A new structural coverage criterion for dynamic detection of program invariants

Gupta, Neelam; Heidepriem, Zachary V.

doi:10.1109/ase.2003.1240294

Cited by 26 publications

(34 citation statements)

References 10 publications

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“…The test suites built with this method proved to be appropriate for dynamic contract inference techniques. Previous authors using dynamic techniques have stated that test suites produced with random-test generation are unsuitable for contract inference [10,14]. Our own experience shows otherwise in the case of programs that are already equipped with a few simple contract elements, with the goal of inferring additional, more sophisticated assertions.…”

Section: Test Suite Generationmentioning

confidence: 90%

Inferring better contracts

Wei

Furia

Kazmin

et al. 2011

Proceedings of the 33rd International Conference on Software Engineering

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Considerable progress has been made towards automatic support for one of the principal techniques available to enhance program reliability: equipping programs with extensive contracts. The results of current contract inference tools are still often unsatisfactory in practice, especially for programmers who already apply some kind of basic Design by Contract discipline, since the inferred contracts tend to be simple assertions-the very ones that programmers find easy to write. We present new, completely automatic inference techniques and a supporting tool, which take advantage of the presence of simple programmer-written contracts in the code to infer sophisticated assertions, involving for example implication and universal quantification.Applied to a production library of classes covering standard data structures such as linked lists, arrays, stacks, queues and hash tables, the tool is able, entirely automatically, to infer 75% of the complete contracts-contracts yielding the full formal specification of the classes-with very few redundant or irrelevant clauses.

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Section: Test Suite Generationmentioning

confidence: 90%

Inferring better contracts

Wei

Furia

Kazmin

et al. 2011

Proceedings of the 33rd International Conference on Software Engineering

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show abstract

“…Gupta and Heidepriem propose a new structural coverage criterion called invariant-coverage criterion for dynamic detection of program invariants [18]. Their experimental results showed that invariant-coverage test suites could effectively augment branch coverage and definition-use pair coverage test suites to remove spurious inferred invariants.…”

Section: Operational-abstraction-based Testingmentioning

confidence: 99%

Tool-assisted unit-test generation and selection based on operational abstractions

Xie

Notkin

2006

Autom Software Eng

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Abstract. Unit testing, a common step in software development, presents a challenge. When produced manually, unit test suites are often insufficient to identify defects. The main alternative is to use one of a variety of automatic unit-test generation tools: these are able to produce and execute a large number of test inputs that extensively exercise the unit under test. However, without a priori specifications, programmers need to manually verify the outputs of these test executions, which is generally impractical. To reduce this cost, unit-test selection techniques may be used to help select a subset of automatically generated test inputs. Then programmers can verify their outputs, equip them with test oracles, and put them into the existing test suite. In this paper, we present the operational violation approach for unit-test generation and selection, a black-box approach without requiring a priori specifications. The approach dynamically generates operational abstractions from executions of the existing unit test suite. These operational abstractions guide test generation tools to generate tests to violate them. The approach selects those generated tests violating operational abstractions for inspection. These selected tests exercise some new behavior that has not been exercised by the existing tests. We implemented this approach by integrating the use of Daikon (a dynamic invariant detection tool) and Parasoft Jtest (a commercial Java unit testing tool), and conducted several experiments to assess the approach.

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“…We note the existence of many active research projects on generating high-coverage test inputs and efficient test suites. In particular, we can take advantage of an entire body of work on generating test suites specifically for dynamic invariant detection [29]- [31].…”

Section: Threats To Validitymentioning

confidence: 99%