DocTer: documentation-guided fuzzing for testing deep learning API functions
Danning Xie, Yitong Li, Mijung Kim, Hung Viet Pham, Lin Tan, Xiangyu Zhang, Michael W. Godfrey
Abstract
Input constraints are useful for many software development tasks. For example, input constraints of a function enable the generation of valid inputs, i.e., inputs that follow these constraints, to test the function deeper. API functions of deep learning (DL) libraries have DL-specific input constraints, which are described informally in the free-form API documentation. Existing constraint-extraction techniques are ineffective for extracting DL-specific input constraints.
Topics & Concepts
Fuzz testingComputer scienceDocumentationParsingFunction (biology)Constraint (computer-aided design)Software bugArtificial intelligenceDependency (UML)SoftwareProgramming languageMachine learningData miningMechanical engineeringBiologyEngineeringEvolutionary biologySoftware Engineering ResearchSoftware Testing and Debugging TechniquesWeb Application Security Vulnerabilities