Telemetry for Debugging Software Issues in Privacy-sensitive Systems

Abstract: Traditionally, when debugging a software system, developers rely on having access to the input data that caused the error. However, with data privacy concerns on the rise, it is becoming increasingly challenging to rely on input data as it might be sensitive or even classified. Telemetry is a method of collecting information about a system that can offer assistance. This thesis proposes a telemetry solution for debugging systems where input data is sensitive. The telemetry solution was implemented in a geographical 3D visualization system and evaluated based on two aspects: its effectiveness in assisting the developers working on the system to locate if and where a problem has occurred, and its ability to deduce the input data that generated the output. The results indicate that the telemetry solution is successful in helping developers identify system errors. Additionally, the system's privacy is maintained, as it is not feasible to directly ascertain the input data responsible from the output. However, no proof is presented and as such, no guarantee can be made. We conclude that telemetry can be a useful tool for developers, making the debugging process more effective while protecting sensitive input data. However, this might not be the case for different customers or systems. The thesis demonstrates the potential of using telemetry for debugging privacy-sensitive systems, with a proof-of-concept solution that can be improved upon in the future.