Key Skills

Job Description

A clear understanding of requirements is essential for effective software engineering. As AI becomes more integrated into development workflows, its ability to support developers in understanding and clarifying requirements becomes increasingly important. This master’s thesis explores how context-driven AI can help developers identify missing information and ask relevant questions before development begins. Artificial Intelligence is increasingly integrated into software engineering and DevOps workflows. However, the effectiveness of AI-assisted development is often limited by incomplete, ambiguous, or poorly specified requirements. Service requests, change requests and development tasks frequently lack essential contextual information, forcing developers and AI systems to make assumptions. Incorrect assumptions can result in rework, reduced software quality, increased development effort and lower trust in AI-assisted workflows. Although research has explored requirements elicitation and clarification techniques, it remains unclear how AI-driven questioning strategies can systematically improve requirement completeness and reduce downstream rework in practical software engineering environments. The challenge is to determine how AI systems can proactively identify missing information and help developers ask the most relevant clarification questions based on the type and context of a request. The Assignment Your task is to explore to what extent context-driven AI can be used to effectively guide developers in asking relevant questions and clarifying requirements. Previous research has investigated the use of LLMs for detecting and explaining ambiguities in software requirements, showing that contextual information and relevant examples can improve ambiguity detection. More recent work has also explored LLM-driven clarification and conversational requirements elicitation, but effectively determining which clarification questions should be asked based on the context of a development request remains an active research area. About Info Support Info Support specializes in custom software, data/AI solutions, management, and training and is active in the Finance, Industry, Agriculture, Food & Retail, Mobility & Public, and Healthcare sectors. We provide solid and innovative solutions for complex and critical software issues. Our headquarters are located in Veenendaal (NL) and Mechelen (BE). At present, approximately 500 employees are employed by Info Support. Info Support’s working method is characterized by a number of core values: solidity, integrity, craftsmanship, and passion. These core values are intertwined in our work and the way we interact with each other. To ensure that all employees are always up to date with the latest developments, Info Support has an in-house IT Academy that eagerly satisfies the hunger for more or different knowledge and skills. B2 language proficiency in Dutch is required.

Core Responsibilities

Explore how context-driven AI can help developers identify missing information in development requests and ask relevant clarification questions. Investigate whether AI-driven questioning can improve requirement completeness and reduce rework in software engineering.

Requirements

The role is a master's thesis internship focused on AI-assisted requirements engineering and software development. Dutch proficiency at B2 level is required.