# Ontology-Based Regression Testing: A Systematic Literature Review
## 1 Introduction  
Regression testing is a relevant research field focused on ensuring software works correctly after being modified or when new functionalities are added. The widespread use of information technology techniques has enabled the rapid development of applications. However, modifications or the addition of new features in the applications require retesting the web applications, which adds the problem or concern for software testers to retest the applications. Retesting web services/web applications is a relatively hard job for testers, and it also incurs a high cost. 'Regression Testing' (RT) with its subtypes 'test case selection', 'test case reduction', and 'test case prioritization' have been widely examined in research studies [1]. Test case selection approaches aim at increasing the effectiveness based on their measurement capabilities, including the cost, coverage, and fault detection [2, 3, 4]. Test case prioritization (TCP) approaches let researchers' reorder test cases to reveal maximum faults based on specific criteria. Test cases with the top defects are tested before the test cases with fewer failures [5]. Proposed RT approaches rely on some criteria, and the ontology of systems is one of these criteria proposed to perform test case selection, reduction, and prioritization.  
Ontology refers to basic concepts and their relationship in a research domain [6]. Due to ontology reasoning, the ideas which are harder for their explicit expression are derived. Ontology provides further analysis and assessment knowledge, including the accurate classification of faulty and non-faulty software engineering modules. The field of ontology covers the aspects of methodologies and metrics applied to solve issues in software engineering [7]. OntoClean is one of these methods that covers the use of some properties, including unity, rigidity, identity, and dependency [8]. The OntoClean method, along with meta-properties, is proposed to provide entities' semantic and logical meaning. In [9], researchers made extensions to define ontology by expressing vocabulary concepts and their use. In this entire document, web applications and web services are interchangeably used.  
The motivation behind this SLR is to investigate the continuous lack of discussion on ontology-derived regression testing in several SLRs [10]. Ontology-derived testing can be considered under the domain of regression testing [11]. Therefore, first, we present an overview of existing SLRs on regression testing and ontologies.  
Table 1 is the illustration of SLRs in the area of regression testing. The first SLR by [PERSON] et al. [12] includes two papers discussing web services' semantic behavior. Studies [13; 14] did not include papers on ontology-based regression testing. A study by [PERSON] et al. [15] presented a description of web services ontologies. They include two ontology-driven models, 'web services modeling ontology' (WSMO) and 'web services description language semantics' (WSD-S). Therefore, our SLR's motivation is to help researchers and software practitioners working on the ontologies in regression testing by presenting the state-of-the-art ontology-based RT approaches. We are also introducing the first SLR on ontology-based regression testing approaches.  
The structure of this paper is as follows.  
First, the authors present a literature review in Section 2. Further, they present the research methods to conduct the SLR on RT and ontologies in Section 3. Next, they show results and their discussions in Section 4. Finally, this SLR study's research limitations are presented in Section 5, while researchers conclude the SLR and present future implications in Section 6.