 was devised by D. F. Hartley of University of Cambridge Mathematical Laboratory in 1961. Known as EDSAC 2 Autocode, it was a straight development from Mercury Autocode adapted for local circumstances, and was noted for its object code optimisation and source-language diagnostics which were advanced for the time. A contemporary but separate thread of development, Atlas Autocode was developed for the University of Manchester Atlas 1 machine. In 1954, language FORTRAN was invented at IBM by John Backus; it was the first widely used high level general purpose programming language to have a functional implementation, as oppo




Another early programming language was devised by Grace Hopper in the US, called FLOW-MATIC. It was developed for the UNIVAC I at Remington Rand during the period from 1955 until 1959. Hopper found that business data processing customers were uncomfortable with mathematical notation, and in early 1955, she and her team wrote a specification for an English programming language and implemented a prototype.[11] The FLOW-MATIC compiler became publicly available in early 1958 and was substantially complete in 1959.[12] Flow-Matic was a major influence in the design of COBOL, since only it and its direct descendent AIMACO were in actual use at the time.[13]
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to have a functional implementation, as opposed to just a design on paper. [7] [8] It is still a popular language for high-performance computing [9] and is used for programs that benchmark and rank the world's fastest supercomputers. [10] <span>Another early programming language was devised by Grace Hopper in the US, called FLOW-MATIC. It was developed for the UNIVAC I at Remington Rand during the period from 1955 until 1959. Hopper found that business data processing customers were uncomfortable with mathematical notation, and in early 1955, she and her team wrote a specification for an English programming language and implemented a prototype. [11] The FLOW-MATIC compiler became publicly available in early 1958 and was substantially complete in 1959. [12] Flow-Matic was a major influence in the design of COBOL, since only it and its direct descendent AIMACO were in actual use at the time. [13] Other languages still in use today include LISP (1958), invented by John McCarthy and COBOL (1959), created by the Short Range Committee. Another milestone in the late 1950s was the p




Other languages still in use today include LISP (1958), invented by John McCarthy and COBOL (1959), created by the Short Range Committee. Another milestone in the late 1950s was the publication, by a committee of American and European computer scientists, of "a new language for algorithms"; the ALGOL 60 Report (the "ALGOrithmic Language").
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ATIC compiler became publicly available in early 1958 and was substantially complete in 1959. [12] Flow-Matic was a major influence in the design of COBOL, since only it and its direct descendent AIMACO were in actual use at the time. [13] <span>Other languages still in use today include LISP (1958), invented by John McCarthy and COBOL (1959), created by the Short Range Committee. Another milestone in the late 1950s was the publication, by a committee of American and European computer scientists, of "a new language for algorithms"; the ALGOL 60 Report (the "ALGOrithmic Language"). This report consolidated many ideas circulating at the time and featured three key language innovations: nested block structure: code sequences and associated declarations could be gr




The period from the late 1960s to the late 1970s brought a major flowering of programming languages. Most of the major language paradigms now in use were invented in this period:

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er to C) 1964 – Speakeasy (computational environment) 1964 – BASIC 1964 – PL/I 1966 – JOSS 1967 – BCPL (forerunner to C) Establishing fundamental paradigms[edit] [imagelink] Smalltalk [imagelink] Scheme <span>The period from the late 1960s to the late 1970s brought a major flowering of programming languages. Most of the major language paradigms now in use were invented in this period: Speakeasy (computational environment), developed in 1964 at Argonne National Laboratory (ANL) by Stanley Cohen, is an OOPS (object-oriented programming, much like the later MATLAB, IDL (programming language) and Mathematica) numerical package. Speakeasy has a clear Fortran foundation syntax. It first addressed efficient physics computation internally at ANL, was modified for research use (as "Modeleasy") for the Federal Reserve Board in the early 1970s and then was made available commercially; Speakeasy and Modeleasy are still in use currently. Simula, invented in the late 1960s by Nygaard and Dahl as a superset of Algol 60, was the first language designed to support object-oriented programming. C, an early systems programming language, was developed by Dennis Ritchie and Ken Thompson at Bell Labs between 1969 and 1973. Smalltalk (mid-1970s) provided a complete ground-up design of an object-oriented language. Prolog, designed in 1972 by Colmerauer, Roussel, and Kowalski, was the first logic programming language. ML built a polymorphic type system (invented by Robin Milner in 1973) on top of Lisp, [14] pioneering statically typed functional programming languages. Each of these languages spawned an entire family of descendants, and most modern languages count at least one of them in their ancestry. The 1960s and 1970s also saw considerable de




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ers" which expect subordinate routines to be defined first, as with Pascal, where the main routine, or driver function, is the final section of the program listing. Some notable languages that were developed in this period include: <span>1968 – Logo 1969 – B (forerunner to C) 1970 – Pascal 1970 – Forth 1972 – C 1972 – Smalltalk 1972 – Prolog 1973 – ML 1975 – Scheme 1978 – SQL (a query language, later extended) 1980s: consolidation, modules, performance[edit] [imagelink] MATLAB [imagelink] Erlang [imagelink] Tcl The 1980s were years of relative consolidat




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es, the RISC movement sparked greater interest in compilation technology for high-level languages. Language technology continued along these lines well into the 1990s. Some notable languages that were developed in this period include: <span>1980 – C++ (as C with classes, renamed in 1983) 1983 – Ada 1984 – Common Lisp 1984 – MATLAB 1984 - FoxPro (as FoxBASE, later developing into Visual FoxPro 1985 – Eiffel 1986 – Objective-C 1986 – LabVIEW (Visual Programming Language) 1986 – Erlang 1987 – Perl 1988 – Tcl 1988 – Wolfram Language (as part of Mathematica, only got a separate name in June 2013) 1989 – FL (Backus) 1990s: the Internet age[edit] [imagelink] Haskell [imagelink] Lua [imagelink] Rebol [imagelink] D Programming Language The rapid gro




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e programs more difficult to write and maintain. [citation needed] Nevertheless, scripting languages came to be the most prominent ones used in connection with the Web. Some notable languages that were developed in this period include: <span>1990 – Haskell 1991 – Python 1991 – Visual Basic 1993 – Ruby 1993 – Lua 1993 – R 1994 – CLOS (part of ANSI Common Lisp) 1995 – Ada 95 1995 – Java 1995 – Delphi (Object Pascal) 1995 – JavaScript 1995 – PHP 1997 – Rebol 1999 – D Current trends[edit] This section needs to be updated. Please update this article to reflect recent events or newly available information. (May 2015) This section p




Some notable languages developed during this period include:

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for coding 2000 processor GPU graphics processing units and supercomputer arrays including OpenCL Early research into (as-yet-unimplementable) quantum computing programming languages [imagelink] Groovy [imagelink] Rust <span>Some notable languages developed during this period include: 2000 – ActionScript 2001 – C# 2003 – Apache Groovy 2003 – Scala 2005 – F# 2006 – Windows PowerShell 2007 – Clojure 2009 – Go 2010 – Rust 2011 – Dart 2011 – Kotlin 2012 – Julia 2014 – Swift Prominent people[edit] [imagelink] Anders Hejlsberg [imagelink] Yukihiro Matsumoto [imagelink] Grace M. Hopper [imagelink] Bjarne Stroustrup