Re-using generators of complex test data

• The efficiency of random testing can be improved by sampling test inputs using a generating program that incorporates knowledge about the types of input most likely to detect faults in the software-under-test (SUT). But when the input of the SUT is a complex data type - such as a domain-specific string, array, record, tree, or graph - creating such a generator may be time- consuming and may require the tester to have substantial prior experience of the domain. In this paper we propose the re-use of generators created for one SUT on other SUTs that take the same complex data type as input. The re-use of a generator in this way would have little overhead, and we hypothesise that the re-used generator will typically be as least as efficient as the most straightforward form of random testing: sampling test inputs from the uniform distribution. We investigate this proposal for two data types using five generators. We assess test efficiency against seven real-world SUTs, and in terms of both structural coverage and the detection of seeded faults. The results support the re-use of generators for complex data types, and suggest that if a library of generators is to be maintained for this purpose, it is possible to extend library generators to accommodate the specific testing requirements of newly-encountered SUTs. © 2015 IEEE.

Ämnesord

NATURVETENSKAP  -- Data- och informationsvetenskap -- Programvaruteknik (hsv//swe)

NATURAL SCIENCES  -- Computer and Information Sciences -- Software Engineering (hsv//eng)

Nyckelord

Testing; Trees (mathematics); Verification

Domain specific; Library generators; Prior experience; Random testing; Sampling test; Test efficiency; Testing requirements; Uniform distribution

Software testing

Publikations- och innehållstyp

ref (ämneskategori)

kon (ämneskategori)