1. Introduction
User acceptence testing is important to analyze whether the application is effective to meet requirements of the users. The current assignment deals with analysis of the data conversion , determining the test environment and deciding the performance testing techniques.
2. User acceptance testing plans
The data conversion is important for application testing. It takes place in several stages:
Determining the amount of data going to be converted: Each application deals with different amount of data. So, it is necessary to decide how much data needs to be converted for the specific application.
2.2 Mapping the data into fields
All the codes and tables of the application needs to be mapped to the test environment. In addition to the mapping, it is necessary to realize how the codes are being impacted in the test environment.
2.3 Exporting the data
The data can be exported either using SQR (structured query report). Application Engine is another method of data exporting, but it reduces the coding flexibility (Chen, 2015). On the other hand, SQR allow the experts to gain control over the codes and also can take user inputs. Therefore in this case, SQR it will be used, as it provides more flexibility and enable the users to modify the system as per their requirements.
3. Describing the test environment, hardware requirements and personnel involved
For carrying out the User Acceptance Tests, setting up the right environment is necessary (Lewis, 2016). Unless the test is carried out in the same environment where the application would be used, getting accurate results is not possible. Nature of hardware used to access the application plays a key role to influence its performance. Therefore, before undertaking the test, it should be ensured that the test environment consists of all types of hardware which are associated with the application.
The performance of a business enterprise application depends significantly on the memory, disk storage and processors trough which the application is being used (Just, et al.2014). Therefore, the performance of the application needs to be tested in different memory , storage and disk configuration.
Configuration of the server machines and load machines also influence the application performance to a great extent (Harman et al. 2015). So, the application requires being tested using the server machines and load machines of different configuration. The nature of network used to access the application impacts its performance to a great extent. Therefore, the test environment should include different types of networks configuration also.
Not only the hardware, the server software and nature of browser also impact the application performance significantly (Choudhury et al.2017). The test environment should include different types of server software and browsers also for analyzing performance of the application.
The user acceptance tests are done to analyze whether the application is able to meet the requirements of the users. So, the users of the business enterprise application take the leading role in testing the application. However, working with other stakeholders such as the project sponsor, developers is also necessary to modify the application effectively.
4. Methods and procedures for testing
Performance testing is a non-functional testing. The performance testing is carried out to analyze the stability and responsiveness of the system using different system parameters. The performance testing also helps experts to understand to want extent the system is effective to perform under various workloads. A number of system parameters is analyzed through performance testing including usage of the resources, scalability and reliability.
Load testing is one of the simplest forms of performance testing (Zogaj et al. 2014). In this case, the system is kept under a load and then how the system is behaving is observed. Use of load testing of a business enterprise application helps the organization to understand how the application responds to the critical load of application server and the database. The load testing can be carried out in several consecutive stages. The procedure for load testing is as follows:
4.2 Setting the test environment
Setting the proper test environment is important to enhance reliability and repeatability of the tests. In case of load testing also at first the test environment needs to be prepared.
4.3 Determining the test scenarios
The aim of load testing is to understand how the system performs under the business environment. Therefore, before load testing it is necessary to identify the types of loads to which the application would be exposed most of the times. The number of users for the system requires being predicted to prepare the test scenarios.
Determining the nature of data that is going to be processed by the system is another critical factor for the preparation of test scenario. The performance of an enterprise application may vary depending upon the connection line and the nature of device from which it is being accessed (Jorgensen, 2016). Therefore, it also needs to be considered while determining the test scenarios.
4.4 Test scenario execution and monitoring
The next stage deals with monitoring the performance of the application under test scenario and collecting the metrics like response time If the system is not found satisfactory, recommendations will be created.
4.5 Fine tuning and re-testing the system
The next phase deals with fine-tuning the application according to the recommendations and re- testing the application until it gives the desired result. While developing a business enterprise application, it is necessary to know the maximum capacity of the system. However, stress testing is done to understand the responses of the application if the load increases than it was expected.
In addition to knowing performance of the business under high load, it is also necessary to know how the application can respond under the continuous load (Orso & Rothermel, 2014). For business enterprise applications, memory utilization is a critical factor that makes the system efficient. In this case, Soak testing needs to be done for detection of issues faced by the applications under continuous load. The soak testing can reveal the issues the application is encountering when being used continuously.
A business enterprise application needs to be scalable to optimum utilization. In other words, the number of users for a business enterprise application can increase over time and the applications need to be flexible to accommodate the increasing number of users. The spike testing indicates how the system can respond with the increasing number of users. The primary objective of executing spike testing understands whether the system can perform under the increasing workload.
The business enterprise applications can change according to the requirements of a business. However, it is necessary to ensure that the system performs with equal efficiency. Regression testing is a technique that helps the experts to understand whether efficiency of the system is affected due to the implemented changes.
The regression testing can be done in several stages. The procedure for carrying out regression testing is described below:
4.5.1 Identification for test components
When the code of the application is changed, it is necessary to identify the bugs (Lu et al. 2015). Identification of test components is necessary to understand the effects of any modification in the code.
4.5.2 Setting the requirements for testing
Setting the requirements of testing is important to measure the metrics in the most appropriate manner. Collaboration among the business stakeholders and developers is required to identify the requirements for testing effectively.
4.5.3 Setting entry and exit criteria and set the schedule
The entry criteria for regression test helps to analyze the defects (Sharma et al 2014). Before starting the test, the defect would be documented properly and a defect tracking system needs to be put in place. Setting the exit criteria is necessary to ensure that all the tests are carried out. Following a schedule ensures that all the tasks are carried out in order.
4.5.4 Running the test and measuring the output
The next stage deals with running the tests and measuring the output. If the result is not found satisfactory, the recommendations should be given to further modify the application.
5. Conclusion
The above discussion indicates that User Acceptance testing will bring out the areas in the application which need to be improved. However, collaboration among the users and the developers is needed to make the business enterprise application more effective.
6. References
Chen, L. (2015). Continuous delivery: Huge benefits, but challenges too. IEEE Software, 32(2), 50-54.
Choudhury, P. P., Dihidar, K., Khan, A. R., Verma, R., & Sarkar, P. (2017). Software measurements and metrics: Role in effective software testing. Data in Brief, 3(2017), 593-596.
Harman, M., Jia, Y., & Zhang, Y. (2015, April). Achievements, open problems and challenges for search based software testing. In Software Testing, Verification and Validation (ICST), 2015 IEEE 8th International Conference on (pp. 1-12). IEEE.
Jorgensen, P. C. (2016). Software testing: a craftsman’s approach. CRC press.
Just, R., Jalali, D., Inozemtseva, L., Ernst, M. D., Holmes, R., & Fraser, G. (2014, November). Are mutants a valid substitute for real faults in software testing?. In Proceedings of the 22nd ACM SIGSOFT International Symposium on Foundations of Software Engineering (pp. 654-665). ACM.
Lewis, W. E. (2016). Software testing and continuous quality improvement. CRC press.
Lu, Z., Li, W., Murthy, K. S., & Raghuram, S. (2015). U.S. Patent No. 8,949,791. Washington, DC: U.S. Patent and Trademark Office.
Orso, A., & Rothermel, G. (2014, May). Software testing: a research travelogue (2000–2014). In Proceedings of the on Future of Software Engineering (pp. 117-132). ACM.
Sharma, C., Sabharwal, S., & Sibal, R. (2014). A survey on software testing techniques using genetic algorithm. arXiv preprint arXiv:1411.1154.
Zogaj, S., Bretschneider, U., & Leimeister, J. M. (2014). Managing crowdsourced software testing: a case study based insight on the challenges of a crowdsourcing intermediary. Journal of Business Economics, 84(3), 375-405.
