Using logs to detect and diagnose problems in software systems is no longer a feasible human process. The ever increasing amount of logs produced by present-day systems calls for more advanced techniques to enable log analysis. A great deal of log research has since then been focused on abstracting over log messages, clever analysis techniques and best practices for logging. An overview of the field, however, has not yet been composed. This makes it difficult for practitioners to identify what is relevant for them, and for researchers to determine interesting angles to explore. To this end we present a literature survey on the field of log analysis. In this survey we outline the different techniques and practices introduced by research in the field. We find that the results of the various works do not lend themselves well to comparison, and suggest future steps of research to overcome this lack of clarity. Furthermore, we suggest areas of improvement in terms of the applicability and feasibility of analysis techniques.

Nowadays, service-oriented architectures are more popular than ever, and more and more companies and organizations depend on services offered through Web APIs. The capabilities and complexity of Web APIs differ from service to service, and therefore the impact of API errors varies. API problem cases related to Adyen’s payment service were found to have direct considerable impact on API consumer applications. With more than 60 thousand daily API errors the potential impact is enormous. Similarly, API consumers of any API can experience errors, and depending on the application the impact can be costly. In an effort to reduce the impact of API related problems, we analyze 2.43 million API error responses to identify the underlying faults and derive 11 generic categories that describe them. We quantify the occurrence of faults in terms of the frequency and impacted API consumers. We investigate the impact of API faults on API consumer applications and illustrate this with 3 case studies. Furthermore, an overview is given of the current practices and challenges to avoid and reduce the impact of API errors by API consumers. Using the results, we introduce 16 recommendations for API providers and API consumers to reduce the impact of API related faults.

Service-oriented architectures are more popular than ever, and increasingly companies and organizations depend on services offered through Web APIs. The capabilities and complexity of Web APIs differ from service to service, and therefore the impact of API errors varies. API problem cases related to Adyen's payment service were found to have direct considerable impact on API consumer applications. With more than 60,000 daily API errors, the potential impact is enormous. In an effort to reduce the impact of API related problems, we analyze 2.43 million API error responses to identify the underlying faults. We quantify the occurrence of faults in terms of the frequency and impacted API consumers. We also challenge our quantitative results by means of a survey with 40 API consumers. Our results show that 1) faults in API integration can be grouped into 11 general causes: invalid user input, missing user input, expired request data, invalid request data, missing request data, insufficient permissions, double processing, configuration, missing server data, internal and third party, 2) most faults can be attributed to the invalid or missing request data, and most API consumers seem to be impacted by faults caused by invalid request data and third party integration; and 3) insufficient guidance on certain aspects of the integration and on how to recover from errors is an important challenge to developers.@en