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Towards Compositional CLP-based Test Data Generation for Imperative Languages
"... Test data generation (TDG) is the process of automatically generating test-cases for interesting test coverage criteria. The coverage criteria measure how well the program is exercised by a test suite. Examples of coverage criteria are: statement coverage which requires that each line of the code is ..."
Abstract
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Test data generation (TDG) is the process of automatically generating test-cases for interesting test coverage criteria. The coverage criteria measure how well the program is exercised by a test suite. Examples of coverage criteria are: statement coverage which requires that each line of the code is executed; path coverage which
Under consideration for publication in Theory and Practice of Logic Programming 1 Test Case Generation for Object-Oriented Imperative Languages in CLP
"... Testing is a vital part of the software development process. Test Case Generation (TCG) is the process of automatically generating a collection of test-cases which are applied to a system under test. White-box TCG is usually performed by means of symbolic execution, i.e., instead of executing the pr ..."
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Testing is a vital part of the software development process. Test Case Generation (TCG) is the process of automatically generating a collection of test-cases which are applied to a system under test. White-box TCG is usually performed by means of symbolic execution, i.e., instead of executing the program on normal values (e.g., numbers), the program is executed on symbolic values representing arbitrary values. When dealing with an objectoriented (OO) imperative language, symbolic execution becomes challenging as, among other things, it must be able to backtrack, complex heap-allocated data structures should be created during the TCG process and features like inheritance, virtual invocations and exceptions have to be taken into account. Due to its inherent symbolic execution mechanism, we pursue in this paper that Constraint Logic Programming (CLP) has a promising application field in TCG. We will support our claim by developing a fully CLP-based framework to TCG of an OO imperative language, and by assessing it on a corresponding implementation on a set of challenging Java programs.
Resource-driven CLP-based Test Case Generation
"... Abstract. Test Data Generation (TDG) aims at automatically obtaining test inputs which can then be used by a software testing tool to validate the functional behaviour of the program. In this paper, we propose resource-aware TDG, whose purpose is to generate test cases (from which the test inputs ar ..."
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Abstract. Test Data Generation (TDG) aims at automatically obtaining test inputs which can then be used by a software testing tool to validate the functional behaviour of the program. In this paper, we propose resource-aware TDG, whose purpose is to generate test cases (from which the test inputs are obtained) with associated resource consumptions. The framework is parametric w.r.t. the notion of resource (it can measure memory, steps, etc.) and allows using software testing to detect bugs related to non-functional aspects of the program. As a further step, we introduce resource-driven TDG whose purpose is to guide the TDG process by taking resource consumption into account. Interestingly, given a resource policy, TDG is guided to generate test cases that adhere to the policy and avoid the generation of test cases which violate it. 1
jPET: an Automatic Test-Case Generator for Java
"... Abstract—We present jPET, a whitebox test-case generator (TCG) which can be used during software development of Java applications within the Eclipse environment. jPET builds on top of PET, a TCG which automatically obtains test-cases from the bytecode associated to a Java program. jPET performs reve ..."
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Abstract—We present jPET, a whitebox test-case generator (TCG) which can be used during software development of Java applications within the Eclipse environment. jPET builds on top of PET, a TCG which automatically obtains test-cases from the bytecode associated to a Java program. jPET performs reverse engineering of the test-cases obtained at the bytecode level by PET in order to yield this information to the user at the source code level. This allows understanding the information gathered at the lower level and using it to test source Java programs. I.

