INTRODUCTION – Final Project and Final Exam
This module will help you develop a final project which will demonstrate your learning proficiency for creating personalized learning paths for developers. This project is intended to catalyze developable skills and knowledge that you have acquired throughout the course to show your ability to personalize learning for developers.
Upon completion of the project, one final examination will be given to students to investigate how well they understand the course. The major points of the course and their applicable knowledge, will be ascertained in this final examination. This is aimed at ensuring that remaining material understood is marked against its practical applications.
FINAL EXAM: GENERATIVE AI FOR SOFTWARE DEVELOPERS
1. What challenge is faced when integrating AI into an established CI toolchain?
- None of the above
- Difficulty in transitioning from traditional CI to AI-driven CI
- Data privacy and security
- Achieving seamless integration (CORRECT)
Correct: That is correct! All organizations having the capability of AI must close gaps in harmony for consistent integration with CI components or workflows by using the existing system.
2. Which company utilizes machine learning for autonomous adjustments in various services?
- Gmail (CORRECT)
- IBM
- Juniper Networks
- Balbix Security Cloud
Correct: You’re exactly right! Gmail works autonomously by making automatic adjustments to the services using machine learning.
3. Which tool utilizes GPT to analyze HTTP requests and responses for detecting vulnerabilities?
- BurpGPT (CORRECT)
- Symantec Endpoint Security
- Sophos Intercept X
- Splunk User Behavior Analytics
Correct: Hooray! BurpGPT is a great tool for using GPT (Generative Pre-trained Transformer) for HTTP request and response analysis for vulnerability detection.
4. What is one major challenge associated with using generative AI in software development?
- The guarantee of privacy and security.
- The lack of creativity and exploration opportunities.
- The potential for bias and inaccuracy in generated outputs. (CORRECT)
- The absence of ethical implications.
Correct: Certainly! A very broad issue with generative AI in software development is the very output bias and possible inaccuracy.
5. Which of these are examples of successful AI-driven apps?
- Netflix and Hulu
- Siri and Alexa (CORRECT)
- TikTok and Instagram
- Facebook and Twitter
Correct: Right! Both Siri and Alexa use artificial intelligence technologies for interpreting and answering user questions, and hence, are exemplary cases of AI-based application.
6. What is one concern associated with generative AI models in software development?
- The need for extensive training data
- The potential for spreading false information (CORRECT)
- The ability to create synthetic vocal recordings
- The requirement to obtain informed consent from users
Correct: It’s correct! Generative AI models can be trained to produce very similar text or content as human beings do.
7. Which of the following is a technique AI-powered code review tools used to analyze source code without executing it and identify potential issues such as coding style violations, unused variables, or memory leaks?
- Automated log analysis
- Predictive debugging
- Static analysis (CORRECT)
- Bug detection
Correct: Indeed! Static analysis is one of the techniques employed by the code review tool developed through Artificial Intelligence for analyzing source code without executing it.
8. What is one of the key capabilities of Large Language Models (LLMs) in software development?
- Code generation and auto-completion (CORRECT)
- Social media analysis
- Image recognition
- Hardware optimization
Correct: That’s right! LLMs actually help coders by generating code, analyzing existing codebases, and completing code to reduce manual effort.
9. Which of the following AI-driven approaches involves applying AI techniques for code refactoring?
- Code analysis
- Code automation
- Anomaly detection
- Design pattern analysis (CORRECT)
Correct: Indeed! These techniques include various AI-led ones for code refactoring, design pattern extraction, architectural trade-offs insights, code suggestions, and bug detection.
10. What feature of AI web builders helps in swiftly creating professional logos.
- AI website generator
- Additional SEO measures
- A text generator
- AI logo maker (CORRECT)
Correct: Absolutely right! The AI logo maker is one of the amazing tools available in AI web builders that helps quickly build professional logos.
11. How does AI contribute to email security, particularly in filtering spam?
- Machine learning and AI algorithms (CORRECT)
- Manually reviewing each email
- Avoiding the use of spam filters
- ignoring potentially harmful content
Correct: That’s right. AI helps identify patterns in emails and flag them as possibly harmful or unwanted content through machine learning algorithms.
12. How can ethical concerns related to NLP technology be addressed?
- By introducing bias intentionally
- By avoiding transparency in algorithm
- By ignoring privacy concern
- By ensuring diversity in training data (CORRECT)
Correct: True! Acse that assures training data diversity is one of the means to tackle ethical issues associated with NLP technologies.
13. Which of the following statements about the use of AI in software testing is true?
- AI techniques are limited to automating test case generation.
- AI algorithms only improve test data generation.
- AI analysis cannot help prioritize test cases based on software quality.
- AI-based techniques enable intelligent test generation and execution of test cases along with other capabilities. (CORRECT)
Correct: Absolutely right! AI-enabled approaches have the capability to generate and execute intelligent test cases for software testing, enhancing efficiency and efficacy to a great extent.
14. Which of the following is a technique used by AI-powered code review tools?
- Social media analysis
- Static analysis (CORRECT)
- Automated log analysis
- Code pattern analysis
Correct: Indeed! Static analysis is a technique, where you analyze the AI-powered code without execution.
15. Which of the following is a role played by AI in CI/CD?
- Bias detection
- Automated Testing and Quality Assurance (CORRECT)
- Manual Code Review
- Predictive debugging
Correct: Absolutely! Automated testing and quality assurance through generative AI in CI/CD enhance the effectiveness and precision of the entire process in software development.
16. What are some challenges associated with using generative AI in software development?
- Limited creativity and exploration options
- Lack of intellectual property protection
- Potential for bias and inaccuracy in generated outputs (CORRECT)
- Low computational power required for training generative AI models
Correct: Absolutely! One of the imperfections of generative artificial intelligence in Software Development is that there could be a degree of bias and inaccuracy in the outputs that it generates.
17. Which of the following is mentioned as an ethical consideration for using generative AI in software development?
- Code automation
- Test case generation
- Bias and Discrimination (CORRECT)
- Speed and efficiency
Correct: Right! Bias and discrimination have indeed vital ethical implications while using generative AI for software development.
18. Which of the following is an example of a generative AI model that excels in language translation tasks?
- Variational autoencoders (VAEs)
- Generative adversarial networks (GANs)
- Transformers (CORRECT)
- Reinforcement learning algorithms
Correct: Great! Transformers are actually a type of generative AI model specially designed for performance in language translation.
19. What is one of the challenges associated with the ethical usage of Large Language Models in software development
- Bias detection (CORRECT)
- Code optimization
- Speed of code generation
- Hardware limitations
Correct: Indeed, LLMs tend to inherit biases from their training data, and it becomes necessary to detect and mitigate such biases as a preventive measure against unfair outcomes in software development.
20. How does AI assists in implementing design patterns in software systems?
- Automating client chat services
- Analyzing code for design patterns (CORRECT)
- Analyzing code for architectural patterns
- Generating high-level architecture
Correct: Yes! Machine learning recognizes code and analyzes the patterns of design patterns. This is done in conjunction with ensuring the consistent and high-quality software systems.
CONCLUSION – Final Project and Final Exam
Finally, this module gives you the great chance to consolidate your learning and demonstrate your ability to create individual learning experiences for developers via the final project. The project is hands-on; the comprehensive knowledge and skills you have acquired can now be used.
At the end of this project, a thorough examination of the final will confirm that you have mastered the important principles and practical applications associated with them in terms of real-life scenarios. Successfully taking the project and exam would therefore give a strong foundation in personalized learning development while comprehensively understanding the content of the course.