inf 115 midterm wip

QA Principles Overview

A set of six key principles guiding software quality management: Partition, Visibility, Feedback, Sensitivity, Redundancy, and Restriction

Partition Principle

A strategy of breaking complex tasks into smaller, manageable, and independently solvable parts

Partition Principle Strategy

Decomposing complicated problems into smaller, independent components; Enables more focused and manageable problem-solving approaches

Visibility Principle

The practice of making project progress, quality, and status measurable and transparent

Visibility Metrics

Quantifiable measures used to track and evaluate the progress, quality, and effectiveness of software development and testing processes

Feedback Principle

A process of learning from past experiences and systematically applying lessons to improve software development processes

Feedback Implementation

Systematic approach to documenting and learning from past errors; Creating mechanisms to capture, analyze, and apply lessons learned from previous software development experiences

Sensitivity Principle

An approach to designing systems and tests that make faults more likely to cause observable failures

Sensitivity in Testing

Designing test strategies that maximize the likelihood of revealing potential issues; Creating test conditions that are more likely to expose hidden faults and vulnerabilities

Redundancy Principle

The practice of creating multiple, independent verification methods to ensure consistency and catch potential errors

Redundancy Strategies

Implementing multiple, independent verification techniques; Developing overlapping checks and balances to reduce the risk of undetected errors

Restriction Principle

The technique of imposing constraints that simplify complex problems

Restriction Implementation

Creating specific guidelines and limitations to reduce complexity; Developing frameworks that narrow the scope of potential solutions to make problem-solving more efficient

Basic Concepts of QA

Software quality management is a comprehensive approach to ensuring that software meets specified requirements and user expectations

QA Comprehensive Approach

Holistic method of ensuring software quality throughout the development process; Involves multiple strategies and techniques to meet and exceed software requirements

Software Process Model Evolution

A historical progression of software development methodologies; Moves from Waterfall (sequential, testing late) to V-Model (earlier test integration) to Spiral Model (continuous quality assurance)

Software Development Methodology History

The changing landscape of software development approaches; Tracing the evolution of methods that increasingly integrate quality assurance throughout the development cycle

Validation vs Verification

Two complementary approaches to software quality: Verification asks "Are we building the machine right?" (internal checks), Validation asks "Are we building the right machine?" (user perspective)

Validation and Verification Techniques

Comprehensive strategies for ensuring software quality from different perspectives; Methods to confirm both internal correctness and external user requirements

Mistake

A human error that leads to an incorrect result or action in the software development process

Human Error in Software Development

Unintentional actions or decisions that can negatively impact software development; Understanding the sources and potential mitigations of human-induced errors

Fault/Bug

An inherent defect or imperfection in the source code that can potentially cause incorrect program behavior

Software Defect Characteristics

Detailed examination of code-level imperfections that can lead to program malfunctions; Understanding the nature and potential impact of structural errors in software

Error

The runtime manifestation of a fault, causing the software to deviate from its expected behavior

Runtime Error Dynamics

The process by which code faults translate into observable incorrect behavior; Exploring how internal software states can become compromised during execution

Failure

The external, observable incorrect behavior of a system that fails to meet its specified requirements

Software Failure Manifestation

The external symptoms of internal software errors; How technical issues translate into user-observable problems

Test Case

A specific set of input conditions, execution steps, and expected results designed to verify a particular functionality of a software application

Test Case Design Principles

Strategies for creating comprehensive and effective test scenarios; Methods for developing test cases that thoroughly validate software functionality

Test Oracle

A mechanism that helps determine whether a software test has passed or failed

Test Validation Mechanism

Techniques for comparing actual test results with expected outcomes; Methods to objectively determine the success or failure of software tests

Exhaustive Testing Limitation

The impossibility of testing every possible input scenario due to the infinite complexity of software input spaces

Testing Resource Constraints

Understanding the practical limitations of comprehensive software testing; Recognizing the economic and time-based challenges of exhaustive test coverage

Black Box Testing

A testing methodology that examines software functionality without knowledge of internal code structure

External Functionality Testing

Approach to software quality assurance that evaluates systems based on their observable behavior; Testing methods that do not require internal code knowledge

White Box Testing

A testing approach that analyzes the internal structure, logic, and code paths of a software application

Internal Code Structure Testing

Detailed examination of software's internal logic and implementation; Strategies for testing all potential code paths and decision points

Equivalence Partitioning

A test design technique that divides input data into equivalent partitions

Input Space Division Strategy

Method of categorizing input data to optimize testing efficiency; Techniques for creating representative test cases across different input domains

Exploratory Testing

A dynamic testing approach where testers simultaneously learn, design, and execute tests

Dynamic Testing Methodology

Flexible approach to software testing that allows real-time adaptation; Testing strategy that combines learning, design, and execution simultaneously

Acceptance Testing Types

A collection of testing methodologies to validate software against user requirements

User Requirement Validation Methods

Techniques for ensuring software meets specific user needs; Different approaches to confirming that software fulfills its intended purpose

Combinatorial Testing

A systematic testing method that examines interactions between multiple input parameters

Multi-Parameter Interaction Testing

Approach to identifying complex software bugs through comprehensive input combination analysis; Methods for uncovering issues that appear only in specific scenario intersections

Test Driven Development (TDD)

A software development methodology where tests are written before the actual implementation code

Proactive Testing Methodology

Approach to software development that prioritizes test creation before code implementation; Systematic method for ensuring code meets predefined requirements

Behavior Driven Development (BDD)

An extension of TDD that focuses on the behavioral outcomes of software

Behavioral Specification Techniques

Methods for describing software requirements using natural language and behavior-focused scenarios; Approach to defining software functionality through user-centric language

Random Testing

A testing approach where test inputs are selected uniformly and randomly without a specific strategy, potentially covering a wide range of inputs but potentially missing critical edge cases

Systematic Testing

A methodical testing approach that deliberately selects test inputs based on specific criteria, focusing on representative values, boundary conditions, and regions more likely to contain faults

Random Testing Advantages

Helps avoid designer bias by treating all inputs equally and potentially uncovering unexpected issues through unpredictable input selection

Random Testing Limitations

May miss important edge cases, has low probability of finding rare but critical bugs, and does not strategically target potential problem areas

Systematic Testing Advantages

Strategically targets potential fault regions, focuses on boundary values and representative inputs, and provides more structured and deliberate test coverage

Systematic Testing Techniques

Includes equivalence partitioning, boundary value analysis, decision table testing, and state transition testing to methodically explore input spaces

Testing Input Selection Strategies

Different methodologies for choosing test inputs; Comparing approaches that range from uniform random selection to strategically targeted testing