CAIN 2024
Sun 14 - Mon 15 April 2024 Lisbon, Portugal
co-located with ICSE 2024
Mon 15 Apr 2024 14:30 - 14:40 at Pequeno Auditório - LLMs and Testing Chair(s): Roland Weiss

Large language models (LLMs) enable state-of-the-art semantic capabilities to be added to software systems such as semantic search of unstructured documents and text generation. However, these models are computationally expensive. At scale, the cost of serving thousands of users increases massively affecting also user experience. To address this problem, semantic caches are used to check for answers to similar queries (that may have been phrased differently) without hitting the LLM service. Due to the nature of these semantic cache techniques that rely on query embeddings, there is a high chance of errors impacting user confidence in the system. Adopting semantic cache techniques usually requires testing the effectiveness of a semantic cache (accurate cache hits and misses) which requires a labelled test set of similar queries and responses which is often unavailable.

In this paper, we present VaryGen, an approach for using LLMs for test input generation that produces similar questions from unstructured text documents. Our novel approach uses the reasoning capabilities of LLMs to 1) adapt queries to the domain, 2) synthesise subtle variations to queries, and 3) evaluate the synthesised test dataset. We evaluated our approach in the domain of a student question and answer system by qualitatively analysing 100 generated queries and result pairs, and conducting an empirical case study with an opensource semantic cache. Our results show that query pairs satisfy human expectations of similarity and our generated data demonstrates failure cases of a semantic cache. Additionally, we also evaluate our approach on Qasper dataset. This work is an important first step into test input generation for semantic applications and presents considerations for practitioners when calibrating a semantic cache.

Mon 15 Apr

Displayed time zone: Lisbon change

14:00 - 15:30
14:00
15m
Talk
A Combinatorial Testing Approach to Hyperparameter OptimizationDistinguished paper Award Candidate
Research and Experience Papers
Krishna Khadka The University of Texas at Arlington, Jaganmohan Chandrasekaran Virginia Tech, Jeff Yu Lei University of Texas at Arlington, Raghu Kacker National Institute of Standards and Technology, D. Richard Kuhn National Institute of Standards and Technology
14:15
15m
Talk
Mutation-based Consistency Testing for Evaluating the Code Understanding Capability of LLMs
Research and Experience Papers
Ziyu Li University of Sheffield, Donghwan Shin University of Sheffield
14:30
10m
Talk
LLMs for Test Input Generation for Semantic Applications
Research and Experience Papers
Zafaryab Rasool Applied Artificial Intelligence Institute, Deakin University, Scott Barnett Applied Artificial Intelligence Institute, Deakin University, David Willie Applied Artificial Intelligence Institute, Deakin University, Stefanus Kurniawan Deakin University, Sherwin Balugo Applied Artificial Intelligence Institute, Deakin University, Srikanth Thudumu Deakin University, Mohamed Abdelrazek Deakin University, Australia
14:40
10m
Talk
(Why) Is My Prompt Getting Worse? Rethinking Regression Testing for Evolving LLM APIs
Research and Experience Papers
MA Wanqin The Hong Kong University of Science and Technology, Chenyang Yang Carnegie Mellon University, Christian Kästner Carnegie Mellon University
14:50
10m
Talk
Welcome Your New AI Teammate: On Safety Analysis by Leashing Large Language Models
Research and Experience Papers
Ali Nouri Volvo cars & Chalmers University of Technology, Beatriz Cabrero-Daniel University of Gothenburg, Fredrik Torner Volvo cars, Hakan Sivencrona Zenseact AB, Christian Berger Chalmers University of Technology, Sweden
15:00
10m
Talk
ML-On-Rails: Safeguarding Machine Learning Models in Software Systems – A Case Study
Research and Experience Papers
Hala Abdelkader Applied Artificial Intelligence Institute, Deakin University, Mohamed Abdelrazek Deakin University, Australia, Scott Barnett Applied Artificial Intelligence Institute, Deakin University, Jean-Guy Schneider Monash University, Priya Rani RMIT University, Rajesh Vasa Deakin University, Australia
15:10
20m
Live Q&A
Test - Q&A Session
Research and Experience Papers