Measuring interprocess communications in distributed systems

Due to the increasing demands for computational scalability and performance, more distributed software systems are being developed than single-process programs. As an important step in software quality assurance, software measurement provides essential means and evidences in quality assessment hence incentives and guidance for quality improvement. However, despite the rich literature on software measurement in general, existing measures are mostly defined for single-process programs only or limited to conventional metrics. In this paper, we propose a novel set of metrics for common distributed systems, with a focus on their interprocess communications (IPC), a vital aspect of their run-time behaviors. We demonstrated the practicality of characterizing IPC dynamics and complexity via the proposed IPC metrics, by computing the measures against nine real-world distributed systems and their varied executions. To demonstrate the practical usefulness of IPC measurements, we extensively investigated how the proposed metrics may help understand and analyze various quality factors of distributed systems, ranging from maintainability and stability to security and performance, on the same nine distributed systems and their executions. We found that higher IPC coupling tended to be generally detrimental to most of the quality aspects while interprocess sharing of common functionalities should be promoted due to its understandability and security benefits.