Mutation testing is a technique that rewrites source code in small ways to remove redundancies. It introduces artificial faults to test whether tests can detect these faults. It benefits developers by bringing new kinds of errors to light that conventional testing may miss. There are three main types of mutations: value mutations change values to test for errors; decision mutations alter conditions to check for design flaws; and statement mutations modify statements through deletion or duplication to simulate copy/paste errors. Mutation testing is a powerful method for detecting hidden defects.
software testing, Regression testing meaning,
requirement of regression testing,
techniques of regression testing:- hybrid, retest all, Test case prioritization, Regression test selection.
pros and cons of using regression testing,
tools for regression testing :-
Relational Functional Tester(RFT)
Quick Test Professional (QTP)
selenium
Software testing metrics | David Tzemach David Tzemach
Overview
What we can measure using metrics
Common metrics to evaluate test process
why do we need to use metrics
Test metrics life cycle (TMLC)
Type of metrics
Fundamental testing metrics
Software Test Metrics and MeasurementsDavis Thomas
Explains in detail with example about calculation of -
1.Percentage Test cases Executed [Test Coverage]
2.Percentage Test cases not executed
3.Percentage Test cases Passed
4.Percentage Test cases Failed
5.Percentage Test cases BLOCKED/Deferred
6.Defect Density
7.Defect Removal Efficiency (DRE)
8.Defect Leakage
9.Defect Rejection ratio [Invalid bug ratio]
10.Percentage of Critical defects
11.Percentage of High defects
12.Percentage of Medium defects
13.Percentage of Low/Lowest defects
software testing, Regression testing meaning,
requirement of regression testing,
techniques of regression testing:- hybrid, retest all, Test case prioritization, Regression test selection.
pros and cons of using regression testing,
tools for regression testing :-
Relational Functional Tester(RFT)
Quick Test Professional (QTP)
selenium
Software testing metrics | David Tzemach David Tzemach
Overview
What we can measure using metrics
Common metrics to evaluate test process
why do we need to use metrics
Test metrics life cycle (TMLC)
Type of metrics
Fundamental testing metrics
Software Test Metrics and MeasurementsDavis Thomas
Explains in detail with example about calculation of -
1.Percentage Test cases Executed [Test Coverage]
2.Percentage Test cases not executed
3.Percentage Test cases Passed
4.Percentage Test cases Failed
5.Percentage Test cases BLOCKED/Deferred
6.Defect Density
7.Defect Removal Efficiency (DRE)
8.Defect Leakage
9.Defect Rejection ratio [Invalid bug ratio]
10.Percentage of Critical defects
11.Percentage of High defects
12.Percentage of Medium defects
13.Percentage of Low/Lowest defects
Test Status Reporting: Focus Your Message for ExecutivesTechWell
Test status reporting is a key factor in the success of test projects. Stephan Obbeck shares some ideas on how to communicate more than just a red-yellow-green status report to executive management and discusses how the right information can influence their decisions. Testers often create reports that are too technical, losing crucial information in a mountain of detailed data. Management needs to make decisions—based on data they do understand—that support the test project. Stephan explains how stakeholder and risk analysis helps you identify recipients of a report and what information is of interest to them. Learn different ways of presenting data to support your message and to get the most possible attention from the executive level. Discover how to avoid pitfalls when generating reports from test automation. Produce a summary of statistics that provides insight into a test project.
Software quality improvement expert Jan Princen and XBOSoft CEO Philip Lew discuss the use of Predictive Analytics to prevent software defects in this XBOSoft webinar on Defect Prevention.
We have experience with testing projects, both large and small. Sometimes our test estimates are accurate—and sometimes they’re not. We often miss deadlines because there are no defined criteria used to create our estimates. Sometimes we miss our schedules due to crunched testing timelines. Shyam Sunder briefly describes the different test estimation techniques including Simple, Medium, Complex; Top Down, Bottom Up; and Test Point Analysis. To assist in better estimating in the future, Shyam has prepared test estimation templates and guidelines, which can significantly help organizations in proper estimation of testing projects. Through his work, effort and schedule variations have significantly improved from ±60 percent to ±2 percent. Shyam explains the test estimation templates in detail and demonstrates how to choose the estimation templates for your organization’s software development process. Learn why effective software test estimation techniques help in tracking and controlling cost/effort overruns significantly.
The anonymised slides from an old (but hopefully still relevant) talk on the case for placing a strategic focus on design testability. The material covers the technical, process and organisational considerations arising from such a strategy and is predominantly a summary of the ideas presented in Brett Pettichord's 2001 "Design For Testability' paper available here. The presentation makes a case for why a high level of design testability can be seen as a critical success factor in achieving sustained agility.
Test Status Reporting: Focus Your Message for ExecutivesTechWell
Test status reporting is a key factor in the success of test projects. Stephan Obbeck shares some ideas on how to communicate more than just a red-yellow-green status report to executive management and discusses how the right information can influence their decisions. Testers often create reports that are too technical, losing crucial information in a mountain of detailed data. Management needs to make decisions—based on data they do understand—that support the test project. Stephan explains how stakeholder and risk analysis helps you identify recipients of a report and what information is of interest to them. Learn different ways of presenting data to support your message and to get the most possible attention from the executive level. Discover how to avoid pitfalls when generating reports from test automation. Produce a summary of statistics that provides insight into a test project.
Software quality improvement expert Jan Princen and XBOSoft CEO Philip Lew discuss the use of Predictive Analytics to prevent software defects in this XBOSoft webinar on Defect Prevention.
We have experience with testing projects, both large and small. Sometimes our test estimates are accurate—and sometimes they’re not. We often miss deadlines because there are no defined criteria used to create our estimates. Sometimes we miss our schedules due to crunched testing timelines. Shyam Sunder briefly describes the different test estimation techniques including Simple, Medium, Complex; Top Down, Bottom Up; and Test Point Analysis. To assist in better estimating in the future, Shyam has prepared test estimation templates and guidelines, which can significantly help organizations in proper estimation of testing projects. Through his work, effort and schedule variations have significantly improved from ±60 percent to ±2 percent. Shyam explains the test estimation templates in detail and demonstrates how to choose the estimation templates for your organization’s software development process. Learn why effective software test estimation techniques help in tracking and controlling cost/effort overruns significantly.
The anonymised slides from an old (but hopefully still relevant) talk on the case for placing a strategic focus on design testability. The material covers the technical, process and organisational considerations arising from such a strategy and is predominantly a summary of the ideas presented in Brett Pettichord's 2001 "Design For Testability' paper available here. The presentation makes a case for why a high level of design testability can be seen as a critical success factor in achieving sustained agility.
QUALITY METRICS OF TEST SUITES IN TESTDRIVEN DESIGNED APPLICATIONSijseajournal
New techniques for writing and developing software have evolved in recent years. One is Test-Driven
Development (TDD) in which tests are written before code. No code should be written without first having
a test to execute it. Thus, in terms of code coverage, the quality of test suites written using TDD should be
high.
In this work, we analyze applications written using TDD and traditional techniques. Specifically, we
demonstrate the quality of the associated test suites based on two quality metrics: 1) structure-based
criterion, 2) fault-based criterion. We learn that test suites with high branch test coverage will also have
high mutation scores, and we especially reveal this in the case of TDD applications. We found that TestDriven
Development is an effective approach that improves the quality of the test suite to cover more of the
source code and also to reveal more.
How to Make the Most of Regression and Unit Testing.pdfAbhay Kumar
Understanding the differences between regression testing and unit testing is paramount for maintaining the robustness of any software. Although both serve the purpose of vulnerability scanning to detect threats, they vary in terms of their test objectives, stages in the development process, and the scope of the code they cover. Let's delve into these distinctions to grasp their roles better.
Difference in Test Objectives:
- While similar, Unit and regression testing have distinct targets within your code. Unit testing, conducted by programmers, assesses individual components, validating the correct functionality of each variable, function, and object.
- On the other hand, regression testing (often termed QA testing) occurs after programmers complete work on specific features. It acts as a system-wide check, ensuring untouched components function as expected. While unit tests provide the precision of individual functions and variables, regression tests collaborate to ascertain that the entire system functions optimally.
Difference in the Development Phase:
- The timing of unit and regression tests sets them apart. Unit tests are conducted during the development phase, where developers run them after implementing changes to confirm no adverse impacts.
- Conversely, regression testing is performed before the feature's production release. It comprises unit tests, integration tests, and various other testing types. Testers are responsible for executing regression testing. Automated regression testing, a key step in continuous integration/continuous delivery, quickly detects if recent code changes have disrupted the existing code.
Difference in Code Coverage:
- A unit test concentrates on a single unit, method, or function, examining one element at a time. It doesn't account for how these units interact, necessitating integration tests. This approach provides swift feedback due to its focused testing nature.
- In contrast, regression tests validate if alterations to existing functionalities have affected other parts of the system by testing against predefined scenarios, ensuring correct integration of units. Given the comprehensive testing involved, it generally consumes more time.
Unit and regression testing are vital pillars in the software development journey. Regular execution of these tests is key to minimizing bugs and refining code quality.
Regression testing conducted post-unit testing before a software release, ensures system integrity despite changes. On the other hand, unit testing meticulously validates new functions, ensuring precise code execution.
Analysis and Design of Algorithms (ADA): An In-depth Exploration
Introduction:
The field of computer science is heavily reliant on algorithms to solve complex problems efficiently. The analysis and design of algorithms (ADA) is a fundamental area of study that focuses on understanding and creating efficient algorithms. This comprehensive overview will delve into the various aspects of ADA, including its importance, key concepts, techniques, and applications.
Importance of ADA:
Efficient algorithms play a critical role in various domains, including software development, data analysis, artificial intelligence, and optimization. ADA provides the tools and techniques necessary to design algorithms that are both correct and efficient. By analyzing the performance characteristics of algorithms, ADA enables computer scientists and engineers to develop solutions that save time, resources, and computational power.
Key Concepts in ADA:
Correctness: ADA emphasizes the importance of designing algorithms that produce correct outputs for all possible inputs. Techniques like mathematical proofs and induction are used to establish the correctness of algorithms.
Complexity Analysis: ADA seeks to analyze the efficiency of algorithms by examining their time and space complexity. Time complexity measures the amount of time required by an algorithm to execute, while space complexity measures the amount of memory consumed.
Asymptotic Notations: ADA employs asymptotic notations, such as Big O, Omega, and Theta, to express the growth rates of functions and classify the efficiency of algorithms. These notations allow for a concise comparison of algorithmic performance.
Algorithm Design Paradigms: ADA explores various design paradigms, including divide and conquer, dynamic programming, greedy algorithms, and backtracking. Each paradigm offers a systematic approach to solving problems efficiently.
Techniques in ADA:
Divide and Conquer: This technique involves breaking down a problem into smaller subproblems, solving them independently, and combining the solutions to obtain the final result. Well-known algorithms like Merge Sort and Quick Sort utilize the divide and conquer approach.
Dynamic Programming: Dynamic programming breaks down a complex problem into a series of overlapping subproblems and solves them in a bottom-up manner. This technique optimizes efficiency by storing and reusing intermediate results. The Fibonacci sequence calculation is a classic example of dynamic programming.
Greedy Algorithms: Greedy algorithms make locally optimal choices at each step, with the hope of achieving a global optimal solution. These algorithms are efficient but may not always yield the best overall solution. The Huffman coding algorithm for data compression is a widely used example of a greedy algorithm.
Backtracking: Backtracking involves searching for a solution to a problem by incrementally building a solution and undoing the choices that lead to dead-ends.
This paper describes the different techniques of testing the software. This paper explicitly addresses the idea for testability and the important thing is that the testing itself-not just by saying that testability is a desirable goal, but by showing how to do it. Software testing is the process we used to measure the quality of developed software. Software Testing is not just about error-finding and their solution but also about checking the client requirements and testing that those requirements are met by the software solution. It is the most important functional phase in the Software Development Life Cycle(SDLC) as it exhibits all mistakes, flaws and errors in the developed software. Without finding these errors, technically termed as ‘bugs,’ software development is not considered to be complete. Hence, software testing becomes an important parameter for assuring quality of the software product. We discuss here about when to start and when to stop the testing of software. How errors or Bugs are formed and rectified. How software testing is done i.e. with the help of Team Work.
What are Software Testing Methodologies | Software Testing Techniques | EdurekaEdureka!
YouTube Link: https://youtu.be/6rNgPXz9A9s
(** Test Automation Masters Program: https://www.edureka.co/masters-program/automation-testing-engineer-training **)
This Edureka PPT on "Software Testing Methodologies and Techniques" will give you in-depth knowledge about different types of software testing models and techniques
The following are the topics covered in the session:
Importance of Software Testing
Software Testing Methodologies
Software Testing Techniques
Black-Box Techniques
White-Box Techniques
Experience-Based Techniques
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Why every dev team needs static analysisCoderGears
CppDepend is a static analysis tool for C/C++. CppDepend supports a large number of code metrics, allows for visualization of dependencies using directed graphs, and dependency matrices. It also performs code base snapshots comparison, and validation of architectural and quality rules.
Sachpazis:Terzaghi Bearing Capacity Estimation in simple terms with Calculati...Dr.Costas Sachpazis
Terzaghi's soil bearing capacity theory, developed by Karl Terzaghi, is a fundamental principle in geotechnical engineering used to determine the bearing capacity of shallow foundations. This theory provides a method to calculate the ultimate bearing capacity of soil, which is the maximum load per unit area that the soil can support without undergoing shear failure. The Calculation HTML Code included.
CFD Simulation of By-pass Flow in a HRSG module by R&R Consult.pptxR&R Consult
CFD analysis is incredibly effective at solving mysteries and improving the performance of complex systems!
Here's a great example: At a large natural gas-fired power plant, where they use waste heat to generate steam and energy, they were puzzled that their boiler wasn't producing as much steam as expected.
R&R and Tetra Engineering Group Inc. were asked to solve the issue with reduced steam production.
An inspection had shown that a significant amount of hot flue gas was bypassing the boiler tubes, where the heat was supposed to be transferred.
R&R Consult conducted a CFD analysis, which revealed that 6.3% of the flue gas was bypassing the boiler tubes without transferring heat. The analysis also showed that the flue gas was instead being directed along the sides of the boiler and between the modules that were supposed to capture the heat. This was the cause of the reduced performance.
Based on our results, Tetra Engineering installed covering plates to reduce the bypass flow. This improved the boiler's performance and increased electricity production.
It is always satisfying when we can help solve complex challenges like this. Do your systems also need a check-up or optimization? Give us a call!
Work done in cooperation with James Malloy and David Moelling from Tetra Engineering.
More examples of our work https://www.r-r-consult.dk/en/cases-en/
Hybrid optimization of pumped hydro system and solar- Engr. Abdul-Azeez.pdffxintegritypublishin
Advancements in technology unveil a myriad of electrical and electronic breakthroughs geared towards efficiently harnessing limited resources to meet human energy demands. The optimization of hybrid solar PV panels and pumped hydro energy supply systems plays a pivotal role in utilizing natural resources effectively. This initiative not only benefits humanity but also fosters environmental sustainability. The study investigated the design optimization of these hybrid systems, focusing on understanding solar radiation patterns, identifying geographical influences on solar radiation, formulating a mathematical model for system optimization, and determining the optimal configuration of PV panels and pumped hydro storage. Through a comparative analysis approach and eight weeks of data collection, the study addressed key research questions related to solar radiation patterns and optimal system design. The findings highlighted regions with heightened solar radiation levels, showcasing substantial potential for power generation and emphasizing the system's efficiency. Optimizing system design significantly boosted power generation, promoted renewable energy utilization, and enhanced energy storage capacity. The study underscored the benefits of optimizing hybrid solar PV panels and pumped hydro energy supply systems for sustainable energy usage. Optimizing the design of solar PV panels and pumped hydro energy supply systems as examined across diverse climatic conditions in a developing country, not only enhances power generation but also improves the integration of renewable energy sources and boosts energy storage capacities, particularly beneficial for less economically prosperous regions. Additionally, the study provides valuable insights for advancing energy research in economically viable areas. Recommendations included conducting site-specific assessments, utilizing advanced modeling tools, implementing regular maintenance protocols, and enhancing communication among system components.
Explore the innovative world of trenchless pipe repair with our comprehensive guide, "The Benefits and Techniques of Trenchless Pipe Repair." This document delves into the modern methods of repairing underground pipes without the need for extensive excavation, highlighting the numerous advantages and the latest techniques used in the industry.
Learn about the cost savings, reduced environmental impact, and minimal disruption associated with trenchless technology. Discover detailed explanations of popular techniques such as pipe bursting, cured-in-place pipe (CIPP) lining, and directional drilling. Understand how these methods can be applied to various types of infrastructure, from residential plumbing to large-scale municipal systems.
Ideal for homeowners, contractors, engineers, and anyone interested in modern plumbing solutions, this guide provides valuable insights into why trenchless pipe repair is becoming the preferred choice for pipe rehabilitation. Stay informed about the latest advancements and best practices in the field.
Overview of the fundamental roles in Hydropower generation and the components involved in wider Electrical Engineering.
This paper presents the design and construction of hydroelectric dams from the hydrologist’s survey of the valley before construction, all aspects and involved disciplines, fluid dynamics, structural engineering, generation and mains frequency regulation to the very transmission of power through the network in the United Kingdom.
Author: Robbie Edward Sayers
Collaborators and co editors: Charlie Sims and Connor Healey.
(C) 2024 Robbie E. Sayers
Water scarcity is the lack of fresh water resources to meet the standard water demand. There are two type of water scarcity. One is physical. The other is economic water scarcity.
Saudi Arabia stands as a titan in the global energy landscape, renowned for its abundant oil and gas resources. It's the largest exporter of petroleum and holds some of the world's most significant reserves. Let's delve into the top 10 oil and gas projects shaping Saudi Arabia's energy future in 2024.
2. What is Mutation Testing?
• Mutation testing is a structural testing technique, which uses the
structure of the code to guide the testing process.
• On a very high level, it is the process of rewriting the source code
in small ways in order to remove the redundancies in the source
code.
• These ambiguities might cause failures in the software if not
fixed.
3. Benefits:
• It brings a whole new kind of errors to the developer's attention.
• It is the most powerful method to detect hidden defects, which might be
impossible to identify using the conventional testing techniques.
• Debugging and Maintaining the product would be more easier .
4. Types:
Value Mutations: An attempt to change the values to detect errors in the
programs.
We usually change one value to a much larger value or one value to a much
smaller value. The most common strategy is to change the constants.
Decision Mutations: The decisions/conditions are changed to check for the design
errors. Typically, one changes the arithmetic operators to locate the defects and
also we can consider mutating all relational operators and logical operators (AND,
OR , NOT)
Statement Mutations: Changes done to the statements by deleting or duplicating
the line which might arise when a developer is copy pasting the code from
somewhere else.