Computer Hardware Utilities Quiz

Hardware Utilities

• Defragmentation Software: It organizes fragmented files on a disk to improve access time and boost system performance.
• System Cleaners and Uninstallers: They remove temporary files and unused programs from a system.
• Security Utilities:
  • Antivirus and anti-malware utilities: Protect against viruses and malicious software.
  • Firewall software: Blocks unauthorized access to a computer network.

File Compression Utilities

• File Compression Programs: Reduce file size, saving disk space or speeding up internet transfers.
• Zip Files: Compressed files with .zip extensions, which can be unzipped to restore the original size.
• MP3: A compression format that drastically reduces audio file sizes with minimal quality loss.

File Defragmentation

• File Fragmentation: Occurs when files are stored in non-contiguous locations on a disk.
• Defragmentation Necessity: Periodically defragmenting files helps optimize disk performance by organizing fragmented files.
• Defragmentation Relevance with SSDs: Defragmentation is generally not required for SSD devices because they access data quickly regardless of file placement.

Virtualization Software

• Virtualization: Creates virtual server environments by dividing a physical computer into multiple 'virtual' servers.
• Benefits: Virtualization reduces the need for physical servers, significantly saving on operational and capital expenses.

Software Development Kits (SDKs)

• SDKs: A collection of tools, libraries, and documentation for application development on specific platforms.
• SDK Source: Offered by hardware, software, and cloud service providers.
• Apple SDK Examples: macOS SDK, iOS SDK, and watchOS SDK.
• Java SDK Examples:
  • Android SDK
  • Apache Tomcat - for hosting Java web applications
  • AWS SDK for Java
  • Google Cloud SDK for Java
  • Microsoft Azure SDK for Java

Programming Languages, IDEs, and SDKs

• Android Development: Google transitioned from providing an SDK to a comprehensive IDE called Android Studio for Android development.
• Android Programming Language: Java.

Programming Libraries

• Libraries: Collections of pre-written code for reusable functions, classes, and data structures, aiding in simplifying software development.
• Java Library Examples:
  • Stanford CoreNLP: Natural Language Processing
  • WEKA: Machine Learning
  • Deeplearning4L (DL4J): Deep Learning
  • JUnit: Software Testing
  • JDBC: Relational Databases

Software Issues and Trends

• Software Bugs: Flaws or errors in software that prevent it from functioning as expected.
• Freeware: Software freely available to the public.
• Open-Source Software: Software distributed with its source code, generally free of charge.
• Software Licensing:
  • Permissive Style (Open Source): Minimal restrictions, example: Android.
  • Copyleft Style (Open Source): Derivative works must maintain the same rights, example: Linux kernel.
  • Proprietary Licenses: Restrict usage, modification, and distribution, example: MS Windows.

Cloud Computing

• Cloud Computing: Software and storage accessed via the internet as a service.
• Cloud Computing Benefits for Businesses: Reduced system design, installation, and maintenance costs; enhanced efficiency; and accessible systems for employees from any internet-connected location.
• Cloud Computing Security: Data security is a primary concern, as data relies on a third-party service provider for protection.

Public Cloud Computing

• Public Cloud Computing: Infrastructure owned and managed by a service provider, allowing access to shared hardware resources over the internet.
• Public Cloud Computing Services:
  • Infrastructure as a Service (IaaS): Provides computing resources like servers and storage.
  • Software as a Service (SaaS): Offers software applications accessed over the internet (e.g., email, CRM).
  • Platform as a Service (PaaS): Provides a platform for building and deploying applications (e.g., databases, programming languages).

Artificial Intelligence (AI)

• AI: Focuses on tasks that require human intelligence, encompassing fields like robotics, natural language processing, and computer vision.
• Machine Learning (ML): A subset of AI that allows computers to learn from data without explicit programming.
• ML Components:
  • Data: The foundation for ML algorithms to learn from.
  • Algorithms: The set of rules or procedures for learning from data.
• ML Types:
  • Supervised Learning: Training with labeled data to make predictions.
  • Generative Learning (Generative AI): Creating new data based on existing information.