You will get Fast AI Agentic Auto-Generated Code Analysis Report for SAP ABAP
Project details
Have you considered using the latest artificial intelligence technology to help employees process ABAP-related code analysis tasks faster and more efficiently? I am part of an AI development team from Japan, and over the past year we have developed a tool that can read ABAP code and generate specification documents using AI.
Summary of Precision Test Results:
The expected goals were achieved, with an overall average parsing accuracy exceeding 80%.
Furthermore, in human reviews, the AI-generated results were understood with a comprehension rate of 68%.
Currently, there are still no commercially available code analysis tools with similar capabilities.
Usage Fees
The statistics are based on a total of 27 samples, comprising 40,555 lines of code.
The total cost was $70, averaging $0.86 per sample (calculated for 500 lines per sample) for large-scale model usage.
The analysis time per sample (calculated for 500 lines) was approximately 30 to 40 minutes.
As a prerequisite, human processing requires professionals with more than 5 years of experience.
AI processing achieves 16 times the efficiency of human processing.
Summary of Precision Test Results:
The expected goals were achieved, with an overall average parsing accuracy exceeding 80%.
Furthermore, in human reviews, the AI-generated results were understood with a comprehension rate of 68%.
Currently, there are still no commercially available code analysis tools with similar capabilities.
Usage Fees
The statistics are based on a total of 27 samples, comprising 40,555 lines of code.
The total cost was $70, averaging $0.86 per sample (calculated for 500 lines per sample) for large-scale model usage.
The analysis time per sample (calculated for 500 lines) was approximately 30 to 40 minutes.
As a prerequisite, human processing requires professionals with more than 5 years of experience.
AI processing achieves 16 times the efficiency of human processing.
AI Algorithms
Convolutional Neural Network, Large Language Model, Multimodal Large Language Model, Transformer ModelAI Applications
AI Chatbot, AI Content Creation, AI-Generated Code, Natural Language Generation, Natural Language UnderstandingAI Development Language
PythonAI Tools
Azure OpenAI, Gradio, Streamlit, TensorFlowAI Models
GPT-4What's included
| Service Tiers |
Starter
$10
|
Standard
$9,600
|
Advanced
$20,000
|
|---|---|---|---|
| Delivery Time | 2 days | 30 days | 60 days |
Number of Revisions | 1 | 4 | 5 |
AI Model Integration | |||
Batch Normalization | - | - | - |
Database Integration | - | - | - |
Detailed Code Comments | - | - | - |
Image Upscaling | - | - | - |
MLOps | - | - | - |
Model Deployment | - | - | - |
Model Documentation | - | - | - |
Model Monitoring | - | - | - |
Model Testing & Optimization | - | ||
Model Tuning | - | ||
Natural Language Processing | |||
NLP Tokenization | - | - | - |
Pre-Training | - | - | - |
Prompt Engineering | - | - | - |
Setup File | - | - | - |
Source Code | - | - | - |
Frequently asked questions
About Lq
Code parsing through AI | SAP ABAP code analysis report
Kanagawa, Japan - 8:07 am local time
Precision Test Results Analysis (Test Results up to September 30, 2024)
The test subjects included 24 English, 26 Chinese, and 25 Japanese code samples.
Summary of Precision Test Results:
The expected goals were achieved, with an overall average parsing accuracy exceeding 80%.
Furthermore, in human reviews, the AI-generated results were understood with a comprehension rate of 68%.
Currently, there are still no commercially available code analysis tools with similar capabilities.
Usage Fees
The statistics are based on a total of 27 samples, comprising 40,555 lines of code.
The total cost was $70, averaging $0.86 per sample (calculated for 500 lines per sample) for large-scale model usage.
The analysis time per sample (calculated for 500 lines) was approximately 30 to 40 minutes.
As a prerequisite, human processing requires professionals with more than 5 years of experience.
AI processing achieves 16 times the efficiency of human processing.
After rigorous testing, we found that AI-assisted manual processing efficiency can be improved by 16 times, and costs can be significantly reduced, which will bring huge profits to businesses. Would you like to learn more about the product we developed? Please leave me a message. I would be happy to communicate further with you to help solve practical production issues.
Steps for completing your project
After purchasing the project, send requirements so Lq can start the project.
Delivery time starts when Lq receives requirements from you.
Lq works on your project following the steps below.
Revisions may occur after the delivery date.
Listen to customer requirements and customer provides ABAP code.
Listen to customer requirements and customer provides ABAP code.
Develop content, deliverables, timeframe based on customer requirements.
Develop content, deliverables, timeframe based on customer requirements.