학술논문

A Parameter Free Choice Function Based Hyper-Heuristic Strategy for Pairwise Test Generation
Document Type
Conference
Source
2017 IEEE International Conference on Software Quality, Reliability and Security Companion (QRS-C) QRS-C Software Quality, Reliability and Security Companion (QRS-C), 2017 IEEE International Conference on. :85-91 Jul, 2017
Subject
Computing and Processing
Testing
Genetic algorithms
Current measurement
Heuristic algorithms
Optimization
Computer security
Search problems
software testing
pairwise testing
hyper-heuristic
meta-heuristic
choice function
Language
Abstract
Hyper-heuristics are advanced high-level search methodologies that solve hard computational problems indirectly via low-level heuristics. Choice function based hyper-heuristics are selection and acceptance hyper-heuristics that use statistical information to rank low-level heuristics for selection. In this paper, we describe a choice function based hyper-heuristic called Pairwise Choice Function based Hyper-heuristic (PCFHH) for the pairwise test generation problem. PCFHH uses a combination of three measures to select and apply an effective low-level heuristic from a set of four low-level heuristics at any stage of the search. Our experimental results have been encouraging as PCFHH outperforms most of pairwise test generation strategies on many of the problem instances.