The gray box testing is the most appropriate method for testing the software system to be used in a healthcare context. The method combines both the white box and black box testing approaches. While the box method tests the internal structure of the software code, the black box approach tests the external structures. However, the gray box technique tests both internal working applications and external aspects of the system (Krawczyk, Barylski, & Barylski, 2013). It also tests the Web Services applications that are essential in the modern technology realm where cloud computing plays a key role. The end-user and the tester, as well as the software developer, can perform the testing process (Liu & Chen, 2009).
Supposing the system uses a Drupal website with several links, the tester or end-user can make any correction made when clicking the links accidentally. The changes can be made in the HTML code because the tester reveals the internal structure of the code. In such cases, the user can change the code and test it on the front end (Lewis, Dobbs, Veerapillai, & Chen, 2011). These approaches are applied respectively and differently in the white box and black-box tests. The main advantage of using gray box testing is that it provides combined techniques of the white box and black-box methods. It depends on the definition of the interface as well as the functional specification rather than the software’s source code (Krawczyk et al., 2013).
Grey box testing provides an excellent testing approach in a communication protocol and data handling, which are essential in healthcare data management. The method has high capacity and greater performance because of the limited omission of errors (Liu & Chen, 2009). It is good because it performs software testing for the designer’s point of view and the user’s viewpoint. On the other hand, testing is done through this method based on the database diagrams and data flow (Lewis et al., 2011).
One of the rationales of choosing a person responsible for testing is expertise. The user must have profound knowledge in software development and usage. In this sense, such an individual will be able to detect errors that occurred during the coding and design of the software (Liu & Chen, 2009). As a result, an excellent testing outcome will be achieved. Another rationale is knowledge of the coding program. It is important to note that software development applies various programming languages that must be understood effectively in order to create a perfect software system (Glad, Buffet, Simonin, & Charpillet, 2009). The person assigned the role of testing must have a broader knowledge of modern programming languages to be able to correct wrong codes using the gray box tester.
It is important to note that testing only recognizes quarter to half of the possible defects in software. Although other verification approaches such as inspections are effective, it becomes difficult to have a software system that is free from defects. Inaccurate testing enhances the presence of a few defects that might seem negligible. However, the presence of defects can result in the vulnerability of the software to external attacks, which is dangerous in the healthcare sector (Lewis et al., 2011).
To deal with the above pitfalls, the users can adhere to several pieces of information about the testing method. The tester should not assume that the system is working by verifying it. The behavior of the system should be tested to determine the level of performance and possible defects. It is important to determine the potential causes of defects and how to avoid them in the software system (Glad et al., 2009). The testing plan must have an explicit statement of the primary objective of the testing, which is to find defects instead of showing that it does not have defects.
References
Glad, A., Buffet, O., Simonin, O., & Charpillet, F. (2009). Self-Organization of patrolling ant Algorithms. 2009 Third IEEE International Conference on Self-Adaptive and Self-Organizing Systems, 4(1), 67-84.
Krawczyk, H., Barylski, M., & Barylski, A. (2013). On software unit testing for improving security and performance of distributed applications. KEM Key Engineering Materials, 597(1), 131-136.
Lewis, W. E., Dobbs, D., Veerapillai, G., & Chen, S. (2011). Ruan jian ce shi yu chi xu zhi liang gai jin- Software testing and continuous quality improvement. Beijing, China: Ren min you dian chu ban she.
Liu, H., & Chen, T. Y. (2009). An innovative approach to randomising quasi-random sequences and its application into software testing. 2009 Ninth International Conference on Quality Software, 2(1), 54-73.