IPOG: A General Strategy for T-Way Software Testing

Abstract

Most existing work on t-way testing has focused on 2-way (or pairwise) testing, which aims to detect faults caused by interactions between any two parameters. However, faults can also be caused by interactions involving more than two parameters. In this paper, we generalize an existing strategy, called In-Parameter-Order (IPO), from pairwise testing to t-way testing. A major challenge of our generalization effort is dealing with the combinatorial growth in the number of combinations of parameter values. We describe a t-way testing tool, called FireEye, and discuss design decisions that are made to enable an efficient implementation of the generalized IPO strategy. We also report several experiments that are designed to evaluate the effectiveness of FireEye.

Interaction Coverage Meets Path Coverage by SMT Constraint Solving

“…for the closure check, which only needs to be performed on those interactions which have new solutions, and only at the end of each partition processing. (5,6), (4,6), (0,7), (2,3), (2,8), (1,5,8 (4,20), (15,19), (8,20), (7,14 Many tools [3,4,5,17] are available to generate t-wise CIT samples, where t is fixed between all parameter interactions, and is usually equal to 2 or 3. Some of these are also able to handle certain types of constraints expressed as "exclusions": specific value combinations that must not occur in the sample.…”

“…In most of this work the focus has been to construct a CIT sample using a model that has a single interaction strength across all parameters of the problem. Two primary algorithm types have been used for CIT sample generation -greedy methods [3,8,17] and meta-heuristic search [4,5]. Other techniques use direct or recursive mathematical constructions (see [15] for a survey).…”

Cumulative interaction strength for T-way Test data Generator (TTG)

“…GMIPOG is a combinatorial test generator based on specified inputs and parameter interaction. Running on a Grid environment, GMIPOG adopts both the horizontal and vertical extension mechanism (i.e., similar to that of IPOG [3]) in order to derive the required test suite for a given interaction strength [9]. GMIPOG supports high degree of interaction and can be run in cumulative mode (i.e., support one-test-at-a-time approach with the capability to vary t automatically until the exhaustive testing is reached) [9].…”

“…More recently, several strategies have been developed on in the past (e.g., IPOG [3], MIPOG [4], GMIPOG [5] and TTG [6]) that can generate test suite for high degree interaction (2 previous work associated with cumulative interaction in order to facilitate the characteristics of cumulative T-way strategy.…”

Comparative Benchmarking of Constraints T-Way Test Generation Strategy Based on Late Acceptance Hill Climbing Algorithm

“…In general, existing t-way strategies can be categorized into two categories, that is, algebraic approaches or computational approaches respectively (Lei, Kacker et al 2007).…”