# KARB Solution: Compliance to Quality by Rule Based Benchmarking

arXiv: https://arxiv.org/abs/2007.05874 · HTML: https://mlsanity.com/paper/2007.05874/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 11 Jul 2020.

## Built on by (most cited first, 2 of 2)

- [SELM: Software Engineering of Machine Learning Models](https://mlsanity.com/paper/2103.11249/) (2021)
- [Stateless and Rule-Based Verification For Compliance Checking Applications](https://mlsanity.com/paper/2204.07430/) (2022)

## Abstract (arXiv)

Instead of proofs or logical evaluations, compliance assessment could be done by benchmarking. Benchmarks, in their nature, are applied. So a set of benchmarks could shape an applied solution for compliance assessment. In this paper, we introduce the KARB solution: Keeping away compliance Anomalies by Rule-based Benchmarking. By rule-based benchmarking, we mean evaluation of under-compliance-system by its symbolic specification and by using a set of symbolic rules (on behalf of semantic logic of evaluation). In order to demonstrate and investigate the manner of KARB solution, we conducted a case study. The IR-QUMA study (Iranian Survey on Quality in Messenger Apps) is defined to evaluate the quality of some messenger apps. the results of evaluations suggest that the Hybrid Method of DD-KARB (with combination of semantics-awareness and data-drivenness) is more effective than solo-methods and could compute a somehow good estimation for messenger-apps user quality scores. So DD-KARB could be considered as a method for quality benchmarking in this technical context.