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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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Performance Data Collection of MES PHARIS
Oháňka, Martin ; Hruška, Martin (referee) ; Smrčka, Aleš (advisor)
This master's thesis deals with monitoring of automated tasks on integration servers and obtaining data from these tasks. Another area of this work is performance testing and to obtain information about hardware utilization from it. Thanks to this, it is possible to perform performance analysis of the implemented solution from different performance perspectives. The result of this master's thesis is a software solution that can obtain data about tasks from DevOps and Jenkins integration servers. In the area of performance testing, there is created a solution for parallel execution of tasks. The output of this work an output passed in JSON format. The data is then transferred to the Elastic platform, specifically Logstash, where it is subsequently visualized using Kibana. The Beat platform is used to collect data from performance testing. The solution was applied to the production information system MES PHARIS of the UNIS company.
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Performance Data Collection of MES PHARIS
Oháňka, Martin ; Hruška, Martin (referee) ; Smrčka, Aleš (advisor)
This master's thesis deals with monitoring of automated tasks on integration servers and obtaining data from these tasks. Another area of this work is performance testing and to obtain information about hardware utilization from it. Thanks to this, it is possible to perform performance analysis of the implemented solution from different performance perspectives. The result of this master's thesis is a software solution that can obtain data about tasks from DevOps and Jenkins integration servers. In the area of performance testing, there is created a solution for parallel execution of tasks. The output of this work an output passed in JSON format. The data is then transferred to the Elastic platform, specifically Logstash, where it is subsequently visualized using Kibana. The Beat platform is used to collect data from performance testing. The solution was applied to the production information system MES PHARIS of the UNIS company.
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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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