FSE 2026
Sun 5 - Thu 9 July 2026 Montreal, Canada
Tue 7 Jul 2026 16:00 - 16:20 at MB 5.215 - Test generation 2 Chair(s): Ezekiel Soremekun

A type checker must reject ill-typed programs in addition to accepting well-typed programs. Negative type checker tests, programs expected to be rejected, validate that a type checker enforces the language’s typing rules as intended. We focus on negative type checker tests for P4, a domain-specific language for programmable network devices, whose type system encodes design principles and hardware constraints of the network dataplane. Failing to reject an ill-typed P4 program risks violating these principles and constraints, leading to unexpected errors. A comprehensive negative test suite covering subtle and diverse ill-typed conditions is thus important. However, constructing comprehensive negative tests is challenging: the negative input space lacks systematic characterization, and existing P4 program generators do not target subtle type errors.

This paper addresses the problem in three steps. (i) We mechanize the P4 type system using the SpecTec framework. Unlike the informal official P4 specification, the mechanized type system is formal and machine-readable. Mechanization enables a systematic analysis of the type system. (ii) Across the mechanized type system, we identify dangling premises, which are premises in the typing rules that, when violated, cause type errors. Based on them, we propose dangling coverage, a novel metric for quantifying negative test coverage. (iii) Finally, we implement a coverage-guided fuzzer that mutates well-typed P4 programs into ill-typed programs that increase dangling coverage. Our method identifies 939 dangling premises that characterize distinct ill-typed conditions in the P4 type system. The fuzzer generates a negative test suite achieving 33.02%p higher dangling coverage than the existing P4C reference compiler’s test suite. The generated tests also reveal 29 previously unknown bugs in the compiler frontend, demonstrating the effectiveness of both the coverage metric and the fuzzer. The tests generated by our fuzzer are now integrated into the P4C test suite.

Tue 7 Jul

Displayed time zone: Eastern Time (US & Canada) change

16:00 - 17:30
Test generation 2Tool Demonstrations / Journal-First Paper / Research Papers at MB 5.215
Chair(s): Ezekiel Soremekun Singapore University of Technology and Design
16:00
20m
Talk
Failing with Purpose: Dangling Coverage-Guided Negative Test Generation from a Mechanized P4 Type System
Research Papers
16:20
10m
Talk
Argus: A Guided and Traceable Mutation Testing Engine
Tool Demonstrations
Zi Yang University of California, Riverside, Zhaorui Yang University of California, Riverside, Jiyuan Wang Tulane University, Qian Zhang University of California at Riverside
16:30
20m
Talk
Evaluating LLM-based Regression Test Generation
Research Papers
Jing Liu Max Planck Institute for Security and Privacy, Seongmin Lee UCLA, Eleonora Losiouk University of Padua, Marcel Böhme MPI for Security and Privacy
DOI Pre-print File Attached
16:50
20m
Talk
TestLoop: A Process Model Describing Human-in-the-Loop Software Test Suite Generation
Journal-First Paper
Matthew C. Davis Carnegie Mellon University, Sangheon Choi Rose-Hulman Institute of Technology, Amy Wei University of Michigan, Sam Estep Carnegie Mellon University, Brad A. Myers Carnegie Mellon University, Joshua Sunshine Carnegie Mellon University
Link to publication DOI
17:10
20m
Talk
MR-Coupler: Automated Metamorphic Test Generation via Functional Coupling Analysis
Research Papers
Congying Xu The Hong Kong University of Science and Technology, China, Hengcheng Zhu The Hong Kong University of Science and Technology, Songqiang Chen The Hong Kong University of Science and Technology, Jiarong Wu , Valerio Terragni University of Auckland, Shing-Chi Cheung Hong Kong University of Science and Technology
Pre-print