Anoushiravan Ghamsari, known as Anoush Ghamsari is a brilliant architect, the way he uses his creativity to create phenomenal concepts is beyond this world.
This document discusses flowcharts and pseudocode as tools for problem solving and programming. It provides examples of how to represent algorithms using flowcharts and pseudocode. Flowcharts graphically show the logical steps and relationships between steps to solve a problem. Pseudocode uses English-like phrases to outline the steps. The document gives examples of flowcharts and pseudocode for problems like calculating postage for letters and finding a class average grade. It also discusses basic flowchart symbols and programming structures like sequence, decision, and looping.
This document discusses the process of problem solving through programming. It begins by defining an algorithm as a sequence of instructions to solve a problem and a program as an algorithm expressed in a language a computer can understand. It then outlines the programming process of analyzing a problem to determine the input and output, planning an algorithm using tools like IPO charts and pseudocode, and coding the algorithm. It provides examples of analyzing problems, planning algorithms, and desk-checking algorithms on sample data.
Operating systems can be classified as single-user or multi-user; single-user systems support only one user at a time and were common for desktop systems, while multi-user systems allow regulated access for multiple simultaneous users through user accounts, as seen in mainframe and Unix systems.
This document provides an overview of problem solving basics and sequential solutions for computer programming problems. It discusses decomposing problems by identifying inputs, outputs, verbs, and linking them. It also covers representing solutions as flowcharts and pseudocode. An example of calculating box volume is used to demonstrate the three-step process of decomposition, flowcharting, and writing pseudocode. The document also introduces selection-based solutions using logical decisions and conditional statements.
An algorithm is a step-by-step process for solving a problem or completing a task. There are two main tools used to document algorithms: flowcharts and pseudocode. A flowchart is a graphical representation of an algorithm that uses standardized symbols to show the sequence of steps, while pseudocode specifies the algorithm steps using natural language. The five steps in using a computer as a problem-solving tool are: developing an algorithm and flowchart, writing the program code, entering the program into the computer, testing and debugging the program, and running the program to obtain results.
Computer Organization and Architecture OverviewDhaval Bagal
This document discusses computer architecture and organization. It defines architecture as the attributes visible to the programmer, like instruction set and data representation, while organization refers to the operational units and interconnections that implement the architecture. Examples of architectural design issues include whether there is a multiply instruction, while organizational issues could be whether multiplication is done in hardware or software. The architecture may not change often but the organization does as technology advances to improve performance and speed.
An algorithm is a step-by-step procedure to solve a problem using a finite number of instructions. To create an algorithm, it must have clear inputs and outputs, unambiguous steps that terminate in a finite number of steps, and each step must be feasible to carry out using paper and pencil. Algorithms use conditional patterns and comments to help with modifications. A flowchart provides a visual representation of an algorithm using blocks like start, stop, assignment, processing, input, output, and conditional statements to depict the sequencing and repetition of instructions.
This document discusses flowcharts and pseudocode as tools for problem solving and programming. It provides examples of how to represent algorithms using flowcharts and pseudocode. Flowcharts graphically show the logical steps and relationships between steps to solve a problem. Pseudocode uses English-like phrases to outline the steps. The document gives examples of flowcharts and pseudocode for problems like calculating postage for letters and finding a class average grade. It also discusses basic flowchart symbols and programming structures like sequence, decision, and looping.
This document discusses the process of problem solving through programming. It begins by defining an algorithm as a sequence of instructions to solve a problem and a program as an algorithm expressed in a language a computer can understand. It then outlines the programming process of analyzing a problem to determine the input and output, planning an algorithm using tools like IPO charts and pseudocode, and coding the algorithm. It provides examples of analyzing problems, planning algorithms, and desk-checking algorithms on sample data.
Operating systems can be classified as single-user or multi-user; single-user systems support only one user at a time and were common for desktop systems, while multi-user systems allow regulated access for multiple simultaneous users through user accounts, as seen in mainframe and Unix systems.
This document provides an overview of problem solving basics and sequential solutions for computer programming problems. It discusses decomposing problems by identifying inputs, outputs, verbs, and linking them. It also covers representing solutions as flowcharts and pseudocode. An example of calculating box volume is used to demonstrate the three-step process of decomposition, flowcharting, and writing pseudocode. The document also introduces selection-based solutions using logical decisions and conditional statements.
An algorithm is a step-by-step process for solving a problem or completing a task. There are two main tools used to document algorithms: flowcharts and pseudocode. A flowchart is a graphical representation of an algorithm that uses standardized symbols to show the sequence of steps, while pseudocode specifies the algorithm steps using natural language. The five steps in using a computer as a problem-solving tool are: developing an algorithm and flowchart, writing the program code, entering the program into the computer, testing and debugging the program, and running the program to obtain results.
Computer Organization and Architecture OverviewDhaval Bagal
This document discusses computer architecture and organization. It defines architecture as the attributes visible to the programmer, like instruction set and data representation, while organization refers to the operational units and interconnections that implement the architecture. Examples of architectural design issues include whether there is a multiply instruction, while organizational issues could be whether multiplication is done in hardware or software. The architecture may not change often but the organization does as technology advances to improve performance and speed.
An algorithm is a step-by-step procedure to solve a problem using a finite number of instructions. To create an algorithm, it must have clear inputs and outputs, unambiguous steps that terminate in a finite number of steps, and each step must be feasible to carry out using paper and pencil. Algorithms use conditional patterns and comments to help with modifications. A flowchart provides a visual representation of an algorithm using blocks like start, stop, assignment, processing, input, output, and conditional statements to depict the sequencing and repetition of instructions.
The document discusses algorithms and flowcharts. It defines an algorithm as a step-by-step procedure to solve a problem and get a desired output. Common algorithm categories include search, sort, insert, update, and delete operations on data structures. Flowcharts provide a graphical representation of an algorithm's steps and logic. The document presents examples of an algorithm to add two numbers and the benefits of algorithms and flowcharts, such as effective problem analysis, proper documentation, and efficient coding and debugging. It also notes potential disadvantages like complexity when logic is complicated and the need to redraw flowcharts during alterations.
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.
This document discusses algorithms and flowcharts. It defines an algorithm as a step-by-step method for solving a problem with characteristics like being precise, finite, and applying to a set of inputs. A flowchart is then introduced as a graphical representation of an algorithm that is helpful for understanding and documenting complex programs. The document provides examples of standard flowchart symbols and guidelines for creating effective flowcharts, such as having a logical start and finish with one flow line entering and leaving symbols. An example algorithm and flowchart are given for finding the average of two numbers by inputting the values, adding them, dividing the sum by two, and outputting the average.
This document discusses fundamentals of algorithms including:
- What algorithms are and their evolution from Persian mathematicians.
- The process of designing algorithms including defining inputs, outputs, and order of instructions.
- The need for algorithms to be correct according to their specifications and methods for confirming correctness.
- Iterative design issues such as use of loops, efficiency considerations, and estimating execution time.
- Algorithmic strategies like divide and conquer, backtracking, dynamic programming, and heuristics.
Problem Solving Techniques and Introduction to CPrabu U
This document provides an overview of problem solving techniques, programs, and the program development cycle. It discusses:
1. The steps of problem solving techniques include defining the problem, formulating a mathematical model, developing an algorithm using a flowchart or pseudocode, writing code, and testing the program.
2. A program consists of a series of instructions and fixed data to perform required operations. The program development cycle involves problem analysis, design, coding, compilation and execution, debugging and testing, and documentation.
3. An algorithm is a finite sequence of steps to solve a problem. Flowcharts use graphical symbols to represent the steps of an algorithm and show the program logic through connections between these symbols.
This document introduces algorithms and their characteristics. It discusses the two phases of programming as problem solving and implementation. It covers understanding the problem, designing the algorithm, proving correctness, analyzing complexity, and coding the algorithm. Common algorithm design techniques like divide-and-conquer, greedy methods, and dynamic programming are presented. The document also discusses representing algorithms in pseudocode and natural language, and analyzing worst-case, average-case, and best-case complexity.
The document provides information on problem solving techniques using algorithms and pseudocode. It discusses key terms, the software development method of problem solving, and basic algorithm control structures like sequence, selection and repetition. It also covers developing algorithms, using pseudocode to represent algorithms, variables, control structures like if-then-else statements and looping constructs. Examples are provided to demonstrate how to represent problems algorithmically using pseudocode and how to develop and test algorithms using a desk checking table.
Programming involves developing programs by specifying computational steps in a programming language. An algorithm is a logical list of steps to solve a problem. Developing good algorithms involves specifying clear input/output, variables, and ensuring the algorithm terminates in a finite number of steps. Flowcharts provide a pictorial representation of algorithm steps and are useful for explaining programs. A computer program consists of instructions provided to the computer to solve a problem.
The document discusses approaches to increasing productivity and quality in software testing through test automation and the use of domain-specific languages (DSLs). It provides two examples of how DSLs can be used to automate testing: one for placing and canceling orders in an e-commerce application, and one for inventory management. The conclusion is that DSLs allow for higher abstraction and better productivity in writing test scripts compared to traditional keyword-driven testing.
The document discusses problem solving using computers. It explains that programming languages allow problems to be solved repeatedly by telling the computer the logic or algorithm to follow. An algorithm is a series of steps, like pseudocode or a flowchart, that represent the procedure for solving a problem. It then provides examples of algorithms for calculating the factorial of a number in different formats, including English steps, flowcharts, and pseudocode. Programming implements the algorithm by translating it line-by-line into source code.
Assignment # 3 computer system and Programming EC-105 NUST Stuff
This 3 sentence summary provides the key details about the document:
The document provides instructions for assignment 3 which is to be completed individually and submitted by January 31st 2017, it includes 3 questions - to write functions for printing an array recursively in reverse order, sorting rows and columns of a 2D 5x5 array, and returning a 1D array of averages of rows in a 2D 5x5 array using pointers. Copying code or plagiarizing will result in a zero mark.
The document outlines the three main stages of developing a C program: 1) Program design which includes problem analysis, outlining structure, algorithm development, and selecting control structures. 2) Program coding which should be readable and avoid complex logic. 3) Program testing which has two stages - human testing like code inspections, and computer-based testing using compilers and detecting run-time errors. The design stage establishes a foundation and strategy for writing the program to solve the problem. Coding then implements the design, and testing identifies any errors before the final program.
Cleanroom Software Engineering By NADEEM AHMED FROM DEPALPURNA000000
Cleanroom is a software development approach that emphasizes defect prevention over testing. It uses formal methods and statistical testing to develop reliable software in increments. Each increment undergoes requirements analysis, formal design, correctness verification, test planning and statistical testing before being certified and integrated into the overall system. This allows many components to be worked on concurrently, improving productivity while avoiding defects.
Programming aids- Algorithm, Flowchart, Pseudocodes and Decision tableAnjali Technosoft
The document discusses algorithms and different ways to represent them, including through flowcharts, pseudocode, and decision tables. It provides examples of each representation type and explains the key components and steps in constructing a flowchart, pseudocode, and decision table to model an algorithm for determining a student's final grade.
The document discusses algorithms, defining them as logical sequences of steps to solve problems and listing properties of good algorithms such as being simple, complete, correct, and having appropriate abstraction. It also provides examples of algorithms and outlines steps for developing algorithms, including analyzing the problem, designing a solution, implementing the program, testing it, and validating it works for all cases.
Lecture Note-2: Performance analysis of AlgorithmsRajesh K Shukla
The execution of an algorithm requires various resources of the computer system to complete the task. The
performance of algorithms depends on the use of these resources. The important resources which contribute
to the efficiency of the algorithms are the memory space and the time required for successful execution of
algorithm. The efficiency of an algorithm is measured in terms of the time and the space required for its
execution therefore analysis of algorithms is divided into two categories
This document discusses programming fundamentals and problem solving using computers. It outlines the steps of defining a problem, designing a solution, and implementing that solution using a programming language. It provides examples of defining problems, designing graphical solutions, and translating those designs into code. Common problems are presented like finding sums, averages, and calculating other values. Computers are useful for solving problems that are too complex, time-consuming, or require extensive inputs or outputs for manual solution.
Detail about cyclomatic complexity, formula to measure cyclomatic complexity and how this metric useful in software testing and uses of cyclomatic complexity etc.
This document provides an overview of problem solving using computers. It discusses the 7 stages of problem solving: 1) problem analysis, 2) algorithm development, 3) flowcharting, 4) coding, 5) compilation and execution, 6) debugging and testing, and 7) documentation. It also covers computer programs, programming languages, and the basic structure of a C program, which typically includes documentation, include libraries, definitions, global declarations, the main function, and subprograms.
Software design involves deriving solutions that satisfy software requirements. The design process involves understanding the problem, identifying solutions, and describing solution abstractions at different levels. Design takes place through overlapping phases like architectural design, interface design, and component design. Good design principles include having linguistic modular units, few interfaces, small interfaces, explicit interfaces, and information hiding. This achieves cohesion within modules and loose coupling between modules.
This document discusses software design principles and processes. It describes key stages of design like problem understanding, identifying solutions, and describing solution abstractions. The design process involves phases like architectural design, interface design, and algorithm design. Good design principles include having linguistic modular units, few interfaces with loose coupling between modules, explicit interfaces, and information hiding. Top-down design and stepwise refinement are common design methods. Cohesion and coupling are important attributes of modular design.
The document discusses algorithms and flowcharts. It defines an algorithm as a step-by-step procedure to solve a problem and get a desired output. Common algorithm categories include search, sort, insert, update, and delete operations on data structures. Flowcharts provide a graphical representation of an algorithm's steps and logic. The document presents examples of an algorithm to add two numbers and the benefits of algorithms and flowcharts, such as effective problem analysis, proper documentation, and efficient coding and debugging. It also notes potential disadvantages like complexity when logic is complicated and the need to redraw flowcharts during alterations.
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.
This document discusses algorithms and flowcharts. It defines an algorithm as a step-by-step method for solving a problem with characteristics like being precise, finite, and applying to a set of inputs. A flowchart is then introduced as a graphical representation of an algorithm that is helpful for understanding and documenting complex programs. The document provides examples of standard flowchart symbols and guidelines for creating effective flowcharts, such as having a logical start and finish with one flow line entering and leaving symbols. An example algorithm and flowchart are given for finding the average of two numbers by inputting the values, adding them, dividing the sum by two, and outputting the average.
This document discusses fundamentals of algorithms including:
- What algorithms are and their evolution from Persian mathematicians.
- The process of designing algorithms including defining inputs, outputs, and order of instructions.
- The need for algorithms to be correct according to their specifications and methods for confirming correctness.
- Iterative design issues such as use of loops, efficiency considerations, and estimating execution time.
- Algorithmic strategies like divide and conquer, backtracking, dynamic programming, and heuristics.
Problem Solving Techniques and Introduction to CPrabu U
This document provides an overview of problem solving techniques, programs, and the program development cycle. It discusses:
1. The steps of problem solving techniques include defining the problem, formulating a mathematical model, developing an algorithm using a flowchart or pseudocode, writing code, and testing the program.
2. A program consists of a series of instructions and fixed data to perform required operations. The program development cycle involves problem analysis, design, coding, compilation and execution, debugging and testing, and documentation.
3. An algorithm is a finite sequence of steps to solve a problem. Flowcharts use graphical symbols to represent the steps of an algorithm and show the program logic through connections between these symbols.
This document introduces algorithms and their characteristics. It discusses the two phases of programming as problem solving and implementation. It covers understanding the problem, designing the algorithm, proving correctness, analyzing complexity, and coding the algorithm. Common algorithm design techniques like divide-and-conquer, greedy methods, and dynamic programming are presented. The document also discusses representing algorithms in pseudocode and natural language, and analyzing worst-case, average-case, and best-case complexity.
The document provides information on problem solving techniques using algorithms and pseudocode. It discusses key terms, the software development method of problem solving, and basic algorithm control structures like sequence, selection and repetition. It also covers developing algorithms, using pseudocode to represent algorithms, variables, control structures like if-then-else statements and looping constructs. Examples are provided to demonstrate how to represent problems algorithmically using pseudocode and how to develop and test algorithms using a desk checking table.
Programming involves developing programs by specifying computational steps in a programming language. An algorithm is a logical list of steps to solve a problem. Developing good algorithms involves specifying clear input/output, variables, and ensuring the algorithm terminates in a finite number of steps. Flowcharts provide a pictorial representation of algorithm steps and are useful for explaining programs. A computer program consists of instructions provided to the computer to solve a problem.
The document discusses approaches to increasing productivity and quality in software testing through test automation and the use of domain-specific languages (DSLs). It provides two examples of how DSLs can be used to automate testing: one for placing and canceling orders in an e-commerce application, and one for inventory management. The conclusion is that DSLs allow for higher abstraction and better productivity in writing test scripts compared to traditional keyword-driven testing.
The document discusses problem solving using computers. It explains that programming languages allow problems to be solved repeatedly by telling the computer the logic or algorithm to follow. An algorithm is a series of steps, like pseudocode or a flowchart, that represent the procedure for solving a problem. It then provides examples of algorithms for calculating the factorial of a number in different formats, including English steps, flowcharts, and pseudocode. Programming implements the algorithm by translating it line-by-line into source code.
Assignment # 3 computer system and Programming EC-105 NUST Stuff
This 3 sentence summary provides the key details about the document:
The document provides instructions for assignment 3 which is to be completed individually and submitted by January 31st 2017, it includes 3 questions - to write functions for printing an array recursively in reverse order, sorting rows and columns of a 2D 5x5 array, and returning a 1D array of averages of rows in a 2D 5x5 array using pointers. Copying code or plagiarizing will result in a zero mark.
The document outlines the three main stages of developing a C program: 1) Program design which includes problem analysis, outlining structure, algorithm development, and selecting control structures. 2) Program coding which should be readable and avoid complex logic. 3) Program testing which has two stages - human testing like code inspections, and computer-based testing using compilers and detecting run-time errors. The design stage establishes a foundation and strategy for writing the program to solve the problem. Coding then implements the design, and testing identifies any errors before the final program.
Cleanroom Software Engineering By NADEEM AHMED FROM DEPALPURNA000000
Cleanroom is a software development approach that emphasizes defect prevention over testing. It uses formal methods and statistical testing to develop reliable software in increments. Each increment undergoes requirements analysis, formal design, correctness verification, test planning and statistical testing before being certified and integrated into the overall system. This allows many components to be worked on concurrently, improving productivity while avoiding defects.
Programming aids- Algorithm, Flowchart, Pseudocodes and Decision tableAnjali Technosoft
The document discusses algorithms and different ways to represent them, including through flowcharts, pseudocode, and decision tables. It provides examples of each representation type and explains the key components and steps in constructing a flowchart, pseudocode, and decision table to model an algorithm for determining a student's final grade.
The document discusses algorithms, defining them as logical sequences of steps to solve problems and listing properties of good algorithms such as being simple, complete, correct, and having appropriate abstraction. It also provides examples of algorithms and outlines steps for developing algorithms, including analyzing the problem, designing a solution, implementing the program, testing it, and validating it works for all cases.
Lecture Note-2: Performance analysis of AlgorithmsRajesh K Shukla
The execution of an algorithm requires various resources of the computer system to complete the task. The
performance of algorithms depends on the use of these resources. The important resources which contribute
to the efficiency of the algorithms are the memory space and the time required for successful execution of
algorithm. The efficiency of an algorithm is measured in terms of the time and the space required for its
execution therefore analysis of algorithms is divided into two categories
This document discusses programming fundamentals and problem solving using computers. It outlines the steps of defining a problem, designing a solution, and implementing that solution using a programming language. It provides examples of defining problems, designing graphical solutions, and translating those designs into code. Common problems are presented like finding sums, averages, and calculating other values. Computers are useful for solving problems that are too complex, time-consuming, or require extensive inputs or outputs for manual solution.
Detail about cyclomatic complexity, formula to measure cyclomatic complexity and how this metric useful in software testing and uses of cyclomatic complexity etc.
This document provides an overview of problem solving using computers. It discusses the 7 stages of problem solving: 1) problem analysis, 2) algorithm development, 3) flowcharting, 4) coding, 5) compilation and execution, 6) debugging and testing, and 7) documentation. It also covers computer programs, programming languages, and the basic structure of a C program, which typically includes documentation, include libraries, definitions, global declarations, the main function, and subprograms.
Software design involves deriving solutions that satisfy software requirements. The design process involves understanding the problem, identifying solutions, and describing solution abstractions at different levels. Design takes place through overlapping phases like architectural design, interface design, and component design. Good design principles include having linguistic modular units, few interfaces, small interfaces, explicit interfaces, and information hiding. This achieves cohesion within modules and loose coupling between modules.
This document discusses software design principles and processes. It describes key stages of design like problem understanding, identifying solutions, and describing solution abstractions. The design process involves phases like architectural design, interface design, and algorithm design. Good design principles include having linguistic modular units, few interfaces with loose coupling between modules, explicit interfaces, and information hiding. Top-down design and stepwise refinement are common design methods. Cohesion and coupling are important attributes of modular design.
The document discusses software design and the software design process. It covers stages of design like problem understanding, identifying solutions, and describing solution abstractions. It also discusses phases in the design process like architectural design, abstract specification, interface design, component design, data structure design, and algorithm design. The document outlines principles for good design like linguistic modular units, few interfaces, small interfaces, explicit interfaces, and information hiding. It discusses concepts like coupling, cohesion, and stepwise refinement in software design.
The document discusses problem-solving and design skills needed for computer programming. It covers several key topics:
1. Candidates should understand top-down design and be able to break down computer systems into subsystems using structure diagrams, flowcharts, pseudocode, and subroutines.
2. Candidates should be able to work with algorithms - explaining them, suggesting test data, and identifying/fixing errors. They should be able to produce algorithms for problems.
3. Top-down design is described as the process of breaking down a computer system into subsystems, then breaking each subsystem into smaller subsystems, until each performs a single action.
The document provides an introduction to computer programming. It discusses what a computer is and its basic parts including hardware and software. It describes the internal and external hardware components. It also explains different types of programming languages from low-level to high-level languages. The document then discusses programming paradigms like procedural, structured, and object-oriented programming. It introduces concepts like algorithms, flowcharts, and the system development life cycle which involves phases from feasibility study to implementation and maintenance.
This calculator has been developed by me. It gives high precision results which
Normal calculator can not give. It is helpful in calculations for Space technology,
Supercomputers, Nano technology etc. I can give this calculator to interested people.
This document provides an overview of a course on multicore architecture. It discusses the transition to multicore processors and the need for parallel programming. It covers threading fundamentals like threads, parallel programming APIs, and performance measurement using Amdahl's law and Gustafson's law. The course content is organized into sections on threading basics, common programming interfaces, and solving parallel programming problems. Suggested textbooks are also listed.
The document discusses software development life cycle (SDLC) and the various steps involved including requirements analysis, design, coding, testing, and maintenance. It also discusses different types of errors that can occur during software development such as unexpected input values and changes that affect software operations. It then discusses the input-process-output (IPO) cycle and how it relates to batch processing systems and online processing systems. For batch systems, the input data is collected in batches and processed as batches, with no user interaction during processing. For online systems, the user can interact with the system as transactions are processed immediately.
The document provides an overview of the syllabus for a Python programming course. It covers conceptual introductions to topics in computer science and algorithms. It also covers modern computer systems including hardware architecture, data representation, software, and operating systems. The course will teach students how to install Python and cover basic syntax, data types, variables, arithmetic operators, and understanding errors.
Scripting experts from Inductive Automation cover general best practices that will help you add flexibility and customization to HMI, SCADA, IIoT, and other industrial applications. Some specific tips about using scripting in the Ignition platform will be included as well.
In this webinar, learn more about:
• Common scripting pitfalls and how to avoid them
• The best programming languages to use
• Things to consider before using scripting
• How scripting environments work
• Scripting timesavers
• And more
Examines some of the fundamental problems with the way the industry thinks about software "engineering", and breaks some notions in order to find useful ways of improving your code quality, and your skills and discipline as a developer.
This document summarizes a presentation by Dr. S. Ducasse on dedicated tools and research for software business intelligence at Tisoca 2014. It discusses:
- The need for dedicated tools tailored to specific problems to aid in maintenance, decision making, and reducing costs.
- The Moose technology for building custom analysis tools through its language-independent meta-model and ability to import different data sources.
- Examples of how analysis tools built with Moose have helped companies with challenges like migration, reverse engineering, and decision support.
- The benefits of an inventive toolkit approach that allows building multi-level dashboards, code analyzers, impact analyzers, and other custom tools to address specific
The document provides an overview of problem solving and C programming at a basic knowledge level. It covers various topics including introduction to problem solving, programming languages, introduction to C programming, selection structures, arrays and strings, pointers, functions, structures and unions, and files. The objective is to understand problem solving concepts, appreciate program design, understand C programming elements, and write effective C programs. It discusses steps in program development, algorithms, modular design, coding, documentation, compilation and more.
Scripting experts from Inductive Automation cover general best practices that will help you add flexibility and customization to HMI, SCADA, IIoT, and other industrial applications. Some specific tips about using scripting in the Ignition platform will be included as well.
In this webinar, learn more about:
• Common scripting pitfalls and how to avoid them
• The best programming languages to use
• Things to consider before using scripting
• How scripting environments work
• Scripting timesavers
• And more
The document summarizes a lecture on algorithms and algorithm design from a course on algorithms. It introduces the concept of algorithms and what will be covered in the course, which includes analyzing algorithms, sorting techniques as a case study, and various algorithmic problems and solutions. It also discusses implementation issues and keeping mathematical analysis independent of specific programming languages or machines. As an example, it analyzes the brute force algorithm for solving the 2D maxima problem in pseudo-code and calculates its running time.
Have you ever wondered how to speed up your code in Python? This presentation will show you how to start. I will begin with a guide how to locate performance bottlenecks and then give you some tips how to speed up your code. Also I would like to discuss how to avoid premature optimization as it may be ‘the root of all evil’ (at least according to D. Knuth).
The document provides information about computing homework questions covering several topics:
- Binary number systems and conversions between binary and decimal
- Floating point numbers and how changing mantissa and exponent sizes affects values
- ASCII encoding and Unicode methods
- Bitmapped and vector graphics
- Computer system components and memory types
- CPU architecture and bus functions
- Benchmark tests and factors affecting computer performance
- Networking concepts like LANs, WANs, servers, and topologies
- Operating systems, file formats, and antivirus software
- The software development process and documentation
Secret Twists to Efficiently Develop Reactive Software SystemsBart Jonkers
A successful software design for reactive software systems follows the three design principles:
■ Divide and conquer, then reuse effectively
■ Visualize your system
■ Automatically and formally verify everything, always
These principles are easy in theory. With traditional programming, however, it is extremely challenging to master them.
Reactive blocks, on the other hand, are a new type of software modules that make the three design principles a natural part of the design process.I
n this whitepaper, we present the secret twists to make these principles work for you and your organization.
This document discusses software engineering and requirements engineering. It defines software engineering as using techniques, methodologies and tools to produce high quality software within budget and deadline constraints. It describes requirements engineering as identifying functional, non-functional and pseudo requirements to develop software. Key activities in requirements engineering include domain analysis, defining the problem scope, and determining what constitutes a requirement.
IGCSE & O Level Computer Workbook for P2 by Inqilab PatelInqilab Patel
This document provides information on problem-solving and design in computer science. It discusses top-down design, structure diagrams, flowcharts, pseudocode, library routines, and subroutines. It also covers test data including normal data, abnormal data, extreme data, and rogue values. Validation and verification methods such as range checks, length checks, type checks, and check digits are explained. Examples of these concepts are given throughout the document.
Best Digital Marketing Strategy Build Your Online Presence 2024.pptxpavankumarpayexelsol
This presentation provides a comprehensive guide to the best digital marketing strategies for 2024, focusing on enhancing your online presence. Key topics include understanding and targeting your audience, building a user-friendly and mobile-responsive website, leveraging the power of social media platforms, optimizing content for search engines, and using email marketing to foster direct engagement. By adopting these strategies, you can increase brand visibility, drive traffic, generate leads, and ultimately boost sales, ensuring your business thrives in the competitive digital landscape.
Practical eLearning Makeovers for EveryoneBianca Woods
Welcome to Practical eLearning Makeovers for Everyone. In this presentation, we’ll take a look at a bunch of easy-to-use visual design tips and tricks. And we’ll do this by using them to spruce up some eLearning screens that are in dire need of a new look.
International Upcycling Research Network advisory board meeting 4Kyungeun Sung
Slides used for the International Upcycling Research Network advisory board 4 (last one). The project is based at De Montfort University in Leicester, UK, and funded by the Arts and Humanities Research Council.
1. Problem #1
●
➔
➔
Assume that you are building a source code transformation toolkit.
The toolkit will contain components that can be configured to
perform specific sets of code transformations on source code. There
are 3 categories of components: parsers (e.g., for C, Ada, COBOL)
that can read in source code and produce internal program
representation, transformers (code formatters, code optimizers, etc.)
that work on the internal program representation, and pretty-printers
that can transform the internal program implementation back into
source code. Assume that the toolkit should be easily extensible with
new components and that the components can work incrementally on
streams of source code or internal representation. The user will work
with the configurations in a batch mode rather than interactively.
What architectural style would be most appropriate for this toolkit?
Why?
Give a sketch of the toolkit architecture.
2. Problem #1 Solution
●
A data-flow system. Data controls computation.
●
Pipes & Filters
●
Parsers, transformers and pretty-printers work on data
streams in an incremental fashion. Consume & produce.
●
Extensibility
●
Batch mode rather than interactive
3. Problem #2
●
Assume that you are building a television controller which
responds to signals from remote control unit.
➔
Which architectural style is most appropriate for the given system?
➔
Give a sketch of a sample architecture for each system.
➔
Discuss the reason for selecting a given style for each system.
4. Problem #2 Solution
●
A control-loop system: process input in a continuous
loop
●
Select the handler based on input
●
State-machine maybe used for complex input/output
–
●
E.g. Button sequence on input (receiver) side or signal
sequence on output (actuator) side
Event-driven architectural style possible as well
5. Problem #3
●
Assume that you are building a voice recognition system (assume
that the system has to perform segmentation into phonems, syllable
creation, word creation, and dictionary lookup; assume that these
tasks cooperate on the recognition problem and there is no simple
algorithmic order for performing these tasks; also, the system
should be easy to extend with new algorithms).
➔
Which architectural style is most appropriate for the given system?
➔
Give a sketch of a sample architecture for each system.
➔
Discuss the reason for selecting a given style for each system.
6. Problem #3 Solution
●
Blackboard architecture.
●
No algorithmic order + cooperative work required.
●
New components register with the blackboard for events.
●
Processes solve partial solutions. Solutions are stored in the
blackboard.
7. Problem #4
●
Assume that you are building an e-commerce system handling high
volumes of transactions per day from on-line customers.
➔
Which architectural style is most appropriate for the given system?
➔
Give a sketch of a sample architecture for each system.
➔
Discuss the reason for selecting a given style for each system.
8. Problem #4 Solution
●
Multi-tier architecture.
●
Middle tier (business logic) allows for scalability.
●
Database layer easy to scale.
●
Clients easy to update.
9. Problem #5
●
Assume that you are building a development environment capable
of integrating a set of tools (e.g., compiler, editor, debugger, etc.)
produced by different vendors.
➔
Which architectural style is most appropriate for the given system?
➔
Give a sketch of a sample architecture for each system.
➔
Discuss the reason for selecting a given style for each system.
10. Problem #5 Solution
●
Implicit invocation.
●
Full decoupling between sender and receiver
–
–
●
Reuse,
Maintenance.
New tools can subscribe.
11. Problem #6
●
Assume that you are building a software performing call
processing for telecom switching equipment.
➔
Which architectural style is most appropriate for the given system?
➔
Give a sketch of a sample architecture for each system.
➔
Discuss the reason for selecting a given style for each system.