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HKU Scholars Hub
Article . 2008
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In black and white

an integrated approach to class-level testing of object-oriented programs
Authors: Chan, FT; Tse, TH; Chen, TY; Chen, HY;

In black and white

Abstract

Because of the growing importance of object-oriented programming, a number of testing strategies have been proposed. They are based either on pure black-box or white-box techniques. We propose in this article a methodology to integrate the black- and white-box techniques. The black-box technique is used to select test cases. The white-box technique is mainly applied to determine whether two objects resulting from the program execution of a test care are observationally equivalent. It is also used to select test cases in some situations. We define the concept of a fundamental pair as a pair of equivalent terms that are formed by replacing all the variables on both sides of an axiom by normal forms. We prove that an implementation is consistent with respect to all equivalent terms if and only if it is consistent with respect to all fundamental pairs. In other words, the testing coverage of fundamental pairs is as good as that of all possible term rewritings, and hence we need only concentrate on the testing of fundamental pairs. Our strategy is based on mathematical theorems. According to the strategy, we propose an algorithm for selecting a finite set of fundamental pairs as test cases. Given a pair of equivalent terms as a test case, we should then determine whether the objects that result from executing the implemented program are observationally equivalent. We prove, however, that the observational equivalence of objects cannot be determined using a finite set of observable contexts (which are operation sequences ending with an observer function) derived from any black-box technique. Hence we supplement our approach with a “relevant observable context” technique, which is a heuristic white-box technique to select a relevant finite subset of the set of observable contexts for determining the observational equivalence. The relevant observable contezxts are constructed from a data member relevance graph (DRG), which is an abstraction of the given implementation for a given specificatin. A semiautomatic tool hass been developed to support this technique.

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Keywords

Languages, 005, D.3.2 [Programming Languages]: Language Classifications - object-oriented languages, D.2.5 [Software Engineering]: Testing and Debugging - test data generators, D.2.1 [Software Engineering]: Requirements/Specifications-languages, Algorithms

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    popularity
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    Top 10%
    influence
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    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
111
Top 10%
Top 1%
Top 10%
Green
hybrid