A Comparative Landscape Analysis of Fitness Functions for Search-Based Testing

Landscape analysis of fitness functions is an important topic. This paper makes an attempt to characterize the search problems associated with the fitness functions used in search-based testing, employing the following measures: diameter, autocorrelation and fitness distance correlation. In a previo...

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Bibliographic Details
Published in:Symbolic and Numeric Algorithms for Scientific Computing, Proceedings pp. 201 - 208
Main Authors: Lefticaru, R., Ipate, F.
Format: Conference Proceeding
Language:English
Published: IEEE 01.09.2008
Subjects:
Algorithm design and analysis
Application software
Automatic testing
finite state machines
fitness functions
Genetic algorithms
landscape analysis
metaheuristic search techniques
Particle swarm optimization
Scientific computing
Search methods
Search problems
search-based testing
Simulated annealing
Software testing
ISBN:0769535232, 9780769535234
Online Access:Get full text
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Summary:Landscape analysis of fitness functions is an important topic. This paper makes an attempt to characterize the search problems associated with the fitness functions used in search-based testing, employing the following measures: diameter, autocorrelation and fitness distance correlation. In a previous work, a general form of objective functions for structural search-based software testing was tailored for state-based testing. A comparison is performed in this paper between the general fitness functions and some problem-specific fitness functions, taking into account their performance with different search methods.
ISBN:0769535232
9780769535234
DOI:10.1109/SYNASC.2008.69