Service-oriented model-based fault prediction and localization for service compositions testing using deep learning techniques

A Recommender System for Fault Recovery Strategies in Web Services Composition Testing

“…The proposed F2RS-WSC approach focuses on identifying the faults in the model-based serviceoriented architectures (SOA). This is because the source code of these architectures is not available and are therefore treated as black box components [1,7]. Therefore, the proposed approach is more suitable for handling the faults caused in the SOA systems, which are based on the cause of fault [1,7].…”

“…This is because the source code of these architectures is not available and are therefore treated as black box components [1,7]. Therefore, the proposed approach is more suitable for handling the faults caused in the SOA systems, which are based on the cause of fault [1,7]. It helps to identify the fault types and their causes, thereby making it easier for the developers to fix the issues [1,7].…”

“…Therefore, the proposed approach is more suitable for handling the faults caused in the SOA systems, which are based on the cause of fault [1,7]. It helps to identify the fault types and their causes, thereby making it easier for the developers to fix the issues [1,7]. The utilization of this approach can have advantages in the enhancement of model-based SOA systems' performance.…”

“…The accuracy metric is used to validate F2RS-WSC among the different datasets as per the formula presented in Table 3 based on the Confusion matrix presented in Table 4 [36]. The calculation involves determining the proportion of accurate predictions made in relation to the overall number of predictions [7]. Table 5 represents the results of the F2RS-WSC approach performance metrics among all the datasets.…”

“…These challenges include interdependencies among services [2], complexities in integration [3], and ensuring quality of service (Q oS) metrics such as response time, throughput, and availability [2,4]. Integration and dependency challenges are prominent concerns in SOC paradigms and web service composition systems [2,5], which can lead to performance degradation [6] and the occurrence of faults [1,7]. Predicting faulty components and facilitating fault recovery in web services testing has become increasingly challenging.…”