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Efficient Test Generation for Dynamic Behaviors Leveraging Token-Level Input Commonalities

Year: 2025

Type: conference-paper

Abstract: Software in the wild exhibits various computational efforts, such as dynamic behaviors arising from runtime invocations and nondeterministic behaviors introduced by probabilistic algorithms. These efforts complicate software testing because they require meaningful inputs for invocation, introduce additional branching decisions at runtime, and produce divergent outcomes for identical inputs.

DOI: 10.1145/3696630.3728509

Authors: Yuxin Qiu, Qian Zhang

Institution: University of California, Riverside

Language: English

Topic: Software Testing and Debugging Techniques

Subfield: Software

Field: Computer Science

Domain: Physical Sciences

Open Access status: gold

Funders: National Science Foundation, Cisco Systems

Award: Collaborative Research: SHF: Small: Software Developer Tools for Enabling Heterogeneous Computing

OpenAlex ID: W4412704037

FWCI:

Cites: 27

Cited by:

Related to: 10