THESIS: AI Imposter validation

High level descriptionModern data engineering faces unprecedented challenges as organizations increasingly deploy IoT devices and edge computing infrastructure that generate massive volumes of distributed data.Traditional centralized data processing approaches struggle with the latency, bandwidth, and reliability constraints inherent in edge-to-cloud data...

BackgroundIn today's digital landscape, services and offerings are increasingly composed of multiple interconnected applications and systems. This complexity makes it difficult to trace which services are tied to a specific customer identifier and to detect issues such as failed orders or recurring system errors.Traditionally, support and operations teams...

High level descriptionWith the rising amount of AI agents (ChatGPT, OpenAI, Grok, Microsoft CoPilot, Google Gemini, …), it becomes more difficult to know which AI agent to use in different contexts. Some agents might not be fact based enough with no access to real time data, others are easily manipulated by the user, others might provide propaganda due to...

High level descriptionAI agents in Customer Success can streamline documentation by automatically capturing key insights from customer interactions and updating knowledge bases with accurate, easy-to-find content. They can analyze large sets of customer data to identify trends, summarize findings, and prepare structured updates. For monthly reporting, AI...

High level descriptionThis project examines the application of artificial intelligence in translating change requests into automated test cases by referencing software interface descriptions, aiming to enhance verification coverage and overall software quality.Who are we looking for?Bachelor/Master of Science in Computer Science/EngineeringProject...

High level descriptionEffort and time estimation remain among the most challenging aspects of software engineering. Despite decades of research, human estimates are still often uncertain and inconsistent.With the rise of advanced AI assistants and code-generating tools such as GitHub Copilot, ChatGPT, Amazon CodeWhisperer, and similar systems, new...

High level descriptionGenerative AI is increasingly used in software development to write code, tests and suggest solutions. This increases productivity but at the cost of several risks, one being security. The AI tools being used may generate code that contains vulnerabilities, reproduce insecure patterns from training data, or create a false sense of...

AbstractManaging third-party dependencies is critical for software security, yet existing tools such as Dependabot treat all version updates and reported vulnerabilities as equally urgent. This lack of prioritization leads to alert fatigue and wasted developer effort. This thesis explores how AI can make dependency risk management more contextual and...

High level descriptionWith the rising popularity of AI agents, Anthropic has developed a new protocol for LLM models to communicate with tools. The Model Context Protocol (MCP) is slowly becoming a standard for developing tools for LLMs and LLM Agents. In MCP there are no security or authentication methods, so exposing tools towards end users can be harmful...

High Level Description Med ökande automatisering inom industrin och den snabba utvecklingen av AI-teknologier ökar behovet av smartare och mer effektiva underhållsstrategier. Traditionella metoder för underhåll är ofta ineffektiva, kostsamma eller leder till oväntade driftstopp.Detta examensarbete fokuserar på att undersöka hur AI och...