An algorithm is a set of steps to accomplish a specific task or solve a problem. It has a well-defined sequence of steps, will produce an output, and will eventually terminate. An algorithm describes the precise steps to solve a computational procedure from an input to an output in a finite number of steps. Examples of algorithms include step-by-step directions for driving to a friend's house or brushing your teeth.
Basics of Video Editing | Types of Video Editing | Video Production ProcessRavi Bhadauria
This presentation displays the most important terms related to video editing and the entire video production industry.
You are going to know about the following topics in detail:
1. What is video editing?
2. Goal of video editing?
3. Types of video editing?
4. Popular video editing software applications
5. Important terminologies of video editing
6. Important terminologies of audio editing
7. Aspect ratios
8. Standard video display sizes
9. Frame rate
10. Process of video production
11. Popular Indian video editors
12. Popular post-production houses in India
In order to learn the complete video editing, we recommend you join video editing courses. We have numerous diploma and certificate programs in post-production which include training in photo editing, video editing, motion graphics, and much more.
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An algorithm is a well-defined procedure for solving a problem through a series of unambiguous instructions. The word derives from the name of mathematician Mohammad Ibn-Musa-al-Khwarizmi. An algorithm must have specified input and output, be definitive, effective, and finite. Common algorithm types include recursive, backtracking, divide-and-conquer, dynamic programming, greedy, branch-and-bound, brute force, and randomized algorithms. Examples provided include algorithms for making brownies and calculating student grades.
This document outlines the key concepts around organizing and human resource management. It discusses the nature and purpose of organizing, including common objectives, division of labor, authority structures, communication, and coordination. It also defines organizing and describes different types of organization structures. The purpose of organizing is to facilitate management, increase efficiency, allow for growth, optimize resource use, and stimulate creativity. The outcome is for students to understand different organization types and the functions of human resources managers.
For most programming/scripting languages the concepts are all the same. The only thing that changes is the syntax in which it is written. Some languages may be easier to remember than others, but if you follow the basic guide line, it will make learning any programming language easier. This is in no way supposed to teach you everything about programming, just a general knowledge so when you do program you will understand what you are doing a little bit better.
The document discusses various parts of the Python programming language including keywords, variables, operators, data types, and more. It provides examples and explanations of concepts like:
- Keywords are reserved words with specific uses like False, None, True, and, or, etc.
- Variables store values in reserved memory locations and can be of different data types like integers, floats, strings.
- Python supports common operators for arithmetic, comparison, logical, bitwise and other operations.
- Core data types include numbers, strings, lists, tuples, and dictionaries.
- Other concepts covered are indentation, comments, input/output functions, type conversions.
The document discusses identifying and controlling workplace hazards. It defines hazards and risks, describes the major types of hazards including safety, biological, chemical, physical, ergonomic, and psychological hazards, and provides examples of each. Methods are presented for assessing hazards and risks in the workplace and ensuring a safe work environment.
This document introduces algorithms and the process of program development. It defines an algorithm as a precise list of instructions that terminates after a finite number of steps to solve a problem. It discusses methods of specifying algorithms like pseudocode and flowcharts. Properties of algorithms include being finite, unambiguous, and having a defined sequence of execution and input/output. The steps of program development are stated as understanding the problem, planning instructions, coding the program, running and debugging it. Flowcharting guidelines and common symbols are provided. Sample exercises demonstrate writing programs to calculate simple formulas.
Algorithms Lecture 1: Introduction to AlgorithmsMohamed Loey
We will discuss the following: Algorithms, Time Complexity & Space Complexity, Algorithm vs Pseudo code, Some Algorithm Types, Programming Languages, Python, Anaconda.
The document provides an introduction to algorithms through a lecture on fundamentals of algorithm analysis. It defines an algorithm as a finite sequence of unambiguous instructions to solve a problem. Characteristics of algorithms like inputs, outputs, definiteness and finiteness are discussed. The document also describes various algorithm design techniques like brute force, divide and conquer and greedy algorithms. It explains steps to write algorithms using pseudo code and discusses validating, analyzing, testing programs and specifying algorithms through pseudo code and flowcharts.
This document discusses different programming paradigms and languages. It describes batch programs which run without user interaction and event-driven programs which respond to user events. It lists many popular programming languages from Machine Language to Java and C#, and describes low-level languages that are close to machine code and high-level languages that are more human-readable. It also discusses the different types of language translators like compilers, interpreters, and assemblers and how they convert code between languages. Finally, it covers testing, debugging, and different types of errors in programming.
The document discusses the origins and drivers of software engineering as a discipline. It arose in response to frequent software project failures in the late 1960s, termed the "software crisis". Key points:
- Software engineering aims to apply systematic and quantifiable principles to software development and maintenance to improve quality, productivity and job satisfaction.
- It draws on computer science, management science, economics and other fields. Processes and models help manage complex software projects.
- Early process models included waterfall and prototyping. Later agile models like spiral emphasize iterative development and risk management over rigid phases.
Programming involves encoding algorithms into programming languages so that computers can execute them. An algorithm is needed first to solve a problem before a program can exist. Programming languages provide control constructs like sequential processing, selection, and iteration to represent algorithmic steps. They also provide data types to represent both the process and data used in algorithms.
To understand algorithm and flowchart, it is better to refer this Slideshare that I have created. I have thoroughly presented the key points that make easy in remembering what algorithm and flowchart is. The slide is really simple and wonderful to use it for a quick reference.
The document introduces programming and the C++ language. It explains that a program is a set of instructions given to a computer in a programming language to perform tasks. High-level languages like C++ were created because computers only understand binary and it is impossible for humans to program in binary. The document then covers the anatomy of a simple "Hello World" C++ program, including main functions, header files, output statements, strings, and terminators. It concludes by explaining how C++ source code is compiled into machine code and executed.
The document discusses algorithm development and provides examples of writing algorithms. It defines an algorithm as a sequence of steps to solve a problem using a computer. It notes algorithms should break problems into simple steps, number steps sequentially, and be written in simple English. Examples provided include algorithms to calculate a student's grade, convert between units of length, find the roots of a quadratic equation, find the largest of two or three numbers, and calculate an employee's bonus based on overtime worked and absences.
The document provides background information on programming languages and their history. It discusses early pioneers in computer programming such as Ada Lovelace, Herman Hollerith, and Konrad Zuse. It outlines the development of many popular modern programming languages such as Fortran, COBOL, BASIC, Pascal, C, C++, Java, PHP, JavaScript, Python, Ruby, and others, describing their key features and common uses. Ada Lovelace is noted as creating the first computer program in 1843 for Charles Babbage's analytical engine.
The document discusses algorithms and their building blocks. It defines an algorithm as a collection of well-defined, unambiguous and effectively computable instructions that return a proper output. The three building blocks of algorithms are identified as sequence, selection, and iteration. Sequence refers to a series of actions performed in order. Selection allows a program to choose between different actions or conditions. Iteration allows a block of code to be repeated while a condition is true. Pseudocode and flowcharts are introduced as common ways to express algorithms and illustrate the control flow and logic of a program.
The document discusses algorithms, providing definitions and examples of algorithms including Euclid's algorithm for computing the greatest common divisor. It also outlines properties that algorithms must have including finiteness, absence of ambiguity, defined sequence and inputs/outputs. Pseudocode is introduced as a way to express algorithms at a high level for human reading using basic logic structures like sequence, selection, and iteration.
The document contains slides from a lecture on software engineering. It discusses definitions of software and software engineering, different types of software applications, characteristics of web applications, and general principles of software engineering practice. The slides are copyrighted and intended for educational use as supplementary material for a textbook on software engineering.
An algorithm is a set of step-by-step instructions to solve a problem or complete a task. It must specify all steps clearly so a computer can follow the algorithm without additional understanding. Algorithms can be represented as pseudocode, a written informal description, or as a flowchart using graphical symbols. The key phases of an algorithm are problem solving to design the steps, then implementation in a programming language. Properties of good algorithms include being correct, efficient, and working for all possible inputs to the problem.
Lect 1. introduction to programming languagesVarun Garg
A programming language is a set of rules that allows humans to communicate instructions to computers. There are many programming languages because they have evolved over time as better ways to design them have been developed. Programming languages can be categorized based on their generation or programming paradigm such as imperative, object-oriented, logic-based, and functional. Characteristics like writability, readability, reliability and maintainability are important qualities for programming languages.
There are two types of programming languages: low-level languages which are machine-oriented and difficult for humans, and high-level languages which are easier for humans to read and write. Programs are initially written in a high-level language and then compiled into machine-executable code. Common high-level programming languages include C, C++, Java, PHP, and Visual Basic.NET.
This document discusses algorithms including:
- An algorithm is a set of instructions to accomplish a task, with inputs and outputs.
- Characteristics of algorithms include being definite, finite, unambiguous, and efficient.
- The design process involves understanding the problem, capabilities of the device, choosing exact or approximate solutions, selecting a data structure, and techniques like divide-and-conquer.
- Algorithms can be specified through languages, pseudocode, or flowcharts and must be proven correct. Their analysis considers time and space complexity.
1) The document introduces algorithms and their components such as programs, functions, variables, constants, expressions, and operators.
2) An algorithm is defined as a set of steps needed to solve a problem and examples of blackjack and squaring a number are provided.
3) The main components of an algorithm are identified as the program name, variable definitions, function prototypes, and the step-by-step algorithm.
This document introduces algorithms and the process of program development. It defines an algorithm as a precise list of instructions that terminates after a finite number of steps to solve a problem. It discusses methods of specifying algorithms like pseudocode and flowcharts. Properties of algorithms include being finite, unambiguous, and having a defined sequence of execution and input/output. The steps of program development are stated as understanding the problem, planning instructions, coding the program, running and debugging it. Flowcharting guidelines and common symbols are provided. Sample exercises demonstrate writing programs to calculate simple formulas.
Algorithms Lecture 1: Introduction to AlgorithmsMohamed Loey
We will discuss the following: Algorithms, Time Complexity & Space Complexity, Algorithm vs Pseudo code, Some Algorithm Types, Programming Languages, Python, Anaconda.
The document provides an introduction to algorithms through a lecture on fundamentals of algorithm analysis. It defines an algorithm as a finite sequence of unambiguous instructions to solve a problem. Characteristics of algorithms like inputs, outputs, definiteness and finiteness are discussed. The document also describes various algorithm design techniques like brute force, divide and conquer and greedy algorithms. It explains steps to write algorithms using pseudo code and discusses validating, analyzing, testing programs and specifying algorithms through pseudo code and flowcharts.
This document discusses different programming paradigms and languages. It describes batch programs which run without user interaction and event-driven programs which respond to user events. It lists many popular programming languages from Machine Language to Java and C#, and describes low-level languages that are close to machine code and high-level languages that are more human-readable. It also discusses the different types of language translators like compilers, interpreters, and assemblers and how they convert code between languages. Finally, it covers testing, debugging, and different types of errors in programming.
The document discusses the origins and drivers of software engineering as a discipline. It arose in response to frequent software project failures in the late 1960s, termed the "software crisis". Key points:
- Software engineering aims to apply systematic and quantifiable principles to software development and maintenance to improve quality, productivity and job satisfaction.
- It draws on computer science, management science, economics and other fields. Processes and models help manage complex software projects.
- Early process models included waterfall and prototyping. Later agile models like spiral emphasize iterative development and risk management over rigid phases.
Programming involves encoding algorithms into programming languages so that computers can execute them. An algorithm is needed first to solve a problem before a program can exist. Programming languages provide control constructs like sequential processing, selection, and iteration to represent algorithmic steps. They also provide data types to represent both the process and data used in algorithms.
To understand algorithm and flowchart, it is better to refer this Slideshare that I have created. I have thoroughly presented the key points that make easy in remembering what algorithm and flowchart is. The slide is really simple and wonderful to use it for a quick reference.
The document introduces programming and the C++ language. It explains that a program is a set of instructions given to a computer in a programming language to perform tasks. High-level languages like C++ were created because computers only understand binary and it is impossible for humans to program in binary. The document then covers the anatomy of a simple "Hello World" C++ program, including main functions, header files, output statements, strings, and terminators. It concludes by explaining how C++ source code is compiled into machine code and executed.
The document discusses algorithm development and provides examples of writing algorithms. It defines an algorithm as a sequence of steps to solve a problem using a computer. It notes algorithms should break problems into simple steps, number steps sequentially, and be written in simple English. Examples provided include algorithms to calculate a student's grade, convert between units of length, find the roots of a quadratic equation, find the largest of two or three numbers, and calculate an employee's bonus based on overtime worked and absences.
The document provides background information on programming languages and their history. It discusses early pioneers in computer programming such as Ada Lovelace, Herman Hollerith, and Konrad Zuse. It outlines the development of many popular modern programming languages such as Fortran, COBOL, BASIC, Pascal, C, C++, Java, PHP, JavaScript, Python, Ruby, and others, describing their key features and common uses. Ada Lovelace is noted as creating the first computer program in 1843 for Charles Babbage's analytical engine.
The document discusses algorithms and their building blocks. It defines an algorithm as a collection of well-defined, unambiguous and effectively computable instructions that return a proper output. The three building blocks of algorithms are identified as sequence, selection, and iteration. Sequence refers to a series of actions performed in order. Selection allows a program to choose between different actions or conditions. Iteration allows a block of code to be repeated while a condition is true. Pseudocode and flowcharts are introduced as common ways to express algorithms and illustrate the control flow and logic of a program.
The document discusses algorithms, providing definitions and examples of algorithms including Euclid's algorithm for computing the greatest common divisor. It also outlines properties that algorithms must have including finiteness, absence of ambiguity, defined sequence and inputs/outputs. Pseudocode is introduced as a way to express algorithms at a high level for human reading using basic logic structures like sequence, selection, and iteration.
The document contains slides from a lecture on software engineering. It discusses definitions of software and software engineering, different types of software applications, characteristics of web applications, and general principles of software engineering practice. The slides are copyrighted and intended for educational use as supplementary material for a textbook on software engineering.
An algorithm is a set of step-by-step instructions to solve a problem or complete a task. It must specify all steps clearly so a computer can follow the algorithm without additional understanding. Algorithms can be represented as pseudocode, a written informal description, or as a flowchart using graphical symbols. The key phases of an algorithm are problem solving to design the steps, then implementation in a programming language. Properties of good algorithms include being correct, efficient, and working for all possible inputs to the problem.
Lect 1. introduction to programming languagesVarun Garg
A programming language is a set of rules that allows humans to communicate instructions to computers. There are many programming languages because they have evolved over time as better ways to design them have been developed. Programming languages can be categorized based on their generation or programming paradigm such as imperative, object-oriented, logic-based, and functional. Characteristics like writability, readability, reliability and maintainability are important qualities for programming languages.
There are two types of programming languages: low-level languages which are machine-oriented and difficult for humans, and high-level languages which are easier for humans to read and write. Programs are initially written in a high-level language and then compiled into machine-executable code. Common high-level programming languages include C, C++, Java, PHP, and Visual Basic.NET.
This document discusses algorithms including:
- An algorithm is a set of instructions to accomplish a task, with inputs and outputs.
- Characteristics of algorithms include being definite, finite, unambiguous, and efficient.
- The design process involves understanding the problem, capabilities of the device, choosing exact or approximate solutions, selecting a data structure, and techniques like divide-and-conquer.
- Algorithms can be specified through languages, pseudocode, or flowcharts and must be proven correct. Their analysis considers time and space complexity.
1) The document introduces algorithms and their components such as programs, functions, variables, constants, expressions, and operators.
2) An algorithm is defined as a set of steps needed to solve a problem and examples of blackjack and squaring a number are provided.
3) The main components of an algorithm are identified as the program name, variable definitions, function prototypes, and the step-by-step algorithm.
The document defines algorithms and different representations of algorithms such as normal English, flow charts, pseudo code, and programs. It provides examples of different control structures like sequence, selection, and repetition. Key points include: algorithms must be unambiguous, terminate in a finite number of steps, and time, memory, accuracy and generality are qualities of a good algorithm. Pseudo code uses keywords and indentation to represent program logic clearly. Flow charts use standard symbols and avoid intersecting lines to depict a process visually. Control structures determine the order of execution through sequencing, conditional checks, or repeated execution.
The document introduces algorithms and provides examples of algorithms for insertion and deletion from an array, as well as matrix multiplication. It also provides the definition of a magic square and asks to write an algorithm to read integers for a square matrix and determine if it represents a magic square.
Dokumen tersebut memberikan penjelasan mengenai konsep dasar data mining klasifikasi, proses klasifikasi menggunakan algoritma Naive Bayes, serta contoh kasus klasifikasi menggunakan atribut usia, pendapatan, pekerjaan, dan punya deposito atau tidak.
This document discusses algorithm analysis and complexity. It introduces algorithm analysis as a way to predict and compare algorithm performance. Different algorithms for computing factorials and finding the maximum subsequence sum are presented, along with their time complexities. The importance of efficient algorithms for problems involving large datasets is discussed.
This document discusses different sorting algorithms including bubble sort, insertion sort, and selection sort. It provides details on each algorithm, including time complexity, code examples, and graphical examples. Bubble sort is an O(n2) algorithm that works by repeatedly comparing and swapping adjacent elements. Insertion sort also has O(n2) time complexity but is more efficient than bubble sort for small or partially sorted lists. Selection sort finds the minimum value and swaps it into place at each step.
This document provides an overview of the Pharo open-source Smalltalk project. It begins with a brief introduction to Smalltalk syntax, object model, and key concepts like message passing and dynamic binding. It then discusses Pharo itself, describing it as a pure object-oriented programming language and integrated development environment based on Smalltalk. The document demonstrates some Pharo tools and features like the class browser and polymorph user interface support. It highlights Pharo's open development process and encourages community involvement through activities like reporting bugs, writing tests, and contributing code.
Seaside is a web application framework that is written in Smalltalk. Smalltalk has been hugely influential on the development of computer languages but realistically how many people have ever used it? Seaside is a practical application of Smalltalk to the web sphere.
(How) Does VA Smalltalk fit into today's IT landscapes?Joachim Tuchel
This talk gives a brief overview of today's most imprtant IT Trends, from rich client and rich internet applications to Web Services. Joachim Tuchel shows how VA Smalltalk and it's existing and upcoming features help developers integrate new and existing VA Smalltalk applications into these architectures.
This presentation was given by Joachim Tuchel at the VA Smalltalk Forum Europe 2008 in Frankfurt am Main.
The document provides an introduction to the Smalltalk programming language, describing its origins at Xerox PARC in the 1970s, key concepts such as everything being an object and the use of images, and concluding with recommendations for further reading on Smalltalk.
This document discusses looping structures in algorithms and programming. It defines looping as repeating statements to fulfill a looping condition. The main types of looping structures are for, while, and repeat loops. Examples are given in pseudocode and Pascal to illustrate for loops that count ascending and descending, while loops, and repeat loops. Exercises are provided to practice different types of loops.
Kevin Luten, the Australian Task 24 expert, invited us to take part of a transport discussion panel following the 2013 Behavior, Energy and Climate Change conference in Sacramento. Here are the slides telling some of the transport stories from several participating countries.
This document provides an introduction to algorithms including definitions, characteristics, and the design process. It defines an algorithm as a finite set of unambiguous instructions to solve a problem. Key points:
- Algorithms must have input, output, be definitive, finite, and effective.
- The design process includes understanding the problem, developing a solution algorithm, proving correctness, analyzing efficiency, and coding.
- Examples of algorithm types are approximate, probabilistic, infinite, and heuristic.
- Pseudocode is commonly used to specify algorithms more clearly than natural language alone.
Computer programs contain instructions that tell computers what to do. Programs are written using programming languages as computers only understand machine code. There are different types of programming languages including machine language, assembly language, and high-level languages. High-level languages are easier for humans to read but must be compiled into machine code for computers to execute. Programming involves defining a problem, describing inputs and outputs, developing an algorithmic solution, and testing the program.
Design and Analysis of Algorithm ppt for unit onessuserb7c8b8
The document outlines an algorithms course, including course details, objectives, and an introduction. The course code is 10211CS202 and name is Design and Analysis of Algorithms. It has 4 credits and meets for 6 hours per week. The course aims to teach fundamental techniques for effective problem solving, analyzing algorithm performance, and designing efficient algorithms. It covers topics like sorting, searching, and graph algorithms.
The document provides an introduction to a course on Data Structures and Algorithms. It outlines the course topics which include arrays, linked lists, stacks, queues, trees, sorting algorithms, and graph algorithms. It introduces the lecturer, Syeda Nazia Ashraf, and provides her background and experience. The grading breakdown and textbooks are listed. The goals of the course are to learn commonly used data structures, design algorithms, and implement data structures and algorithms in C language code.
A typical programming task can be divided into two phases:
Problem-solving phase: produce an ordered sequence of steps that describe the solution of the problem this sequence of steps is called an algorithm.
Implementation phase: implement the program in some programming language.
Every algorithm must satisfy the following criteria:
Input. Zero or more quantities are externally supplied.
Output. At least one quantity is produced.
Definiteness. Each instruction must be clear and unambiguous(Unique meaning).
Finiteness. An algorithm terminates in a finite number of steps.
Effectiveness. Every instruction must be basic enough to be carried out than, means not so complex.
An algorithm is a finite set of steps defining the solution of a particular problem.
What is the difference between an algorithm and a program?
a program is an implementation of an algorithm to be run on a specific computer and operating system.
an algorithm is more abstract – it does not deal with machine-specific details – think of it as a method to solve a problem.
What is a good algorithm?
Efficient algorithms are good, we generally measure the efficiency of an algorithm based on:
Time: the algorithm should take minimum time to execute.
Space: the algorithm should use less memory.
DIFFERENCE BETWEEN ALGORITHM AND PSEUDOCODE?
An algorithm is a well-defined sequence of steps that provides a solution for a given problem, while pseudocode is one of the methods that can be used to represent an algorithm.
While algorithms can be written in natural language, pseudocode is written in a format that is closely related to high-level programming language structures.
But pseudocode does not use specific programming language syntax and therefore could be understood by programmers who are familiar with different programming languages. Additionally, transforming an algorithm presented in pseudocode to programming code could be much easier than converting an algorithm written in natural language.
But pseudocode does not use specific programming language syntax and therefore could be understood by programmers who are familiar with different programming languages.
Additionally, transforming an algorithm presented in pseudocode to programming code could be much easier than converting an algorithm written in natural language.
Concept of Problem Solving, Introduction to Algorithms, Characteristics of Algorithms, Introduction to Data Structure, Data Structure Classification (Linear and Non-linear, Static and Dynamic, Persistent and Ephemeral data structures), Time complexity and Space complexity, Asymptotic Notation - The Big-O, Omega and Theta notation, Algorithmic upper bounds, lower bounds, Best, Worst and Average case analysis of an Algorithm, Abstract Data Types (ADT)
The document discusses the concepts of programs and algorithms. It defines a program as a group of sequential statements that are executed line by line to achieve a goal. An algorithm is described as a step-by-step process that precisely defines a sequence of operations to solve a computational problem. The document also outlines the key components of a programming language, characteristics of good programs, stages of the program development process, and provides examples of algorithms.
01 Introduction to analysis of Algorithms.pptxssuser586772
An algorithm is a set of steps of operations to solve a problem performing calculation, data processing, and automated reasoning tasks.
An algorithm is an efficient method that can be expressed within finite amount of Time and space.
The important aspects of algorithm design include creating an efficient algorithm to solve a problem in an efficient way using minimum time and space.
To solve a problem, different approaches can be followed. Some of them can be efficient with respect to time consumption, whereas other approaches may be memory efficient. To Evaluate An Algorithm we have to Satisfy the following Criteria:
INPUT: The Algorithm should be given zero or more input.
OUTPUT: At least one quantity is produced. For each input the algorithm produced value from specific task.
DEFINITENESS: Each instruction is clear and unambiguous.
FINITENESS: If we trace out the instructions of an algorithm, then for all cases, the algorithm terminates after a finite number of steps.
EFFECTIVENESS: Every instruction must very basic so that it can be carried out, in principle, by a person using only pencil & paper.Algorithm : Systematic logical approach which is a well-defined, step-by-step procedure that allows a computer to solve a problem.
Pseudocode : It is a simpler version of a programming code in plain English which uses short phrases to write code for a program before it is implemented in a specific programming language.
Program : It is exact code written for problem following all the rules of the programming language.Algorithm can be described (Represent) in four ways.
Natural language like English:
When this way is chooses, care should be taken, we
should ensure that each & every statement is definite.
(no ambiguity)
2. Graphic representation called flowchart:
This method will work well when the algorithm is small& simple.
3. Pseudo-code Method:
In this method, we should typically describe algorithms as
program, which resembles language like Pascal & Algol
(Algorithmic Language).
4.Programming Language:
we have to use programming language to write algorithms like
C, C++,JAVA etc.Comments begin with // and continue until the end of line.
Blocks are indicated with matching braces { and }.
An identifier begins with a letter. The data types of variables are not explicitly declared.
node= record
{
data type 1 data 1;
data type n data n;
node *link;
}
4. There are two Boolean values TRUE and FALSE.
Logical Operators
AND, OR, NOT
Relational Operators
<, <=,>,>=, =, !=
1.How to create an algorithm: To create an algorithm we have following design technique
a) Divide & Conquer
b) Greedy method
c) Dynamic Programming
d) Branch & Bound
e) Backtracking
2.How to validate an algorithm:
Once an algorithm is created it is necessary to show that it computes the correct Pr
This document discusses algorithms and provides an example algorithm for adding three numbers and printing the sum. It defines an algorithm as a set of steps to solve a problem and lists characteristics of algorithms such as being clear, well-defined, finite, feasible, and language independent. The document also outlines a process for designing algorithms which includes defining the problem, developing a model, specifying the algorithm, designing it, checking correctness, analyzing it, implementing it, testing it, and documenting it. It then provides an example algorithm that takes three numbers as input, adds them together, stores the sum in a variable, and prints the result.
02 Algorithms and flowcharts - computers.pptxarifaqazi2
Computer programming involves writing code to give computers instructions. An algorithm is a set of steps to solve a problem or complete a task. It takes inputs and produces outputs. Algorithms can be expressed using pseudocode, flowcharts, or programming languages. Pseudocode and flowcharts allow visualizing the steps in an informal way before writing actual code. Computer languages include low-level assembly languages close to machine code, and high-level languages like Python and Java that are easier for humans to read and write.
The document discusses algorithms and flowcharts. It defines an algorithm as a finite set of steps to solve a problem and notes that algorithms can be expressed in various ways, including pseudocode and flowcharts. Pseudocode uses a language similar to programming but without specific syntax, making it readable by programmers familiar with different languages. A flowchart provides a graphical representation of an algorithm's logical flow. The document provides examples of algorithms expressed in pseudocode and represented through flowcharts, such as finding the average of two numbers and calculating the largest of several inputs. It also discusses common flowchart structures like sequence, selection, and iteration.
The document provides an introduction to programming and problem solving using computers. It discusses the following key points:
- Problem solving involves determining the inputs, outputs, and steps to solve a problem. Computers can be programmed to solve problems more quickly if they involve extensive inputs/outputs or complex/time-consuming methods.
- The software development process includes requirements specification, analysis, design, implementation, testing, and documentation. Algorithms using pseudocode or flowcharts are designed to solve problems.
- Programming languages have evolved from low-level machine languages to high-level languages. Earlier generations like assembly language were more machine-oriented while modern languages are more portable, problem-oriented, and easier for humans to read and write
Dokumen tersebut memberikan tips untuk membuat formatting kode program yang baik agar mudah dibaca dan dipahami. Terdapat dua jenis formatting, yaitu vertical dan horizontal formatting. Secara vertical, kode perlu diatur dengan memperhatikan konsep-konsep, jarak antar konsep, kerapatan kode yang berkaitan, dan letak deklarasi dan pemanggilan fungsi. Secara horizontal, perlu memperhatikan pemberian jarak, penyamaan baris, dan pengindentasian untuk membedakan struktur program.
Slide ini menjelaskan perihal penggunaan komentar yang baik dan buruk pada suatu kode program. Slide ini merupakan bahan ajar untuk mata kuliah Clean Code dan Design Pattern.
Dokumen tersebut memberikan tips-tips untuk membuat nama variabel, fungsi, kelas, dan paket yang baik dalam pembuatan kode program. Beberapa tips utama adalah menggunakan nama yang jelas maksudnya, hindari penggunaan encoding, gunakan kata benda untuk nama kelas dan verba untuk nama metode, serta tambahkan konteks yang bermakna.
Dokumen tersebut membahas tentang pengujian perangkat lunak, termasuk definisi pengujian perangkat lunak, tujuan pengujian, jenis pengujian seperti manual testing, automated testing, unit testing, integration testing, serta metode pengujian seperti white box testing dan black box testing.
Slide ini berisi penjelasan tentang Data Mining Klasifikasi. Di dalamnya ada tiga algoritma yang dibahas, yaitu: Naive Bayes, kNN, dan ID3 (Decision Tree).
Dokumen tersebut membahas algoritma program dinamis untuk menentukan lintasan terpendek antara dua simpul dalam sebuah graf. Metode yang digunakan adalah program dinamis mundur dimana permasalahan dibagi menjadi beberapa tahap dan dihitung secara mundur untuk menentukan nilai optimal pada setiap tahap. Hasil akhir adalah terdapat tiga lintasan terpendek dengan panjang 11 antara simpul 1 dan 10.
Teks tersebut membahas strategi algoritma Divide and Conquer untuk memecahkan masalah. Strategi ini membagi masalah menjadi submasalah kecil, memecahkan submasalah tersebut secara rekursif, lalu menggabungkan hasilnya untuk mendapatkan solusi masalah awal. Dua contoh masalah yang dijelaskan adalah mencari nilai maksimum dan minimum dalam tabel, serta mencari pasangan titik terdekat dalam himpunan titik.
Slide ini berisi penjelasan tentang teorema-teorema yang berlaku untuk notasi asimptotik beserta cara perhitungannya untuk kebutuhan waktu suatu algoritma.
Automating Map Production With FME and PythonSafe Software
People still love a good paper map, but every time a request lands on a GIS team’s desk, it takes time to create that perfect, individual map—even when you're ready and have projects prepped. Then come the inevitable changes and iterations that add even more time to the process. This presentation explores a solution for automating map production using FME and Python. FME handles the setup of variables, leveraging GIS reference layers and parameters to manage details like map orientation, label sizes, and layout elements. Python takes over to export PDF maps for each location and template size, uploading them monthly to ArcGIS Online. The result? Fresh, regularly updated maps, ready for anyone to grab anytime—saving you time, effort, and endless revisions while keeping users happy with up-to-date, accessible maps.
Key AI Technologies Used by Indian Artificial Intelligence CompaniesMypcot Infotech
Indian tech firms are rapidly adopting advanced tools like machine learning, natural language processing, and computer vision to drive innovation. These key AI technologies enable smarter automation, data analysis, and decision-making. Leading developments are shaping the future of digital transformation among top artificial intelligence companies in India.
For more information please visit here https://www.mypcot.com/artificial-intelligence
In today's world, artificial intelligence (AI) is transforming the way we learn.
This talk will explore how we can use AI tools to enhance our learning experiences, by looking at some (recent) research that has been done on the matter.
But as we embrace these new technologies, we must also ask ourselves:
Are we becoming less capable of thinking for ourselves?
Do these tools make us smarter, or do they risk dulling our critical thinking skills?
This talk will encourage us to think critically about the role of AI in our education. Together, we will discover how to use AI to support our learning journey while still developing our ability to think critically.
Who will create the languages of the future?Jordi Cabot
Will future languages be created by language engineers?
Can you "vibe" a DSL?
In this talk, we will explore the changing landscape of language engineering and discuss how Artificial Intelligence and low-code/no-code techniques can play a role in this future by helping in the definition, use, execution, and testing of new languages. Even empowering non-tech users to create their own language infrastructure. Maybe without them even realizing.
Integrating Survey123 and R&H Data Using FMESafe Software
West Virginia Department of Transportation (WVDOT) actively engages in several field data collection initiatives using Collector and Survey 123. A critical component for effective asset management and enhanced analytical capabilities is the integration of Geographic Information System (GIS) data with Linear Referencing System (LRS) data. Currently, RouteID and Measures are not captured in Survey 123. However, we can bridge this gap through FME Flow automation. When a survey is submitted through Survey 123 for ArcGIS Portal (10.8.1), it triggers FME Flow automation. This process uses a customized workbench that interacts with a modified version of Esri's Geometry to Measure API. The result is a JSON response that includes RouteID and Measures, which are then applied to the feature service record.
Maximizing Business Value with AWS Consulting Services.pdfElena Mia
An overview of how AWS consulting services empower organizations to optimize cloud adoption, enhance security, and drive innovation. Read More: https://www.damcogroup.com/aws-cloud-services/aws-consulting.
Join the Denver Marketo User Group, Captello and Integrate as we dive into the best practices, tools, and strategies for maintaining robust, high-performing databases. From managing vendors and automating orchestrations to enriching data for better insights, this session will unpack the key elements that keep your data ecosystem running smoothly—and smartly.
We will hear from Steve Armenti, Twelfth, and Aaron Karpaty, Captello, and Frannie Danzinger, Integrate.
Integration Ignited Redefining Event-Driven Architecture at Wix - EventCentricNatan Silnitsky
At Wix, we revolutionized our platform by making integration events the backbone of our 4,000-microservice ecosystem. By abandoning traditional domain events for standardized Protobuf events through Kafka, we created a universal language powering our entire architecture.
We'll share how our "single-aggregate services" approach—where every CUD operation triggers semantic events—transformed scalability and extensibility, driving efficient event choreography, data lake ingestion, and search indexing.
We'll address our challenges: balancing consistency with modularity, managing event overhead, and solving consumer lag issues. Learn how event-based data prefetches dramatically improved performance while preserving the decoupling that makes our platform infinitely extensible.
Key Takeaways:
- How integration events enabled unprecedented scale and extensibility
- Practical strategies for event-based data prefetching that supercharge performance
- Solutions to common event-driven architecture challenges
- When to break conventional architectural rules for specific contexts
Meet You in the Middle: 1000x Performance for Parquet Queries on PB-Scale Dat...Alluxio, Inc.
Alluxio Webinar
June 10, 2025
For more Alluxio Events: https://www.alluxio.io/events/
Speaker:
David Zhu (Engineering Manager @ Alluxio)
Storing data as Parquet files on cloud object storage, such as AWS S3, has become prevalent not only for large-scale data lakes but also as lightweight feature stores for training and inference, or as document stores for Retrieval-Augmented Generation (RAG). However, querying petabyte-to-exabyte-scale data lakes directly from S3 remains notoriously slow, with latencies typically ranging from hundreds of milliseconds to several seconds.
In this webinar, David Zhu, Software Engineering Manager at Alluxio, will present the results of a joint collaboration between Alluxio and a leading SaaS and data infrastructure enterprise that explored leveraging Alluxio as a high-performance caching and acceleration layer atop AWS S3 for ultra-fast querying of Parquet files at PB scale.
David will share:
- How Alluxio delivers sub-millisecond Time-to-First-Byte (TTFB) for Parquet queries, comparable to S3 Express One Zone, without requiring specialized hardware, data format changes, or data migration from your existing data lake.
- The architecture that enables Alluxio’s throughput to scale linearly with cluster size, achieving one million queries per second on a modest 50-node deployment, surpassing S3 Express single-account throughput by 50x without latency degradation.
- Specifics on how Alluxio offloads partial Parquet read operations and reduces overhead, enabling direct, ultra-low-latency point queries in hundreds of microseconds and achieving a 1,000x performance gain over traditional S3 querying methods.
AI and Deep Learning with NVIDIA TechnologiesSandeepKS52
Artificial intelligence and deep learning are transforming various fields by enabling machines to learn from data and make decisions. Understanding how to prepare data effectively is crucial, as it lays the foundation for training models that can recognize patterns and improve over time. Once models are trained, the focus shifts to deployment, where these intelligent systems are integrated into real-world applications, allowing them to perform tasks and provide insights based on new information. This exploration of AI encompasses the entire process from initial concepts to practical implementation, highlighting the importance of each stage in creating effective and reliable AI solutions.
Providing Better Biodiversity Through Better DataSafe Software
This session explores how FME is transforming data workflows at Ireland’s National Biodiversity Data Centre (NBDC) by eliminating manual data manipulation, incorporating machine learning, and enhancing overall efficiency. Attendees will gain insight into how NBDC is using FME to document and understand internal processes, make decision-making fully transparent, and shine a light on underlying code to improve clarity and reduce silent failures.
The presentation will also outline NBDC’s future plans for FME, including empowering staff to access and query data independently, without relying on external consultants. It will also showcase ambitions to connect to new data sources, unlock the full potential of its valuable datasets, create living atlases, and place its valuable data directly into the hands of decision-makers across Ireland—ensuring that biodiversity is not only protected but actively enhanced.
The Future of Open Source Reporting Best Alternatives to Jaspersoft.pdfVarsha Nayak
In recent years, organizations have increasingly sought robust open source alternative to Jasper Reports as the landscape of open-source reporting tools rapidly evolves. While Jaspersoft has been a longstanding choice for generating complex business intelligence and analytics reports, factors such as licensing changes and growing demands for flexibility have prompted many businesses to explore other options. Among the most notable alternatives to Jaspersoft, Helical Insight stands out for its powerful open-source architecture, intuitive analytics, and dynamic dashboard capabilities. Designed to be both flexible and budget-friendly, Helical Insight empowers users with advanced features—such as in-memory reporting, extensive data source integration, and customizable visualizations—making it an ideal solution for organizations seeking a modern, scalable reporting platform. This article explores the future of open-source reporting and highlights why Helical Insight and other emerging tools are redefining the standards for business intelligence solutions.
GDG Douglas - Google AI Agents: Your Next Intern?felipeceotto
Presentation done at the GDG Douglas event for June 2025.
A first look at Google's new Agent Development Kit.
Agent Development Kit is a new open-source framework from Google designed to simplify the full stack end-to-end development of agents and multi-agent systems.
FME as an Orchestration Tool - Peak of Data & AI 2025Safe Software
Processing huge amounts of data through FME can have performance consequences, but as an orchestration tool, FME is brilliant! We'll take a look at the principles of data gravity, best practices, pros, cons, tips and tricks. And of course all spiced up with relevant examples!
Insurance policy management software transforms complex, manual insurance operations into streamlined, efficient digital workflows, enhancing productivity, accuracy, customer service, and profitability for insurers. Visit https://www.damcogroup.com/insurance/policy-management-software for more details!
In this session we cover the benefits of a migration to Cosmos DB, migration paths, common pain points and best practices. We share our firsthand experiences and customer stories. Adiom is the trusted partner for migration solutions that enable seamless online database migrations from MongoDB to Cosmos DB vCore, and DynamoDB to Cosmos DB for NoSQL.
How Insurance Policy Administration Streamlines Policy Lifecycle for Agile Op...Insurance Tech Services
A modern Policy Administration System streamlines workflows and integrates with core systems to boost speed, accuracy, and customer satisfaction across the policy lifecycle. Visit https://www.damcogroup.com/insurance/policy-administration-systems for more details!
4. • Name of subject : Algorithm and and Programming
• Prerequisite : none
• Lecturer : Adam Mukharil Bachtiar
• SKS : 4 SKS (Divide into 2 Teoritics and 2 Practises)
Description of Subject
12. SyllabusofSubject
• Introduction of Algorithms
• Introduction of Dev Pascal, Data Type, value,
and naming
• Sequential Structure
• Branching Structure
• Looping and Structure
• Procedure and Function
• Middle Test
18. Some Terms in Programming
• Program is implementation of ALGORITHM that
was made from one programming language.
• Programming language is notation that was used
in ALGORITHM NOTATION to communicate with
computers.
• Programmers are people who made the
programs with ONE OR MANY programming
languages.
20. Build the Program
• Problem Definition
• Requirements Analysis
• Build the algorithms
• Coding
• Testing and Debugging
• Maintenance
• Documentation
23. Example of Descriptive Analysis
How to Make Scramble Egg:
• Pour oil into skillet.
• Heat oil.
• Break the eggs and pour into the hot oil.
• Fry it
• Serve on a plate
24. Example of Flow Chart
SYMBOL ACTIVITY
INPUT/OUTPUT
PROCESSING
DECISION
PROCEDURE/SUBROUTINE
25. Example of Flow Chart
SYMBOL ACTIVITY
FLOW LINES
START/TERMINATOR
ON PAGE CONNECTOR
OFF PAGE REFERENCE
33. Exercise 1
Turn the process of exchange value with variable
into:
• Descriptive Analysis
• Flow Chart
• Pseudo Code
34. Exercise 2
Make algoritm for exchange value without variable
(this case only suitable for integer) in:
• Descriptive Analysis
• Flow Chart
• Pseudo Code
35. Exercise 3
Make algoritm for basic arithmetic operation (add,
substract, multiply, and divide) in:
• Descriptive Analysis
• Flow Chart
• Pseudo Code