Automating test case generation from Z specifications with Isabelle

Helke, Steffen; Neustupny, Thomas; Santen, Thomas

doi:10.1007/bfb0027283

Cited by 44 publications

(22 citation statements)

References 12 publications

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“…Initially, we considered SMT solvers but it was impossible to find one implementing the Z mathematical toolkit [5]. Our first approach was, then, to use a general theorem prover as suggested in [12]. So, we used Z/EVES to prune testing trees as is described in Sect.…”

Section: Discussion Of the Methodsmentioning

confidence: 99%

“…In this section we compare our work with a first attempt using the Z/EVES proof assistant, with the results reported in [12], and with other similar approaches. The key issues to compare are: the amount of inconsistent test classes that can be pruned automatically; the computing time required to prune; and the amount and simplicity of theorems needed to prune.…”

Section: Comparison With Similar Approachesmentioning

confidence: 98%

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Pruning Testing Trees in the Test Template Framework by Detecting Mathematical Contradictions

Cristiá

Albertengo²,

Monetti³

2010

2010 8th IEEE International Conference on Software Engineering and Formal Methods

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Abstract-Fastest is an automatic implementation of Phil Stocks and David Carrington's Test Template Framework (TTF) [1], a model-based testing (MBT) framework for the Z formal notation. In this paper we present a new feature of Fastest that helps TTF users to eliminate inconsistent test classes automatically. The method is very simple and practical, and makes use of the peculiarities of the TTF. Perhaps its most interesting features are extensibility and ease of use, since it does not assume previous knowledge on theorem proving. Also we compare the solution with a first attempt using the Z/EVES proof assistant and with the HOL-Z environment. At the end, we show the results of an empirical assessment based on applying Fastest to four real-world, industrial-strength case studies and to six toy examples.

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Section: Discussion Of the Methodsmentioning

confidence: 99%

Section: Comparison With Similar Approachesmentioning

confidence: 98%

Pruning Testing Trees in the Test Template Framework by Detecting Mathematical Contradictions

Cristiá

Albertengo²,

Monetti³

2010

2010 8th IEEE International Conference on Software Engineering and Formal Methods

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“…• The use and probation of various test design approaches: using classification trees [18], the Z method [20], or even a combination of the two [32].…”

Section: Validation Of the Test Specificationsmentioning

confidence: 99%

Model based testing of data constraints

Paladi

Arts

2009

Proceedings of the 8th ACM SIGPLAN Workshop on ERLANG

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Correct implementation of data constraints, such as referential integrity constraints and business rules is an essential precondition for data consistency. Though most modern commercial DBMSs support data constraints, the latter are often implemented in the business logic of the applications. This is especially true for non relational DBMS like Mnesia, which do not provide constraints enforcement mechanisms. This case study examines a database application which uses Mnesia as data storage in order to determine, express and test data constraints with Quviq QuickCheck, adopting a model-based testing approach. Some of the important stages of the study described in the article are: reverse engineering of the database, analysis of the obtained database structure diagrams and extraction of data constraint, validation of constraints, formulating the test specifications and finally running the generated test suits. As a result of running the test suits randomly generated by QuickCheck, we have detected several violations of the identified and validated business rules. We have found that the applied methodology is suitable for applications using non relational, unnormalized databases. It is important to note the methodology applied within the case study is not bound to a specific application or DBMS, and can be applied to other database applications.

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“…They developed the well-known DNF approach. Later, Helke et al [21] developed a technique based on the DNF approach for automatically generating test cases from Z specifications. They employed a theorem prover to support generation.…”

Section: Specification-based Test Generationmentioning

confidence: 99%

Software assurance by bounded exhaustive testing

Sullivan

Yang

Coppit

et al. 2004

Proceedings of the 2004 ACM SIGSOFT International Symposium on Software Testing and Analysis

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Abstract-Bounded exhaustive testing (BET) is a verification technique in which software is automatically tested for all valid inputs up to specified size bounds. A particularly interesting case of BET arises in the context of systems that take structurally complex inputs. Early research suggests that the BET approach can reveal faults in small systems with inputs of low structural complexity, but its potential utility for larger systems with more complex input structures remains unclear. We set out to test its utility on one such system. We used Alloy and TestEra to generate inputs to test the Galileo dynamic fault tree analysis tool, for which we already had both a formal specification of the input space and a test oracle. An initial attempt to generate inputs using a straightforward translation of our specification to Alloy did not work well. The generator failed to generate inputs to meaningful bounds. We developed an approach in which we factored the specification, used TestEra to generate abstract inputs based on one factor, and passed the results through a postprocessor that reincorporated information from the second factor. Using this technique, we were able to generate test inputs to meaningful bounds, and the inputs revealed nontrivial faults in the Galileo implementation, our specification, and our oracle. Our results suggest that BET, combined with specification abstraction and factoring techniques, could become a valuable addition to our verification toolkit and that further investigation is warranted.

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Automating test case generation from Z specifications with Isabelle

Cited by 44 publications

References 12 publications

Pruning Testing Trees in the Test Template Framework by Detecting Mathematical Contradictions

Pruning Testing Trees in the Test Template Framework by Detecting Mathematical Contradictions

Model based testing of data constraints

Software assurance by bounded exhaustive testing

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