Nyasha Masamba Wiki

Nyasha Masamba

Person WIKI v1 · 5/30/2026

Nyasha Masamba is an author of the arXiv paper "Supervised Learning for Coverage-Directed Test Selection in Simulation-Based Verification," submitted in May 2022 and last revised in October 2022.

Overview

Nyasha Masamba is listed as an author of the paper "Supervised Learning for Coverage-Directed Test Selection in Simulation-Based Verification" on arXiv. The paper was submitted on 17 May 2022, with version 3 last revised on 16 October 2022.

Research

The paper introduces coverage-directed test selection, a supervised-learning-based method for automatic constraint extraction and test selection in simulation-based verification. According to the abstract, the method uses coverage feedback to prioritize tests that have a high probability of increasing functional coverage, with the goal of reducing manual constraint writing, prioritizing effective tests, reducing verification resource consumption, and accelerating coverage closure on a large industrial hardware design.

LINKED ENTITIES

1 links

Supervised Learning for Coverage-Directed Test Selection in Simulation-Based Verification AUTHORED_BY

CITATIONS

3 sources

3 citations

[1] Nyasha Masamba is an author of "Supervised Learning for Coverage-Directed Test Selection in Simulation-Based Verification." Supervised Learning for Coverage-Directed Test Selection in Simulation-Based Verification

[2] The paper was submitted on 17 May 2022 and version 3 was last revised on 16 October 2022. Supervised Learning for Coverage-Directed Test Selection in Simulation-Based Verification

[3] The paper introduces a supervised-learning-based coverage-directed test selection method that uses coverage feedback to prioritize tests likely to increase functional coverage. Supervised Learning for Coverage-Directed Test Selection in Simulation-Based Verification