Backend Workflows and Processes
Last updated
Last updated
Voltius employs a comprehensive and systematic approach to smart contract verification:
Initial Submission and Pre-Processing: The process starts with users submitting their smart contracts. These submissions undergo initial validation for syntax correctness, followed by pre-processing steps like parsing and normalization.
Feature Extraction and Analysis: Critical structural and semantic features of the smart contract code are extracted using Python-based tools. Techniques like Natural Language Processing are applied for deeper semantic analysis.
Machine Learning Model Engagement: The pre-processed data is fed into machine learning models, which are hosted on scalable cloud infrastructures. These models are trained to identify vulnerabilities, patterns, and anomalies.
Validation and Benchmarking: The identified issues are cross-validated against internal test cases and benchmarks, as well as known vulnerabilities, to enhance the accuracy of the analysis.
Report Generation and Delivery: Insights from the analysis are compiled into detailed reports, providing actionable recommendations. These reports are then made accessible to the users through the platform's interface.
Feedback and Iteration: User feedback is solicited to continuously improve the analysis process. Based on this feedback and new data, the machine learning models are iteratively retrained.
This workflow exemplifies Voltius's commitment to a thorough, accurate, and user-friendly smart contract verification process, ensuring continuous evolution and adaptability to the changing blockchain landscape.
