MYCIN was an early expert system developed at Stanford University in 1972 to assist physicians in diagnosing and selecting treatment for bacterial and blood infections. It used over 600 production rules encoding the clinical decision criteria of infectious disease experts to diagnose patients based on reported symptoms and test results. While it could not replace human diagnosis due to computing limitations at the time, MYCIN demonstrated that expert knowledge could be represented computationally and established a foundation for more advanced machine learning and knowledge base systems.
Testing metrics provide objective measurements of software quality and the testing process. They measure attributes like test coverage, defect detection rates, and requirement changes. There are base metrics that directly capture raw data like test cases run and results, and calculated metrics that analyze the base metrics, like first run failure rates and defect slippage. Tracking these metrics throughout testing provides visibility into project readiness, informs management decisions, and identifies areas for improvement. Regular review and interpretation of the metrics is needed to understand their implications and make changes to the development lifecycle.
Static testing is a software testing method that involves examination of program's code and its associated documentation but does not require the program to be executed.
Static Testing Techniques
Informal Reviews
Formal Reviews
Technical Reviews
Walk Through
Inspection Process
Static Code Review
The document discusses different types of intelligent agents. It defines an agent as something that perceives its environment, acts upon it, and maps perceptions to actions. The document then describes ideal rational agents, different types of agent architectures including table-based, reflex, model-based, goal-based, utility-based, and learning agents. It also covers properties of task environments and how learning agents improve through experience.
Black box testing, equivalence partitioning, equivalence class partition, ECP, Boundary Value Analysis, BVA, ISTQB Foundation level, Manual Testing, Examples for Equivalence Partitioning, Examples for Boundary value analysis
RTM is a tool that helps maintain a project's scope, requirements, and deliverables by tracing each requirement from initiation through final implementation. It enhances scope management and assists with process control and quality management by documenting connections between initial requirements and the final product. An RTM should be created at the beginning of a project and contain unique, clearly defined requirements including an ID, use case ID, use requirement, and testing details to ease control and tracing.
Linux System Administration (November – 2018) [Choice Based | Question Paper]Mumbai B.Sc.IT Study
This document contains questions for an exam on Linux System Administration. It covers topics such as piping and redirecting commands, the duties of a Linux system administrator, find commands, process management commands, hard and symbolic links, RPM and YUM, Linux partitions, file systems, runlevels and services, enabling SSH, managing users and groups, firewalls, iptables tables and rules, encrypting and decrypting files, NFS, Samba file servers, DNS hierarchy, dhcp.conf parameters, MTA and MDA, Apache configuration, virtual hosts, shell script elements, script to create a directory, high-availability clusters, bonding devices, TFTP servers, and Kickstart files. The exam expects students to answer 15 marks
MYCIN was an early expert system developed at Stanford University in 1972 to assist physicians in diagnosing and selecting treatment for bacterial and blood infections. It used over 600 production rules encoding the clinical decision criteria of infectious disease experts to diagnose patients based on reported symptoms and test results. While it could not replace human diagnosis due to computing limitations at the time, MYCIN demonstrated that expert knowledge could be represented computationally and established a foundation for more advanced machine learning and knowledge base systems.
Testing metrics provide objective measurements of software quality and the testing process. They measure attributes like test coverage, defect detection rates, and requirement changes. There are base metrics that directly capture raw data like test cases run and results, and calculated metrics that analyze the base metrics, like first run failure rates and defect slippage. Tracking these metrics throughout testing provides visibility into project readiness, informs management decisions, and identifies areas for improvement. Regular review and interpretation of the metrics is needed to understand their implications and make changes to the development lifecycle.
Static testing is a software testing method that involves examination of program's code and its associated documentation but does not require the program to be executed.
Static Testing Techniques
Informal Reviews
Formal Reviews
Technical Reviews
Walk Through
Inspection Process
Static Code Review
The document discusses different types of intelligent agents. It defines an agent as something that perceives its environment, acts upon it, and maps perceptions to actions. The document then describes ideal rational agents, different types of agent architectures including table-based, reflex, model-based, goal-based, utility-based, and learning agents. It also covers properties of task environments and how learning agents improve through experience.
Black box testing, equivalence partitioning, equivalence class partition, ECP, Boundary Value Analysis, BVA, ISTQB Foundation level, Manual Testing, Examples for Equivalence Partitioning, Examples for Boundary value analysis
RTM is a tool that helps maintain a project's scope, requirements, and deliverables by tracing each requirement from initiation through final implementation. It enhances scope management and assists with process control and quality management by documenting connections between initial requirements and the final product. An RTM should be created at the beginning of a project and contain unique, clearly defined requirements including an ID, use case ID, use requirement, and testing details to ease control and tracing.
Linux System Administration (November – 2018) [Choice Based | Question Paper]Mumbai B.Sc.IT Study
This document contains questions for an exam on Linux System Administration. It covers topics such as piping and redirecting commands, the duties of a Linux system administrator, find commands, process management commands, hard and symbolic links, RPM and YUM, Linux partitions, file systems, runlevels and services, enabling SSH, managing users and groups, firewalls, iptables tables and rules, encrypting and decrypting files, NFS, Samba file servers, DNS hierarchy, dhcp.conf parameters, MTA and MDA, Apache configuration, virtual hosts, shell script elements, script to create a directory, high-availability clusters, bonding devices, TFTP servers, and Kickstart files. The exam expects students to answer 15 marks
Best Python Libraries For Data Science & Machine Learning | EdurekaEdureka!
This document provides an overview of popular Python libraries for data science and machine learning tasks. It discusses libraries for statistical analysis (NumPy, SciPy, Pandas, StatsModels), data visualization (Matplotlib, Seaborn, Plotly, Bokeh), machine learning (Scikit-learn, XGBoost, Eli5), deep learning (TensorFlow, Keras, Pytorch), and natural language processing (NLTK, SpaCy, Gensim). For each category, it lists the top libraries and briefly describes their main functionalities. The document serves as an introduction to the Python data science ecosystem.
Stuart russell and peter norvig artificial intelligence - a modern approach...Lê Anh Đạt
This document provides publishing information for the book "Artificial Intelligence: A Modern Approach". It lists the editorial staff and production team, including the Vice President and Editorial Director, Editor-in-Chief, Executive Editor, and others. It also provides copyright information, acknowledging that the content is protected and requires permission for reproduction. Finally, it is dedicated to the authors' families and includes a preface giving an overview of the book.
Token, Pattern and Lexeme defines some key concepts in lexical analysis:
Tokens are valid sequences of characters that can be identified as keywords, constants, identifiers, numbers, operators or punctuation. A lexeme is the sequence of characters that matches a token pattern. Patterns are defined by regular expressions or grammar rules to identify lexemes as specific tokens. The lexical analyzer collects attributes like values for number tokens and symbol table entries for identifiers and passes the tokens and attributes to the parser. Lexical errors occur if a character sequence cannot be scanned as a valid token. Error recovery strategies include deleting or inserting characters to allow tokenization to continue.
This document discusses various software testing metrics including defect density, requirement volatility, test execution productivity, and test efficiency. Defect density measures the number of defects found divided by the size of the software. Requirement volatility measures the percentage of original requirements that were changed. Test execution productivity measures the number of test cases executed per day. Test efficiency measures the percentage of defects found during testing versus post-release. These metrics provide ways to measure software quality and testing effectiveness.
This document discusses intelligent agents and rational behavior. It defines an agent as anything that can perceive its environment and act upon it, using sensors and actuators. An agent's behavior is described by its agent function, which maps percepts to actions. A rational agent is one that does the right thing and selects actions expected to maximize its performance based on its percepts and prior knowledge. For a rational agent, its rationality depends on the performance measure, its prior knowledge, available actions, and percept sequence.
The document discusses the benefits of exercise for mental health. Regular physical activity can help reduce anxiety and depression and improve mood and cognitive functioning. Exercise boosts blood flow and levels of neurotransmitters and endorphins which elevate and stabilize mood.
The document discusses the evolution of software economics and cost estimation models over three generations:
1) Conventional (1960s-1970s) used custom tools/processes and languages with underachieved goals
2) Transition (1980s-1990s) used more repeatable processes/tools and higher languages with some commercial products
3) Modern practices (2000-present) use managed processes, integrated environments and mostly commercial products.
It also examines debates on cost estimation, noting COCOMO is well-documented but data is inconsistent. A good estimate is based on a credible model, relevant experience, and well-defined risks.
Testbytes is a community of software testers who are passionate about quality and love to test. We develop an in-depth understanding of the applications under test and include software testing strategies that deliver quantifiable results.
In short, we help in building incredible software.
Python programming using problem solving approach by thareja, reema (z lib.org)arshpreetkaur07
The document discusses the history and evolution of the English language from its origins as Anglo-Frisian dialects brought to Britain by Anglo-Saxon settlers in the 5th century AD. It details how Old English emerged as the dominant language by the 7th century and later transformed into Middle English after the Norman conquest of 1066, absorbing elements from Old Norse and Norman French. The modern English language began emerging in the 15th century.
Machine-Independent Optimizations: The Principal Sources of Optimization, Introduction to Data-Flow Analysis, Foundations of Data-Flow Analysis, Constant Propagation, Partial Redundancy Elimination, Loops in Flow Graphs
This document discusses software metrics that can be used to measure process and project attributes. It defines key terms like measurement, measure, metric and indicator. It describes different types of metrics like process metrics, project metrics, size-oriented metrics, function-oriented metrics and quality metrics. It also discusses concepts like defect removal efficiency and redefining defect removal efficiency to measure effectiveness of quality assurance activities.
The document discusses various compiler optimizations including:
1. Procedure integration replaces procedure calls with the procedure body to eliminate function call overhead.
2. Common subexpression elimination replaces repeated computations of the same expression with a single variable to store the result.
3. Constant propagation replaces variables assigned a constant value with the constant throughout the code.
4. The document provides examples of these and other optimizations like copy propagation, code motion, induction variable elimination, and loop unrolling which aims to improve performance by reducing instructions and improving pipeline utilization.
This document discusses using Google Colab for Python programming. It explains that Google Colab allows for collaboration and runs code on Google servers without needing to install anything. Notebooks are saved to the user's Google Drive account. The document then provides steps for creating folders and notebooks in Google Drive, setting the runtime to use GPU hardware acceleration, opening notebooks from Drive or by URL, running basic and imported Python code, and cloning GitHub repositories in Colab.
Adversarial search is a technique used in game playing to determine the best move when facing an opponent who is also trying to maximize their score. It involves searching through possible future game states called a game tree to evaluate the best outcome. The minimax algorithm searches the entire game tree to determine the optimal move by assuming the opponent will make the best counter-move. Alpha-beta pruning improves on minimax by pruning branches that cannot affect the choice of move. Modern game programs use techniques like precomputed databases, sophisticated evaluation functions, and extensive search to defeat human champions at games like checkers, chess, and Othello.
The document discusses regression testing, which involves re-testing software after changes to ensure existing functionality still works properly and new changes do not cause unintended issues. It describes the types of regression testing as regular, done between test cycles, and final, done before release. It outlines best practices for regression testing like classifying test cases by priority and selecting relevant ones based on changes. The document provides guidance on resetting test cases, executing the regression tests, and concluding the results.
This document provides an overview of a lecture on designing and analyzing computer algorithms. It discusses key concepts like what an algorithm and program are, common algorithm design techniques like divide-and-conquer and greedy methods, and how to analyze algorithms' time and space complexity. The goals of analyzing algorithms are to understand their behavior, improve efficiency, and determine whether problems can be solved within a reasonable time frame.
This document discusses various problem solving techniques through search. It begins with an introduction to problem representation, problem solving through search, and examples like the 8-puzzle and missionaries and cannibals problem. It then covers search methods and algorithms like breadth-first search, depth-first search, and A* search. Key concepts discussed include problem states, operators, initial states, goals, and search strategies. Real-world problems are abstracted and represented as states, operators, and paths for solving through search techniques.
Best Python Libraries For Data Science & Machine Learning | EdurekaEdureka!
This document provides an overview of popular Python libraries for data science and machine learning tasks. It discusses libraries for statistical analysis (NumPy, SciPy, Pandas, StatsModels), data visualization (Matplotlib, Seaborn, Plotly, Bokeh), machine learning (Scikit-learn, XGBoost, Eli5), deep learning (TensorFlow, Keras, Pytorch), and natural language processing (NLTK, SpaCy, Gensim). For each category, it lists the top libraries and briefly describes their main functionalities. The document serves as an introduction to the Python data science ecosystem.
Stuart russell and peter norvig artificial intelligence - a modern approach...Lê Anh Đạt
This document provides publishing information for the book "Artificial Intelligence: A Modern Approach". It lists the editorial staff and production team, including the Vice President and Editorial Director, Editor-in-Chief, Executive Editor, and others. It also provides copyright information, acknowledging that the content is protected and requires permission for reproduction. Finally, it is dedicated to the authors' families and includes a preface giving an overview of the book.
Token, Pattern and Lexeme defines some key concepts in lexical analysis:
Tokens are valid sequences of characters that can be identified as keywords, constants, identifiers, numbers, operators or punctuation. A lexeme is the sequence of characters that matches a token pattern. Patterns are defined by regular expressions or grammar rules to identify lexemes as specific tokens. The lexical analyzer collects attributes like values for number tokens and symbol table entries for identifiers and passes the tokens and attributes to the parser. Lexical errors occur if a character sequence cannot be scanned as a valid token. Error recovery strategies include deleting or inserting characters to allow tokenization to continue.
This document discusses various software testing metrics including defect density, requirement volatility, test execution productivity, and test efficiency. Defect density measures the number of defects found divided by the size of the software. Requirement volatility measures the percentage of original requirements that were changed. Test execution productivity measures the number of test cases executed per day. Test efficiency measures the percentage of defects found during testing versus post-release. These metrics provide ways to measure software quality and testing effectiveness.
This document discusses intelligent agents and rational behavior. It defines an agent as anything that can perceive its environment and act upon it, using sensors and actuators. An agent's behavior is described by its agent function, which maps percepts to actions. A rational agent is one that does the right thing and selects actions expected to maximize its performance based on its percepts and prior knowledge. For a rational agent, its rationality depends on the performance measure, its prior knowledge, available actions, and percept sequence.
The document discusses the benefits of exercise for mental health. Regular physical activity can help reduce anxiety and depression and improve mood and cognitive functioning. Exercise boosts blood flow and levels of neurotransmitters and endorphins which elevate and stabilize mood.
The document discusses the evolution of software economics and cost estimation models over three generations:
1) Conventional (1960s-1970s) used custom tools/processes and languages with underachieved goals
2) Transition (1980s-1990s) used more repeatable processes/tools and higher languages with some commercial products
3) Modern practices (2000-present) use managed processes, integrated environments and mostly commercial products.
It also examines debates on cost estimation, noting COCOMO is well-documented but data is inconsistent. A good estimate is based on a credible model, relevant experience, and well-defined risks.
Testbytes is a community of software testers who are passionate about quality and love to test. We develop an in-depth understanding of the applications under test and include software testing strategies that deliver quantifiable results.
In short, we help in building incredible software.
Python programming using problem solving approach by thareja, reema (z lib.org)arshpreetkaur07
The document discusses the history and evolution of the English language from its origins as Anglo-Frisian dialects brought to Britain by Anglo-Saxon settlers in the 5th century AD. It details how Old English emerged as the dominant language by the 7th century and later transformed into Middle English after the Norman conquest of 1066, absorbing elements from Old Norse and Norman French. The modern English language began emerging in the 15th century.
Machine-Independent Optimizations: The Principal Sources of Optimization, Introduction to Data-Flow Analysis, Foundations of Data-Flow Analysis, Constant Propagation, Partial Redundancy Elimination, Loops in Flow Graphs
This document discusses software metrics that can be used to measure process and project attributes. It defines key terms like measurement, measure, metric and indicator. It describes different types of metrics like process metrics, project metrics, size-oriented metrics, function-oriented metrics and quality metrics. It also discusses concepts like defect removal efficiency and redefining defect removal efficiency to measure effectiveness of quality assurance activities.
The document discusses various compiler optimizations including:
1. Procedure integration replaces procedure calls with the procedure body to eliminate function call overhead.
2. Common subexpression elimination replaces repeated computations of the same expression with a single variable to store the result.
3. Constant propagation replaces variables assigned a constant value with the constant throughout the code.
4. The document provides examples of these and other optimizations like copy propagation, code motion, induction variable elimination, and loop unrolling which aims to improve performance by reducing instructions and improving pipeline utilization.
This document discusses using Google Colab for Python programming. It explains that Google Colab allows for collaboration and runs code on Google servers without needing to install anything. Notebooks are saved to the user's Google Drive account. The document then provides steps for creating folders and notebooks in Google Drive, setting the runtime to use GPU hardware acceleration, opening notebooks from Drive or by URL, running basic and imported Python code, and cloning GitHub repositories in Colab.
Adversarial search is a technique used in game playing to determine the best move when facing an opponent who is also trying to maximize their score. It involves searching through possible future game states called a game tree to evaluate the best outcome. The minimax algorithm searches the entire game tree to determine the optimal move by assuming the opponent will make the best counter-move. Alpha-beta pruning improves on minimax by pruning branches that cannot affect the choice of move. Modern game programs use techniques like precomputed databases, sophisticated evaluation functions, and extensive search to defeat human champions at games like checkers, chess, and Othello.
The document discusses regression testing, which involves re-testing software after changes to ensure existing functionality still works properly and new changes do not cause unintended issues. It describes the types of regression testing as regular, done between test cycles, and final, done before release. It outlines best practices for regression testing like classifying test cases by priority and selecting relevant ones based on changes. The document provides guidance on resetting test cases, executing the regression tests, and concluding the results.
This document provides an overview of a lecture on designing and analyzing computer algorithms. It discusses key concepts like what an algorithm and program are, common algorithm design techniques like divide-and-conquer and greedy methods, and how to analyze algorithms' time and space complexity. The goals of analyzing algorithms are to understand their behavior, improve efficiency, and determine whether problems can be solved within a reasonable time frame.
This document discusses various problem solving techniques through search. It begins with an introduction to problem representation, problem solving through search, and examples like the 8-puzzle and missionaries and cannibals problem. It then covers search methods and algorithms like breadth-first search, depth-first search, and A* search. Key concepts discussed include problem states, operators, initial states, goals, and search strategies. Real-world problems are abstracted and represented as states, operators, and paths for solving through search techniques.
Penetration Testing con Python - Network SnifferSimone Onofri
Una nota massima dice che "se ascolto dimentico, se vedo ricordo, se faccio capisco", il "fare", come lo scrivere codice e non usare strumenti già pronti è la chiave per essere un buon Penetration Tester. Non è un caso che Chris Miller dice che "la differenza stra uno script kiddies e i professionisti è la mera differenza tra chi usa strumenti di altri o i propri" Ovviamente questo presuppone una profonda conoscenza di quello che si sta facendo - una tecnica di attacco particolare, i protocolli utilizzati, dei sistemi, delle aplicazioni e così via. Quindi scrivere i propri strumenti è un modo di imparare realmente quello che accade sotto al "motore" di altri strumenti e come funzionano gli attacchi. Durante il talk vedremo in particolare i raw socket su linux e come scrivere uno sniffer.
Questi sono i miei appunti di informatica sviluppati durante i lockdown. Di fatto costituiscono il libro di testo dei miei corsi. La grafica è ispirata a D&D 5e nella speranza di accattivarmi l'interesse dei ragazzi.
Questa parte è adatta ai ragazzi di 1-2° liceo SSA e di 2°-3° ITIS (in particolare ad indirizzo informatico)
Slide dell'evento del FabLab Western Sicily del 3 ottobre Coding Class: Da Scratch a Python.
Introduzione alle basi del pensiero computazionale ed esempi in Scratch che in Python.
Slide della lezione 2 del corso di Python tenuto per gli studenti del Collegio Don Nicola Mazza di Padova in data 6 Aprile 2020. Argomenti trattati: script, IDLE, espressioni booleane, controllo del flusso, cicli, funzioni, classi, file
Il seguente corso intende fornire le competenze di base per insegnare a programmare in modo creativo e mostrare come l’insegnamento dell’informatica possa diventare una strategia per insegnare a progettare il proprio apprendimento e risolvere problemi.
Il corso è un’introduzione alla programmazione con Scratch e le slide della prima lezione sono un’espansione di quanto già implementato con: Micro Corso di Scratch”.
Questa lezione, con le successive che verranno pubblicate, potranno essere utilizzate in corsi introduttivi alla programmazione con Scratch.
Chi cerca una parola autorevole ha sbagliato posto. In tutti i campi, ma in particolare nella didattica, siamo tutti alla ricerca di strumenti efficaci. L'efficacia forse è più nella ricerca che negli strumenti.