Several efforts have been made to study the nature of performance interference in co-allocated applications running in different environments. Such performance interference degrades the performance of co-allocated applications. Many researchers propose techniques, methods and approaches that use mathematical equations, machine learning algorithms or other kind of techniques to predict/analyze performance degradation. Hardware counters, virtual machine monitor metrics and third-party tools are commonly used to provide the input data for prediction techniques. Performance prediction/analysis is useful for understanding, preventing, and minimizing performance degradation. This paper presents a systematic literature review of methods for the prediction/analysis of performance degradation due to performance interference of co-allocated applications, which were published in the open literature during the period 2006-2023. We classified and categorized each analyzed article depending on the method used and the environment employed, among others features. In addition, we identify some directions and trends in performance interference, as well as some unresolved issues.