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Extending Category Partition's B ase C hoice criterion to better support constraints
Author(s) -
Khalsa Sunint Kaur,
Labiche Yvan
Publication year - 2018
Publication title -
journal of software: evolution and process
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.371
H-Index - 29
eISSN - 2047-7481
pISSN - 2047-7473
DOI - 10.1002/smr.1868
Subject(s) - base (topology) , partition (number theory) , set (abstract data type) , computer science , mathematical optimization , choice set , mathematics , econometrics , mathematical analysis , combinatorics , programming language
To ensure software is performing as intended, it can be black‐box or white‐box tested. Category partition is a black‐box, specification‐based testing technique that begins by identifying the parameters, categories (characteristics of parameters), and choices (acceptable values for categories). These choices are then combined to form test frames on the basis of various criteria such as Base Choice and Each Choice. To ensure that the combinations of choices are feasible, constraints on choices are introduced. Combining choices, while accounting for constraints, to form an each choice adequate test set is feasible (eg, using constrained covering arrays from combinatorial testing). However, the Base Choice criterion has not been defined to specifically account for constraints on choices, resulting in adverse consequences. In this paper, we introduce two extensions to the Base Choice criterion, namely, Constrained Base Choice and Extended Constrained Base Choice to specifically account for (complex) constraints on choices. We use a number of academic and industrial case studies to compare different adequacy criteria, including the new ones, in terms of cost and effectiveness at finding faults. Results show the performance of the new criteria equivalent to a 3‐way combination criterion with a much smaller cost.