Performance Testing and Assessment of Various Network-Based Applications

University essay from Blekinge Tekniska Högskola/Institutionen för datavetenskap

Abstract: Performance Testing is one of the crucial parts of any software cycle process. In today’s world, there is any number of network-based applications. Manual Testing and Automated Testing are the two important ways to test any type of application. For Manual Testing a mobile application known as BlekingeTrafiken is used. For Automated Testing, a web application known as Edmodo is used. Selenium is the automated tool included for automated testing. But, for each application, there are several users and because of that, there might be a decrease in performance of the application as an increase in the number of users. Performance of an application also depends on response times, mean, stability, speed, capacity, accuracy. The performance also depends on the device (memory consumption, battery, software variation) and Server/API (less no of calls) and depends on the network performance (jitters, packet loss, network speed). There are several tools for performance testing. By using these tools, we can get accurate performance results of each request.  In this thesis, we performed manual testing of a mobile application by increasing the number of users under similar network conditions, automated testing of a web application under various test cases and tested the performance of an iPad application (PLANETJAKTEN). It is a real-time gaming application used to learn mathematics for children. Apache JMeter is the tool used for performance testing. The interaction between the JMeter tool and the iPad is done through HTTP Proxy method. When any user starts using the application, we can measure the performance of each request sent by the user. Nagios is the tool used to monitor the various environments. Results show that for manual testing, the time taken for connecting to WI-FI is low compared to opening and using the application. For automated testing, it is found that the time taken to run each test case for the first time is high compared to the remaining trials. For performance testing, the experimental results show that the error percentage (the percentage of failed requests) is high for logging into the application compared to using the application. 

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