2022/05/12 by Catherine Tony, Mohana Balasubramanian, Tony, Catherine +5 · 2 citations
Computer Science · Psychology · #AI in Service Interactions #Cryptography and Security (cs.CR) #Digital Mental Health Interventions #FOS: Computer and information sciences #Human-Computer Interaction (cs.HC) #Open Source Software Innovations #Software Engineering (cs.SE)
paper · pdf · doi:10.48550/arxiv.2205.06200
openalex publication_date 2022/05/12 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/03
Conversational agents or chatbots are widely investigated and used across different fields including healthcare, education, and marketing. Still, the development of chatbots for assisting secure coding practices is in its infancy. In this paper, we present the results of an empirical study on SKF chatbot, a software-development bot (DevBot) designed to answer queries about software security. To the best of our knowledge, SKF chatbot is one of the very few of its kind, thus a representative instance of conversational DevBots aiding secure software development. In this study, we collect and analyse empirical evidence on the effectiveness of SKF chatbot, while assessing the needs and expectations of its users (i.e., software developers). Furthermore, we explore the factors that may hinder the elaboration of more sophisticated conversational security DevBots and identify features for improving the efficiency of state-of-the-art solutions. All in all, our findings provide valuable insights pointing towards the design of more context-aware and personalized conversational DevBots for security engineering.