Examination and analysis in mobile cloud forensics involve extracting, interpreting, and correlating digital evidence from interconnected mobile and cloud environments to reconstruct events accurately and support legal investigations. Research in this area focuses on designing advanced methodologies for artifact extraction, metadata interpretation, and data correlation across multiple devices, cloud servers, and virtualized platforms. Key topics include automated analysis frameworks for synchronized mobile-cloud data, detection of data tampering and manipulation, and cross-platform evidence reconstruction. Other important research areas encompass AI- and ML-driven forensic analytics, visualization of complex forensic relationships, and the use of blockchain for ensuring evidence integrity. Emerging directions also include privacy-preserving forensic analysis, real-time monitoring and examination of cloud-hosted mobile applications, and standardization of evidence handling procedures for hybrid infrastructures. Developing scalable, reliable, and legally admissible examination models remains a crucial goal in advancing mobile cloud forensic research.