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Automated Detection of Types in Data Structures
Oháňka, Martin ; Hruška, Martin (referee) ; Smrčka, Aleš (advisor)
This bachelor's thesis deals with data structure synthesis for software testing. In particular, the thesis focuses on analysis of real data in order to detect data types for further test data generation. Data analysis is performed in two layers: a control system for scheduling and invoking partial detections, and a set of data detectors. The thesis deals with analysis and implementation of tool consisting of set of data type detectors over tree structured data like JSON, YAML, or XML. The goal of the detectors is to determine a semantics of values of analysed structure and dependencies between data. The set can be easily expanded as needed, to detect even more complicated meanings and dependencies. The results of these analysis can be used to generate new test data for software testing.
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Automatic Test Input Generation for Information Systems
Naňo, Andrej ; Fiedor, Tomáš (referee) ; Smrčka, Aleš (advisor)
ISAGENis a tool for the automatic generation of structurally complex test inputs that imitate real communication in the context of modern information systems . Complex, typically tree-structured data currently represents the standard means of transmitting information between nodes in distributed information systems. Automatic generator ISAGENis founded on the methodology of data-driven testing and uses concrete data from the production environment as the primary characteristic and specification that guides the generation of new similar data for test cases satisfying given combinatorial adequacy criteria. The main contribution of this thesis is a comprehensive proposal of automated data generation techniques together with an implementation, which demonstrates their usage. The created solution enables testers to create more relevant testing data, representing production-like communication in information systems.
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Automatic Test Input Generation for Information Systems
Naňo, Andrej ; Fiedor, Tomáš (referee) ; Smrčka, Aleš (advisor)
ISAGENis a tool for the automatic generation of structurally complex test inputs that imitate real communication in the context of modern information systems . Complex, typically tree-structured data currently represents the standard means of transmitting information between nodes in distributed information systems. Automatic generator ISAGENis founded on the methodology of data-driven testing and uses concrete data from the production environment as the primary characteristic and specification that guides the generation of new similar data for test cases satisfying given combinatorial adequacy criteria. The main contribution of this thesis is a comprehensive proposal of automated data generation techniques together with an implementation, which demonstrates their usage. The created solution enables testers to create more relevant testing data, representing production-like communication in information systems.
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|
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Automated Detection of Types in Data Structures
Oháňka, Martin ; Hruška, Martin (referee) ; Smrčka, Aleš (advisor)
This bachelor's thesis deals with data structure synthesis for software testing. In particular, the thesis focuses on analysis of real data in order to detect data types for further test data generation. Data analysis is performed in two layers: a control system for scheduling and invoking partial detections, and a set of data detectors. The thesis deals with analysis and implementation of tool consisting of set of data type detectors over tree structured data like JSON, YAML, or XML. The goal of the detectors is to determine a semantics of values of analysed structure and dependencies between data. The set can be easily expanded as needed, to detect even more complicated meanings and dependencies. The results of these analysis can be used to generate new test data for software testing.
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