Abstract: Systems and methods are provided for detecting discrepancies in information that is displayed to a user across different webpages of an online shopping system. User interaction with the online shopping system is simulated in one example to collect data relating to webpages of the online shopping system. The data is analyzed to identify relevant semantic blocks of data and compare the data in those blocks across webpages. In an additional example, source code for the webpages is analyzed using machine-learning systems, which are targeted based on the results of the user interaction simulation to identify problematic source code and correct associated issues.

Abstract: Modifications to caching performed between different services may be determined. A history of requests and responses between the different services may be obtained. The history may be evaluated to determine respective frequencies of parameters between the services. The frequencies of parameters may be evaluated to determine one or more modifications to caching among the different services. The modifications may be provided in order to be applied to change caching performance for subsequent requests.

Abstract: Systems and methods are provided for rendering content for presentation in a portion of a user interface based on context-independent data and a template that is selected based on context information associated with the user interface. The template may be selected from among a number of different templates based at least in part on a template selection data structure that associates each template with one or more combinations of contextual attributes associated with the context of the user interface. The content for inclusion in at least a portion of the user interface may then be rendered using the selected template and at least a portion of the context-independent data.