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Sunday, 7 September 2025

What is Quality and Defect in Manual Testing?

 

What is Quality in Manual Testing?

In manual testing, quality does not simply mean “no bugs.” It’s a broader concept. Quality is the degree to which a software product meets the stated and implied needs of its users when it is used under specified conditions.

In simpler terms, a high-quality software is:

  1. Fit for its purpose: It does what it’s supposed to do.
  2. Meets user expectations: It provides a good experience, not just basic functionality.

Breaking Down Quality with Examples: The “Ice Cream Cone” Model

Imagine a user wants to buy an ice cream cone from a shop. Let’s see how different levels of quality apply.

1. Functional Quality: “Does it work?”

This is the most basic level. Does the software perform its intended functions correctly?

  • Example: The user pays for a chocolate ice cream cone.
    • Low Quality: The server gives them an empty cone. Or the payment system crashes. The core function fails.
    • High Quality: The user correctly receives a chocolate ice cream cone. The core function works.

2. Non-Functional Quality: “How well does it work?”

This is where user experience (UX) comes into play. The function works, but is it a good experience?

  • Reliability:
    • Low Quality: The ice cream cone breaks immediately, spilling ice cream everywhere. (The software crashes under normal use).
    • High Quality: The cone is sturdy and holds the ice cream reliably.
  • Usability (Ease of Use):
    • Low Quality: The ice cream is scooped into the cone upside down, making it messy to eat. The menu is confusing and hard to read. (The software is clunky and illogical).
    • High Quality: The ice cream is neatly presented. The menu is clear. It’s easy and intuitive to order.
  • Performance:
    • Low Quality: The user has to wait 10 minutes in line while the server struggles to scoop the ice cream. (The software is slow and sluggish).
    • High Quality: The user is served quickly and efficiently.
  • Compatibility:
    • Low Quality: The shop only accepts cash, but the user only has a card. (The software only works on one specific browser or device).
    • High Quality: The shop accepts cash, card, and mobile pay. (The software works across different browsers, devices, and operating systems).
  • Security:
    • Low Quality: The cashier writes down the user’s credit card number on a piece of paper for everyone to see. (The software has vulnerabilities that leak user data).
    • High Quality: The payment is processed securely through an encrypted system.

3. Perceived Quality: “How does it feel?”

This is the emotional response the product generates.

  • Example:
    • Low Quality: The ice cream is served in a dirty, chipped bowl. The server is rude. (The software has a poor, outdated design with spelling mistakes).
    • High Quality: The ice cream is served in a nice wafer cone with a chocolate flake on top. The shop is clean, and the server is friendly. (The software has a beautiful, modern UI with smooth animations and a helpful tone). The user feels good about their purchase.

The Manual Tester’s Role in Ensuring Quality

A manual tester’s job is to verify all these aspects of quality.

  • For Functional Quality: They execute test cases to ensure “the chocolate ice cream is indeed chocolate and is given to the user.”
  • For Non-Functional Quality: They explore the software to ask: “Is it easy to find the ‘order’ button? Does the page load quickly? Does it look right on my phone?”
  • For Perceived Quality: They provide feedback like: “This error message is harsh and confusing. The color scheme is unpleasant. This workflow feels frustrating.”

Conclusion: Finding a bug where the software crashes (functional quality) is crucial. But a great manual tester also identifies issues that lead to a poor user experience (non-functional and perceived quality). True quality is achieved when the software not only works correctly but is also a pleasure to use.

What is a Defect in Manual Testing?

In manual testing, a defect (also called a bug or fault) is any imperfection, flaw, or deviation in the software application that causes it to behave in an unintended, unexpected, or incorrect way compared to its requirements or expected behavior.

The core idea is a variance between the actual result and the expected result.


4 Detailed Examples of Defects

Here are four common types of defects a manual tester might find, ranging from simple to complex.

Example 1: Functional Defect (Calculation Error)

  • Scenario: Testing a calculator app.
  • Expected Result: When a user enters 5 + 5 and presses =, the result should be 10.
  • Actual Result: The app displays 55.
  • The Defect: The “+” button is concatenating the numbers (behaving like a string operator) instead of performing mathematical addition. This is a clear functional failure.

Example 2: User Interface (UI) Defect

  • Scenario: Testing an e-commerce website’s product page on a mobile phone.
  • Expected Result: The “Add to Cart” button should be fully visible and clickable without needing to scroll sideways.
  • Actual Result: The “Add to Cart” button is cut off on the right side of the screen, and the user cannot click it.
  • The Defect: This is a UI or layout bug. The page is not responsive for a specific mobile screen size, directly preventing the user from making a purchase.

Example 3: Content Defect

  • Scenario: Testing a banking application’s fund transfer confirmation screen.
  • Expected Result: The confirmation message should be professional, clear, and free of spelling errors, e.g., “Your transfer of $100 to John Doe was successful.”
  • Actual Result: The message says, “Your transfer of $100 to John Doe was sucessful.” (misspelling of “successful”).
  • The Defect: This is a content or cosmetic bug. While it doesn’t break functionality, it looks unprofessional and can erode user trust in the application’s attention to detail.

Example 4: Logical / Workflow Defect

  • Scenario: Testing a user registration flow.
  • Expected Result: After successfully filling out a form and clicking “Submit,” the user should receive a “Registration Successful!” message and be logged into their new account.
  • Actual Result: The user gets a “Registration Successful!” message but is then redirected back to the login page instead of being logged in automatically.
  • The Defect: This is a logical or workflow bug. The individual steps work (form validation, saving data, showing message), but the overall sequence of events is incorrect and creates a poor user experience.

What a Tester Does Upon Finding a Defect:

A manual tester doesn’t just find the defect; they report it systematically. A good defect report includes:

  1. Title: A short, clear summary (e.g., “Add to Cart button not visible on iPhone 12 screen”).
  2. Description: Detailed explanation of the issue.
  3. Steps to Reproduce: Exact steps to make the defect appear consistently.
  4. Expected vs. Actual Result: As shown in the examples above.
  5. Evidence: A screenshot or screen recording.
  6. Severity & Priority: How bad the bug is and how quickly it needs to be fixed.

Finding these defects early is the primary goal of manual testing, as it saves the company time, money, and protects its reputation.

Product vs Project-Based Companies: Key Differences

 

The Core Difference (Simple Analogy)

  • A Product-Based Company is like a chef who creates their own unique recipe (the product) and serves it to many customers.
  • A Project-Based Company is like a caterer who is hired by different clients to create and manage events (the projects) based on the client’s specific menu and requirements.

What is a Product-Based Company?

A product-based company invests in building its own product or software. Its primary goal is to develop, market, sell, and support this product to its customers.

Examples:

  • Tech Giants: Google (Search, Gmail, YouTube), Microsoft (Windows, Office 365), Apple (iOS, MacOS), Meta (Facebook, Instagram, WhatsApp), Adobe (Photoshop, Acrobat).
  • Product Startups/SaaS Companies: Spotify, Netflix, Slack, Zoom, Canva, and thousands of smaller companies building a specific software product.

Key Characteristics:

  • Owns the Product: The company has full ownership and control over its product’s vision, roadmap, and intellectual property.
  • Focus on Innovation: The culture is heavily focused on innovation, user experience (UX), and creating the best possible product to win the market.
  • End-Users are Customers: The people using the product are the company’s customers. The goal is to acquire and retain millions of them.
  • Work Nature: Work is often organized in long-term cycles or sprints focused on releasing new features and versions (v1.0, v2.0) of the product.
  • Scale: The product is built to serve a massive number of users simultaneously (scalability is a huge focus).

What is a Project-Based Company?

A project-based company (often called a service-based or client-servicing company) does not have its own product. Instead, it provides software services and solutions to other companies (clients) based on the client’s requirements.

Examples:

  • IT Service Giants: TCS, Infosys, Wipro, Accenture, Capgemini, Cognizant, Deloitte.
  • Digital Agencies & Consultancies: Companies that build websites, apps, or custom software for clients.

Key Characteristics:

  • Works on Client Projects: The company works on projects defined and paid for by a client. The client owns the final software/product.
  • Focus on Client Requirements: The culture is focused on meeting client specifications, delivering on time, and within the allocated budget.
  • The Client is the Customer: The company’s primary relationship is with the client, not the end-user of the software.
  • Work Nature: Work is organized into fixed-duration projects with a defined start and end date. Once the project is delivered, teams might be moved to a new project for a different client.
  • Scope: The project’s scope is defined by a contract and a Statement of Work (SoW) from the client.

Comparison Table: Product vs. Project-Based Companies

FeatureProduct-Based CompanyProject-Based Company
Core BusinessDevelop and sell its own software product.Provide software services and solutions to clients.
OwnershipCompany owns the product and its IP.The client owns the final deliverable and its IP.
Primary GoalProduct success, user growth, and market share.Client satisfaction, project delivery (on time & budget).
Work CultureOften more innovative, flexible, and creative.Often more structured, process-driven (e.g., strict deadlines).
End-UserMillions of external users/customers.The client’s employees or customers (you rarely interact with them).
TechnologyUsually works on modern, cutting-edge tech stacks.Technology is often dictated by the client’s existing systems.
Job StabilityCan be less stable; if the product fails, layoffs can happen.Often more stable; income comes from multiple clients.
LearningDeep, specialized knowledge in the product’s domain and tech.Broad exposure to different technologies, domains, and clients.

Which is Better for a Manual Tester?

Both offer excellent opportunities, but the experience differs:

  • In a Product Company:
    • Pros: You become a domain expert in your product. You deeply understand the user and work on improving the same product over years. You often have more freedom to suggest improvements and focus on UX. Compensation and perks are generally higher.
    • Cons: You might work on the same technology or product for a long time.
  • In a Project Company:
    • Pros: You get exposure to various industries (e.g., banking, healthcare, retail) and different technologies by working on multiple client projects. It’s a fantastic way to build a broad skillset and resume quickly.
    • Cons: Work can be repetitive (e.g., lots of regression testing for a bank’s mainframe system). You may have less creative input, as requirements are strictly set by the client.

Conclusion: There’s no single “better” option. It depends on your career goals. If you love deep expertise and innovation, aim for a product role. If you want diverse experience and want to see how different businesses work, a project role is great. Many testers start in project-based companies to gain experience and then move to product-based companies.

What is Manual Testing? Key Skills, Career Path, and Why You Should Choose It

1. What is Manual Testing?

Manual Testing is the process of verifying and validating a software application manually (i.e., without using any automation tools or scripts) to ensure it behaves as expected and is free from defects.

A manual tester takes on the role of an end-user. They execute test cases step-by-step, using the application’s features to identify any unexpected behavior, bugs, or usability issues. The goal is to find as many defects as possible before the software is released to real users.

Key Characteristics:

  • Human-Centric: Relies on the tester’s intuition, experience, and creativity.
  • No Automation Scripts: Tests are executed by a person, not a program.
  • Exploratory: Allows testers to go “off-script” to explore the application and find hidden bugs.
  • UI and Usability Focus: Excellent for evaluating user experience, look-and-feel, and ease of use.

2. Why Do We Choose a Career in Manual Testing? (Why Choose a Career as a Manual Tester?)

There are many compelling reasons to choose a career in manual testing:

  1. Foundation of Software Quality: It is the fundamental process for ensuring software quality. Every application is tested manually at some point, making it an always-relevant skill.
  2. High Demand: The software industry is booming, and every software product needs testers. There is a constant demand for skilled manual testers in every sector.
  3. Low Barrier to Entry: It is one of the most accessible ways to start a career in tech. You don’t need an advanced computer science degree or deep programming knowledge to begin.
  4. Creative and Critical Thinking: It’s not just about following steps. It requires analytical thinking to design test cases and creativity to “break” the software and think of unusual user scenarios.
  5. User Advocacy: You become the voice of the customer. You ensure the final product is not just functionally correct but also user-friendly and intuitive.
  6. Stepping Stone to Other Roles: It’s a fantastic launchpad for careers in automation testing, performance testing, QA leadership, product management, or business analysis, as it gives you a deep understanding of the software development lifecycle (SDLC).

3. Key Skills Required for Manual Testing

To be a successful manual tester, you need a blend of technical, analytical, and soft skills.

A) Analytical Skills

  • Analytical Thinking: The ability to break down complex software requirements into smaller, testable units.
  • Attention to Detail: A keen eye to spot the smallest irregularities, like a misaligned button, a wrong color, or an incorrect error message.
  • Critical Thinking: The ability to question “what if?” and think of scenarios that developers might not have considered.

B) Technical Skills

  • Understanding of SDLC & STLC: Strong knowledge of the Software Development Life Cycle and the Software Testing Life Cycle (Requirements Analysis, Test Planning, Case Development, Test Execution, etc.).
  • Writing Test Cases & Bug Reports: The ability to write clear, concise, and comprehensive test cases and detailed bug reports. A good bug report includes steps to reproduce, expected vs. actual results, and evidence (screenshots/videos).
  • Test Design Techniques: Knowledge of techniques like Equivalence Partitioning, Boundary Value Analysis, Decision Table Testing, and State Transition Diagrams to create effective test cases with minimum effort.
  • Basic SQL Knowledge: Ability to write simple SQL queries (SELECTUPDATEWHEREJOIN) to verify data in the database backend.
  • Basic Knowledge of APIs: Understanding what an API is and how to use tools like Postman or Swagger to test them manually is a huge plus.
  • Familiarity with Testing Tools: Experience with tools like Jira, Trello (for bug tracking), TestRail, Zephyr (for test management), and browser DevTools.

C) Domain Knowledge

  • Understanding the specific industry you are testing for (e.g., banking, healthcare, e-commerce) is a massive advantage. It helps you think like a real user.

D) Soft Skills

  • Communication Skills: You must communicate clearly and effectively with developers (to report bugs) and with managers (to report progress). This is arguably the most important soft skill.
  • ** Curiosity & a “Tester’s Mindset”:** A natural desire to explore, experiment, and ask questions. A good tester is naturally skeptical and doesn’t take “it works” for an answer.
  • Patience and Persistence: Testing can be repetitive. It requires patience to execute hundreds of test cases and persistence to re-test a fixed bug multiple times.
  • Time Management: The ability to prioritize testing efforts and meet deadlines.

Summary

AspectDescription
What it isManually testing software without automation scripts to find bugs.
Why choose itHigh demand, great entry into tech, creative, user-focused, and a strong career foundation.
Key SkillsAnalytical thinking, attention to detail, test case design, bug reporting, basic SQL/API knowledge, and excellent communication.

Manual testing is a rewarding and critical field that ensures the software we use every day is reliable, functional, and enjoyable. It’s a career built on the principle of protecting the user from bad experiences.

Tuesday, 19 August 2025

What is AI Artificial Intelligence ? software course Details in Telugu #ai #artificialintelligence

 AI (Artificial Intelligence) అంటే ఏమిటి?

AI అనేది మానవుల మాదిరిగానే ఆలోచించే, నేర్చుకునే మరియు సమస్యలను పరిష్కరించే సామర్థ్యం ఉన్న యంత్రాలు లేదా సాఫ్ట్‌వేర్. ఇది కేవలం ప్రోగ్రామింగ్ చేసిన పనులను మాత్రమే కాకుండా, ఇచ్చిన డేటా ఆధారంగా సొంతంగా నిర్ణయాలు తీసుకోవడం మరియు భవిష్యత్తును అంచనా వేయడం వంటివి కూడా చేస్తుంది. మనం ఉపయోగించే స్మార్ట్‌ఫోన్లలోని వాయిస్ అసిస్టెంట్‌లు (Siri, Google Assistant), రికమండేషన్ సిస్టమ్స్ (Netflix, YouTube), మరియు స్వయంచాలకంగా నడిచే కార్లు వంటివి AIకి కొన్ని ఉదాహరణలు.


ఎవరు నేర్చుకోవచ్చు?

AI అనేది ఒక విశాలమైన రంగం, దీనిని చాలా మంది నేర్చుకోవచ్చు.

  • కంప్యూటర్ సైన్స్ విద్యార్థులు: మెషిన్ లెర్నింగ్ మరియు డేటా సైన్స్ వంటి ఆధునిక టెక్నాలజీలను నేర్చుకోవడానికి.

  • సాఫ్ట్‌వేర్ డెవలపర్లు: ఇప్పటికే ఉన్న అప్లికేషన్‌లకు AI ఫీచర్లను జోడించడానికి లేదా కొత్త AI-ఆధారిత ఉత్పత్తులను నిర్మించడానికి.

  • డేటా సైంటిస్ట్‌లు: పెద్ద మొత్తంలో డేటాను విశ్లేషించడానికి మరియు దాని నుండి విలువైన అంతర్దృష్టులను కనుగొనడానికి.

  • మరెవరైనా: గణితం మరియు ప్రోగ్రామింగ్ పై ఆసక్తి ఉన్నవారు, ఎలాంటి డిగ్రీతో సంబంధం లేకుండా AI నేర్చుకోవచ్చు.


నేర్చుకోవడానికి అవసరమైనవి (Prerequisites)

AI నేర్చుకోవడానికి కొన్ని ప్రాథమిక విషయాలపై అవగాహన ఉండటం చాలా అవసరం:

  • గణితం: లీనియర్ ఆల్జీబ్రా, కాలిక్యులస్, మరియు స్టాటిస్టిక్స్ వంటి గణిత అంశాలు AI అల్గారిథమ్‌లను అర్థం చేసుకోవడానికి చాలా ముఖ్యమైనవి.

  • ప్రోగ్రామింగ్ భాష: పైథాన్ అనేది AIకి ఎక్కువగా ఉపయోగించే భాష. కాబట్టి పైథాన్‌పై మంచి పట్టు ఉండాలి.

  • డేటా పరిజ్ఞానం: డేటాబేస్‌లు, డేటా స్ట్రక్చర్స్ మరియు డేటాను ఎలా శుభ్రం చేసి, ప్రాసెస్ చేయాలో తెలిసి ఉండాలి.


ప్రధాన సర్టిఫికేషన్లు

AI రంగంలో అనేక కోర్సులు మరియు సర్టిఫికేషన్లు అందుబాటులో ఉన్నాయి. వాటిలో ముఖ్యమైనవి:

  1. Google AI Professional Certificates: గూగుల్ ద్వారా అందించబడే ఈ సర్టిఫికేషన్ మెషిన్ లెర్నింగ్, డీప్ లెర్నింగ్ మరియు ఇతర AI కాన్సెప్ట్‌లపై మీ నైపుణ్యాలను ధృవీకరిస్తుంది.

  2. Microsoft Certified: Azure AI Fundamentals: మైక్రోసాఫ్ట్ క్లౌడ్ ప్లాట్‌ఫామ్ అయిన Azure పై AI మరియు మెషిన్ లెర్నింగ్‌కు సంబంధించిన ప్రాథమిక జ్ఞానాన్ని ఈ సర్టిఫికేషన్ సూచిస్తుంది.


జాబ్ మార్కెట్ మరియు ఉద్యోగ పాత్రలు

ప్రస్తుతం AI అనేది అత్యంత వేగంగా అభివృద్ధి చెందుతున్న రంగం. చాలా కంపెనీలు తమ వ్యాపారాలను మెరుగుపరచుకోవడానికి AI ని ఉపయోగిస్తున్నాయి, కాబట్టి AI నైపుణ్యాలు ఉన్నవారికి మంచి జీతాలు మరియు అనేక ఉద్యోగ అవకాశాలు ఉన్నాయి.

ముఖ్యమైన ఉద్యోగ పాత్రలు:

  • AI ఇంజనీర్: AI మోడల్స్ మరియు సిస్టమ్‌లను నిర్మించడం మరియు అమలు చేయడం.

  • మెషిన్ లెర్నింగ్ ఇంజనీర్: మెషిన్ లెర్నింగ్ అల్గారిథమ్‌లను అభివృద్ధి చేయడం మరియు వాటిని శిక్షణ ఇవ్వడం.

  • డేటా సైంటిస్ట్: డేటాను విశ్లేషించి, దాని ఆధారంగా వ్యాపార నిర్ణయాలకు సహాయపడే మోడల్స్‌ను రూపొందించడం.

  • రోబోటిక్స్ ఇంజనీర్: AI-ఆధారిత రోబోలను రూపొందించడం మరియు ప్రోగ్రామ్ చేయడం.



What is AI (Artificial Intelligence)? software course Details #AI #ArtificialIntelligence #Python

 

What is AI (Artificial Intelligence)?

Artificial Intelligence (AI) is a field of computer science focused on creating systems that can perform tasks that would typically require human intelligence. This includes the ability to learn, reason, solve problems, understand language, and perceive the world. AI is not just a single technology but a broad field encompassing sub-disciplines like machine learning (ML), deep learning, and natural language processing (NLP).

AI applications are widespread and can be found in everyday life, such as in:

  • Virtual assistants like Siri and Google Assistant.

  • Recommendation engines on platforms like Netflix and Amazon.

  • Self-driving cars and robotics.

  • Fraud detection systems in finance.


Who Can Learn It?

AI is a vast field with opportunities for people from various backgrounds.

  • Computer Science & Engineering Students: A strong foundation in these areas is a common starting point for a career in AI.

  • Software Developers: Developers can specialize in AI by learning relevant programming languages and frameworks to build AI-powered applications.

  • Data Scientists & Analysts: Professionals who work with large datasets can leverage AI to perform advanced analytics and build predictive models.

  • Anyone with a Strong Interest in Math and Logic: Given the reliance of AI on mathematics and programming, individuals with a passion for these subjects can learn AI regardless of their academic background.


Prerequisites to Learn

A solid foundation in these key areas is highly recommended before diving into AI:

  • Mathematics: A strong grasp of linear algebra, calculus, and statistics is essential for understanding the algorithms and theories behind AI.

  • Programming Language: Python is the most widely used language in AI. Proficiency in Python and its libraries (like NumPy, Pandas, and scikit-learn) is crucial.

  • Data Knowledge: You should have an understanding of data structures, databases, and how to clean, process, and analyze data.


Main 2 Certifications

While many certifications exist, two of the most well-known are offered by leading tech companies.

  1. Google AI Professional Certificates: These are highly valued and provide a structured learning path. They cover key concepts in machine learning, deep learning, and practical applications, helping to validate your skills.

  2. Microsoft Certified: Azure AI Engineer Associate: This certification focuses on using Microsoft's Azure cloud platform to build, manage, and deploy AI solutions. It validates your ability to use Azure services for tasks like computer vision and natural language processing.


Job Market and Job Roles

The job market for AI professionals is booming and is one of the fastest-growing sectors in the tech industry. As businesses across all sectors adopt AI to improve efficiency and make data-driven decisions, the demand for skilled professionals continues to grow.

Common job roles that require AI skills include:

  • AI Engineer: Focuses on building and deploying AI models and systems.

  • Machine Learning Engineer: Specializes in developing and training machine learning algorithms and maintaining ML systems.

  • Data Scientist: Analyzes large datasets, designs experiments, and builds models to extract insights that can drive business decisions.

  • Robotics Engineer: Combines knowledge of robotics and AI to design and program autonomous robots.