DD-KARB: Data-Driven Compliance to Quality by Rule Based Benchmarking

Abstract

Rather than proof and logical evaluation, benchmarking can be used for compliance assessment. Naturally, a set of benchmarks can shape an applied solution to compliance assessment. This paper proposes the KARB solution system, i.e. preventing compliance anomalies through rule-based benchmarking. In fact, rule-based benchmarking means evaluating an under-compliance system with its symbolic specification and using a set of symbolic rules (on the behalf of the semantic logic of evaluation). A case study was conducted to demonstrate and analyze the KARB solution. The IR-QUMA study (Iranian Survey on Quality in Messenger Apps) was then conducted to evaluate the quality of some messenger applications. According to the evaluation results, the hybrid DD-KARB method (with a combination of semantics-awareness and data-drivenness) is more effective than solo methods and can compute a somehow good estimation for the messenger application user quality scores. Therefore, DD-KARB can be considered a method for quality benchmarking in this technical context.