Using Azure OpenAI, Copilot, and Azure ML Services in Software Development

15 min readFeb 29, 2024

Introduction: In today’s rapidly evolving technological landscape, organizations are constantly seeking innovative solutions to streamline development processes, enhance productivity, and deliver high-quality software products efficiently. As a leader in digital transformation and technology services, I recognize the potential of leveraging cutting-edge technologies to drive innovation and accelerate software development. By harnessing the power of Azure OpenAI, Copilot, and other Azure AI services, I aim to revolutionize code generation, API development, and testing methodologies, paving the way for more agile and efficient software engineering practices.

Leveraging Azure OpenAI and Copilot for Code Generation: Azure OpenAI and Copilot are groundbreaking AI-powered tools that provide developers with intelligent assistance and code generation capabilities. I utilize these tools to expedite the development process and improve code quality by automating repetitive tasks and suggesting contextually relevant code snippets. By leveraging natural language processing (NLP) and machine learning algorithms, Azure OpenAI and Copilot analyze code patterns, understand developer intent, and generate code snippets tailored to specific requirements. This enables developers to focus on higher-level tasks, such as architectural design and business logic implementation, while reducing the time and effort required for mundane coding tasks. Additionally, these AI-driven tools facilitate knowledge sharing and collaboration among development teams, as they provide real-time suggestions and insights based on collective coding experiences and best practices.

Empowering API Development with Azure AI Services: API development plays a crucial role in enabling seamless integration and interoperability between software systems. I leverage Azure AI services such as Azure API Management, Azure Functions, and Azure Cognitive Services to streamline API development and enhance functionality. Azure API Management enables me to design, publish, secure, and monitor APIs at scale, providing a centralized platform for API lifecycle management. Azure Functions, a serverless computing service, allows me to build lightweight, event-driven APIs quickly and efficiently, without the need to manage infrastructure. Additionally, Azure Cognitive Services, which encompass a range of AI-powered APIs for vision, speech, language, and decision-making capabilities, enables me to enrich APIs with advanced functionality, such as natural language understanding, image recognition, and sentiment analysis. By leveraging Azure AI services for API development, I deliver robust and intelligent APIs that meet the evolving needs of modern applications and ecosystems.

Enhancing Testing Practices with AI-driven Test Case Generation: Effective testing is essential for ensuring software quality, reliability, and security. I harness the power of Azure AI services, such as Azure DevOps and Azure Machine Learning, to enhance testing practices and automate test case generation. Azure DevOps provides a comprehensive set of tools for test planning, execution, and reporting, enabling me to manage testing activities seamlessly within the software development lifecycle. Leveraging Azure Machine Learning, I can apply machine learning algorithms to analyze code repositories, identify potential edge cases, and generate test scenarios automatically. By automating test case generation, I can accelerate the testing process, improves test coverage, and reduces manual effort, thereby enhancing overall software quality and reducing time-to-market.

Conclusion: In conclusion, organizations should strategic adopt Azure OpenAI, Copilot, and other Azure AI services to revolutionize software development practices, enabling faster, more efficient, and more intelligent development processes. By leveraging AI-driven code generation, API development, and test case generation capabilities, Azure empowers developers to focus on innovation and creativity, while automating mundane tasks and improving productivity. As I continue to embrace emerging technologies and drive digital transformation, Azure OpenAI and other Azure AI services will play a pivotal role in shaping the future of software engineering and delivering value to clients and stakeholders alike.

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The content below represents samples of code development using Generative AI services:

An example of how to use ChatGPT 3.5 to generate code for an API call in Python and Flask:

To create a Python-based API to wrap functions you’ve created in Python, you can use Flask, a lightweight web framework for Python. Below is a basic example of how to create an API using Flask to wrap your Python functions:

from flask import Flask, request, jsonify

app = Flask(__name__)

# Define your custom function to be wrapped by the API

def custom_function(param1, param2):

# Your custom logic here

result = param1 + param2

return result

# Define an endpoint for your API

@app.route(‘/api/custom_function’, methods=[‘POST’])

def api_custom_function():

# Parse request parameters

data = request.get_json()

param1 = data[‘param1’]

param2 = data[‘param2’]

# Call your custom function with the provided parameters

result = custom_function(param1, param2)

# Return the result as JSON

return jsonify({‘result’: result})

if __name__ == ‘__main__’:

app.run(debug=True)In this example:

We import the Flask class from the flask module.
We create an instance of the Flask class and name it app.
We define a custom function custom_function that you want to wrap with the API.
We define an endpoint /api/custom_function for our API using the @app.route decorator. This endpoint accepts POST requests.
Inside the endpoint function api_custom_function, we extract the parameters from the request payload using request.get_json().
We call the custom_function with the extracted parameters.
We return the result of the function call as a JSON response.

To use this API:

Save the code in a Python file, e.g., api.py.
Install Flask by running pip install Flask in your terminal.
Run the Python file (api.py) by executing python api.py in your terminal.
Your API will be available at http://127.0.0.1:5000/api/custom_function.

You can then send POST requests to http://127.0.0.1:5000/api/custom_function with JSON data containing the parameters param1 and param2, and the API will return the result of calling custom_function with those parameters.

Generate a test plan and test cases for a Python API call using Generative AI:

Below is a basic test plan and test case for testing a Python-based API that wraps functions you’ve created in Python using Flask:

Test Plan:

Objective: To verify that the Python-based API wraps the custom functions correctly and returns expected results.

Scope: This test plan covers testing of the API endpoints and the functionality of the custom functions.

Testing Approach: Black-box testing will be performed to validate the behavior of the API endpoints. Unit tests will be created to test the functionality of the custom functions.

Test Environment:

Operating System: [Specify OS]
Python Version: [Specify Python version]
Testing Framework: pytest

Test Cases:

1. Test Case: Verify API Endpoint for Custom Function

Description: Ensure that the API endpoint for the custom function is accessible and returns expected results.
Test Steps:

Send a POST request to the API endpoint /api/custom_function with valid parameters.
Verify that the response status code is 200 (OK).
Verify that the response body contains the expected result.

Expected Result: The API endpoint returns the expected result.

2. Test Case: Verify Error Handling for Invalid Requests

Description: Verify that the API returns appropriate error responses for invalid requests.
Test Steps:

Send a POST request to the API endpoint /api/custom_function with invalid parameters.
Verify that the response status code is 400 (Bad Request) or 422 (Unprocessable Entity).
Verify that the response body contains an error message indicating the reason for the error.

Expected Result: The API returns an appropriate error response for invalid requests.

3. Test Case: Verify API Endpoint for Custom Function with Negative Parameters

Description: Ensure that the API endpoint handles negative parameters correctly.
Test Steps:

Send a POST request to the API endpoint /api/custom_function with negative parameters.
Verify that the response status code is 200 (OK).
Verify that the response body contains the expected result.

Expected Result: The API endpoint correctly handles negative parameters and returns the expected result.

4. Test Case: Verify API Endpoint for Custom Function with Large Parameters

Description: Ensure that the API endpoint handles large parameters correctly.
Test Steps:

Send a POST request to the API endpoint /api/custom_function with large parameters.
Verify that the response status code is 200 (OK).
Verify that the response body contains the expected result.

Expected Result: The API endpoint correctly handles large parameters and returns the expected result.

5. Test Case: Verify API Endpoint for Custom Function with Null Parameters

Description: Ensure that the API endpoint handles null parameters correctly.
Test Steps:

Send a POST request to the API endpoint /api/custom_function with null parameters.
Verify that the response status code is 400 (Bad Request) or 422 (Unprocessable Entity).
Verify that the response body contains an error message indicating the reason for the error.

Expected Result: The API endpoint returns an appropriate error response for null parameters.

6. Test Case: Verify API Endpoint for Custom Function with Invalid Parameters

Description: Ensure that the API endpoint handles invalid parameters correctly.
Test Steps:

Send a POST request to the API endpoint /api/custom_function with invalid parameters.
Verify that the response status code is 400 (Bad Request) or 422 (Unprocessable Entity).
Verify that the response body contains an error message indicating the reason for the error.

Expected Result: The API endpoint returns an appropriate error response for invalid parameters.

Note: These test cases cover basic scenarios. Additional test cases may be required based on the specific functionality of the custom functions and the API endpoints. Additionally, unit tests should be written to test the functionality of the custom functions independently of the API.

Converting Microsoft SQL Server tSQL Stored Procedure to Snowflake Scripting Language:

To convert the SQL Server stored procedure to Snowflake Scripting Language stored procedure, we’ll create a JavaScript stored procedure since Snowflake does not support T-SQL like syntax directly. Below is an example of how you can achieve the functionality using JavaScript in a Snowflake stored procedure:

— Create or replace the stored procedure

CREATE OR REPLACE PROCEDURE uspGetList(

Product VARCHAR,

MaxPrice FLOAT,

OUT ComparePrice FLOAT,

OUT ListPrice FLOAT

)

RETURNS VARIANT

LANGUAGE JAVASCRIPT

// Define the SQL statement

var sql = `

SELECT p.”Name” AS Product, p.”ListPrice” AS “List Price”

FROM Production.Product AS p

JOIN Production.ProductSubcategory AS s

ON p.ProductSubcategoryID = s.ProductSubcategoryID

WHERE s.”Name” LIKE ? AND p.”ListPrice” < ?`;

// Execute the SQL statement

var stmt = snowflake.createStatement({ sqlText: sql, binds: [Product, MaxPrice] });

var resultSet = stmt.execute();

// Fetch the result and assign to output variables

if (resultSet.next()) {

ListPrice = resultSet.getColumnValue(“List Price”);

} else {

ListPrice = null;

}

// Assign ComparePrice

ComparePrice = MaxPrice;

// Return the result as a variant

return { Product: Product, “List Price”: ListPrice };

$$;

In this script, we’re using JavaScript as the language for the stored procedure in Snowflake. The snowflake.createStatement() method is used to execute the SQL statement, and the result is processed to assign values to the output variables. Finally, we return the result as a JSON-like variant object. Note that the exact mapping of data types might vary based on your specific use case and data requirements.

Converting COBOL Code to Python using Generative AI:

Here’s the COBOL code converted to Python. In Python, we’ll use dictionaries to represent data structures and functions to represent procedures. Since COBOL uses positional parameters and Python uses named parameters, I’ve updated the code accordingly. Note that this conversion does not include a full emulation of the COBOL environment or behavior, but it provides a rough translation of the logic.

# Define the working-storage section using dictionaries

work_area = {

“SUB”: 0,

“WORK_PREMIUM”: 0.0,

“STATE_TAX”: 0.0,

“PERCENT_LOAD”: 0.0,

“TARGET_LOAD_UNDER”: 0.0,

“TARGET_LOAD_OVER”: 0.0,

}

release_identifier = {“WV1001-ID”: “WV1001”}

# Define the premium table as a list of dictionaries

premium_table = [

{“PREMIUM_AMOUNT”: 0.0, “NET_PREMIUM”: 0.0},

# Add more premium entries as needed

]

# Define constants

PER_DOLLAR_UNDER_TARGET = 0.0 # Set your value here

PER_DOLLAR_OVER_TARGET = 0.0 # Set your value here

# Procedure to perform pre-update user module

def pre_update_user_module(guideline_params):

# Implement your logic here based on COBOL code

# Procedure to perform post-update user module

def post_update_user_module(guideline_params):

# Implement your logic here based on COBOL code

# Main procedure

def main(guideline_params, guideline_work_area, premium_table):

# Perform pre-update user module

pre_update_user_module(guideline_params)

# Check for errors

if not guideline_params[“ERROR_FREE”]:

return

for premium_entry in premium_table:

if premium_entry[“PREMIUM_AMOUNT”] == 0.0:

continue

if (

guideline_params[“CALC_GUIDELINES”]

and guideline_params[“PROCESS_SINGLE_PREM”]

and guideline_params[“PROCESS_MATERIAL_CHANGE”]

premium_entry[“NET_PREMIUM”] = premium_entry[“PREMIUM_AMOUNT”]

else:

work_area[“WORK_PREMIUM”] = premium_entry[“PREMIUM_AMOUNT”]

# Calculate WORK_PREMIUM

work_area[“WORK_PREMIUM”] -= premium_entry[“LOAD_AMOUNT”]

# Calculate STATE_TAX

work_area[“STATE_TAX”] = (

guideline_params[“STATE_TAX_PERCENT”] * work_area[“WORK_PREMIUM”]

)

# Deduct STATE_TAX from WORK_PREMIUM

work_area[“WORK_PREMIUM”] -= work_area[“STATE_TAX”]

# Calculate PERCENT_LOAD

work_area[“PERCENT_LOAD”] = (

work_area[“WORK_PREMIUM”] * premium_entry[“LOAD_PERCENT”]

)

# Deduct PERCENT_LOAD from WORK_PREMIUM

work_area[“WORK_PREMIUM”] -= work_area[“PERCENT_LOAD”]

# Deduct TRX_FEE from WORK_PREMIUM

work_area[“WORK_PREMIUM”] -= premium_entry[“TRX_FEE”]

if guideline_params[“CALC_SHADOW”]:

premium_entry[“TARGET_AMOUNT”] = work_area[“WORK_PREMIUM”]

if premium_entry[“TARGET_AMOUNT”] != 0.0:

if work_area[“WORK_PREMIUM”] <= premium_entry[“TARGET_AMOUNT”]:

# Calculate TARGET_LOAD_UNDER

work_area[“TARGET_LOAD_UNDER”] = (

PER_DOLLAR_UNDER_TARGET * work_area[“WORK_PREMIUM”]

)

else:

# Calculate TARGET_LOAD_UNDER

work_area[“TARGET_LOAD_UNDER”] = (

premium_entry[“TARGET_AMOUNT”]

* PER_DOLLAR_UNDER_TARGET

)

# Calculate TARGET_LOAD_OVER

work_area[“TARGET_LOAD_OVER”] = (

(work_area[“WORK_PREMIUM”] — premium_entry[“TARGET_AMOUNT”])

* PER_DOLLAR_OVER_TARGET

)

# Adjust WORK_PREMIUM based on TARGET_LOAD_UNDER and TARGET_LOAD_OVER

work_area[“WORK_PREMIUM”] -= (

work_area[“TARGET_LOAD_UNDER”] + work_area[“TARGET_LOAD_OVER”]

)

# Update NET_PREMIUM in premium table

premium_entry[“NET_PREMIUM”] = work_area[“WORK_PREMIUM”]

# Ensure NET_PREMIUM is not negative

if premium_entry[“NET_PREMIUM”] < 0:

premium_entry[“NET_PREMIUM”] = 0.0

# Perform post-update user module

post_update_user_module(guideline_params)

# Sample guideline parameters

guideline_params = {

“CALC_GUIDELINES”: True,

“PROCESS_SINGLE_PREM”: True,

“PROCESS_MATERIAL_CHANGE”: True,

“ERROR_FREE”: True,

“STATE_TAX_PERCENT”: 0.05, # Set your value here

“CALC_SHADOW”: True,

}

# Sample guideline work area

guideline_work_area = {“MAX_PROJ_MONTHS”: 12} # Set your value here

# Call the main procedure

main(guideline_params, guideline_work_area, premium_table)

# Print the updated premium table

for i, premium_entry in enumerate(premium_table):

print(f”Entry {i + 1}: NET_PREMIUM = {premium_entry[‘NET_PREMIUM’]}”)

This code provides a Python implementation of the logic from the COBOL code. It defines the necessary data structures as dictionaries, represents the premium table as a list of dictionaries, and translates the procedural code into Python functions. Please note that you may need to adapt this code further based on your specific requirements and the actual data structures and logic used in your application.

This was the original COBOL conversion to Python request:

Convert the following COBOL code to python: 000100 IDENTIFICATION DIVISION.

000200

000300 PROGRAM-ID. IUAEJNE.

000400

000500*TITLE. CALCULATE NET PREMIUMS FOR ITERITIVE PROCESSING.

000600

000700 AUTHOR. CSC FINANCIAL SERVICES SECTOR.

000800

000900 SECURITY. THIS PROGRAM IS THE PROPERTY OF CSC FINANCIAL

001000 SERVICES GROUP.IT MAY NOT BE COPIED IN WHOLE OR IN

001100 PART WITHOUT THE EXPRESS WRITTEN CONSENT OF CSC

001200 FINANCIAL SERVICES GROUP.

001300

001400 DATE-WRITTEN. AUGUST, 1993

001500 DATE-COMPILED.

001600 EJECT

001700*REMARKS.

001800*================================================================*

001900* MODULE MODIFICATIONS *

002000*================================================================*

002100* ENH # NAME YEAR ENHANCEMENT DESCRIPTION *

002200* — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — -*

002300* ENH:293B JOINT 1994 INSURANCE ON MULTIPLE LIVES *

002400* ENH:136 V054 1997 PERF — REDUCE LOOP OCCURS *

002410* ENH922 V570 2010 SHADOW ACCOUNT *

002500*================================================================*

002600

002700* ************************************************************

002800* * PROGRAM NARRATIVE *

002900* ************************************************************

003000

003100* THE FUNCTION OF THIS MODULE IS TO LOOP THRU ALL OCCURRENCES

003200* OF THE PREMIUM TABLE (CIUAEJ8E) AND CALCUALTE NET PREMIUMS.

003300

003400* ************************************************************

003500* * CALLING MODULE *

003600* ************************************************************

003700*

003800* IUAEJGE — ITERITIVE GUIDELINE, TAMRA AND SEC PROCESSOR

003900*

004000* ************************************************************

004100* * CALLED MODULES *

004200* ************************************************************

004300*

004400* NONE

004500

004600* ************************************************************

004700* * LINKAGE INPUT AREA *

004800* ************************************************************

004900*

005000* GUIDELINE PARMS

005100* PREMIUM TABLE

005200*

005300* ************************************************************

005400* * OUTPUT *

005500* ************************************************************

005600*

005700* CALCULATED NET PREMIUM IN PREMIUM TABLE

005800 EJECT

005900* ************************************************************

006000* * PROGRAM OUTLINE *

006100* ************************************************************

006200*

006300* A. PROCESS PRE-INSERT EDIT ROUTINES.

006400* 1. COPY THE PRE-INSERT USER EXIT.

006500*

006600* B. LOOP THRU ALL OCCURRENCES IN THE PREMIUM TABLE.

006700* 1. IF PREMIUM AMOUNT IN PREMIUM TABLE EQUAL ZERO,

006800* EXIT SECTION.

006900* 2. MOVE PREMIUM AMOUNT TO NET PREMIUM.

007000* 3. SUBTRACT LOAD AMOUNT FROM NET PREMIUM

007100* 4. CALCULATE STATE TAX EQUAL STATE TAX PERCENT

007200* * PREMIUM AMOUNT.

007300* 5. SUBTRACT STATE TAX FROM NET PREMIUM.

007400* 6. CALCULATE PERCENT LOAD EQUAL NET PREMIUM

007500* * LOAD PERCENT.

007600* 7. SUBTRACT PERCENT LOAD FROM NET PREMIUM.

007700* 8. SUBTRACT TRX FEE FROM NET PREMIUM

007800* 9. IF TARGET AMOUNT NOT EQUAL ZERO

007900* A. IF NET PREMIUM NOT GREATER THAN

008000* TARGET AMOUNT

008100* 1. CALC TARGET LOAD UNDER EQUAL NET PREMIUM

008200* * PER DOLLAR UNDER TARGET

008300* 2. TARGET LOAD OVER EQUAL ZERO.

008400* B. IF NET PREMIUM GREATER THAN TARGET AMOUNT

008500* 1. CALC TARGET LOAD UNDER EQUAL

008600* TARGET AMONT * PER DOLLAR UNDER TARGE

008700* 2. CALC TARGET LOAD OVER EQUAL (NET PREMIUM

008800* — TARGET AMOUNT) * PER DOLLAR OVER

008900* TARGET.

009000* C. SUBTRACT TARGET LOAD UNDER AND TARGET LOAD

009100* OVER FROM NET PREMIUM.

009200* 10. IF NET PREMIUM LESS THAN ZERO, MOVE ZERO

009300* TO NET PREMIUM.

009400*

009500* C. PROCESS POST-INSERT EDIT ROUTINES.

009600* 1. COPY THE POST-INSERT USER EXIT.

009700*

009800* D. EXIT MODULE.

009900

010000 EJECT

010100 ENVIRONMENT DIVISION.

010200

010300 DATA DIVISION.

010400

010500 WORKING-STORAGE SECTION.

010600

010700 01 FILLER PIC X(46) VALUE

010800 ‘******** MODULE IUAEJNE STARTS HERE ********’.

010900

011000 01 WORK-AREA.

011100 05 SUB PIC S9(4) COMP.

011200 05 WORK-PREMIUM PIC S9(9)V9(6) COMP-3.

011300 05 STATE-TAX PIC S9(9)V9(6) COMP-3.

011400 05 PERCENT-LOAD PIC S9(9)V9(6) COMP-3.

011500 05 TARGET-LOAD-UNDER PIC S9(9)V9(6) COMP-3.

011600 05 TARGET-LOAD-OVER PIC S9(9)V9(6) COMP-3.

011700

011710 01 RELEASE-IDENTIFIER.

011720 05 WV1001-ID PIC X(6) VALUE ‘WV1001’.

011730

011800 01 FILLER PIC X(44) VALUE

011900 ‘******** MODULE IUAEJNE ENDS HERE ********’.

012000 EJECT

012100 LINKAGE SECTION.

012200

012300 01 GUIDELINE-PARMS. COPY CIUAEJ1E SUPPRESS.

012400

012410 01 GUIDELINE-WORK-AREA. COPY CIUAEJ2E SUPPRESS.

012420

012500 01 PREMIUM-TABLE. COPY CIUAEJ8E SUPPRESS.

012600 EJECT

012700******************************************************************

012800* PROCEDURE DIVISION *

012900******************************************************************

013000 PROCEDURE DIVISION USING GUIDELINE-PARMS

013010 GUIDELINE-WORK-AREA

013100 PREMIUM-TABLE.

013200

013300 PERFORM 010000-PRE-UPDATE-USER-MODULE THRU 010000-EXIT.

013400

013500 IF NOT ERROR-FREE IN GUIDELINE-PARMS

013600 GO TO 000000-MODULE-EXIT.

013700

013800 PERFORM 100000-FILL-PREMIUM-TABLE THRU 100000-EXIT

013900 VARYING SUB FROM 1 BY 1

014000 UNTIL SUB GREATER THAN

014010 MAX-PROJ-MONTHS IN GUIDELINE-WORK-AREA.

014100

014200 PERFORM 999990-POST-UPDATE-USER-MODULE THRU 999990-EXIT.

014300

014400 000000-MODULE-EXIT.

014500 GOBACK.

014600 EJECT

014700 010000-PRE-UPDATE-USER-MODULE.

014800

014900 COPY PUUAEJNA.

015000

015100 010000-EXIT.

015200 EXIT.

015300 EJECT

015400 100000-FILL-PREMIUM-TABLE.

015500

015600 IF PREMIUM-AMOUNT IN PREMIUM-TABLE (SUB)

015700 EQUAL ZERO

015800 GO TO 100000-EXIT.

015900

015910 IF CALC-GUIDELINES IN GUIDELINE-PARMS

015920 AND PROCESS-SINGLE-PREM IN GUIDELINE-PARMS

015930 AND PROCESS-MATERIAL-CHANGE IN GUIDELINE-PARMS

015940 MOVE PREMIUM-AMOUNT IN PREMIUM-TABLE (SUB)

015950 TO NET-PREMIUM IN PREMIUM-TABLE (SUB)

015960 GO TO 100000-EXIT.

015970

016000 MOVE PREMIUM-AMOUNT IN PREMIUM-TABLE (SUB)

016100 TO WORK-PREMIUM IN WORK-AREA.

016200

016300 COMPUTE WORK-PREMIUM IN WORK-AREA

016400 EQUAL WORK-PREMIUM IN WORK-AREA

016500 — LOAD-AMOUNT IN PREMIUM-TABLE (SUB).

016600

016700 COMPUTE STATE-TAX IN WORK-AREA

016800 EQUAL STATE-TAX-PERCENT IN PREMIUM-TABLE (SUB)

016900 * WORK-PREMIUM IN WORK-AREA.

017000

017100 COMPUTE WORK-PREMIUM IN WORK-AREA

017200 EQUAL WORK-PREMIUM IN WORK-AREA

017300 — STATE-TAX IN WORK-AREA.

017400

017500 COMPUTE PERCENT-LOAD IN WORK-AREA

017600 EQUAL WORK-PREMIUM IN WORK-AREA

017700 * LOAD-PERCENT IN PREMIUM-TABLE (SUB).

017800

017900 COMPUTE WORK-PREMIUM IN WORK-AREA

018000 EQUAL WORK-PREMIUM IN WORK-AREA

018100 — PERCENT-LOAD IN WORK-AREA.

018200

018300 COMPUTE WORK-PREMIUM IN WORK-AREA

018400 EQUAL WORK-PREMIUM IN WORK-AREA

018500 — TRX-FEE IN PREMIUM-TABLE (SUB).

018600

018610 IF CALC-SHADOW IN GUIDELINE-PARMS

018620 MOVE WORK-PREMIUM IN WORK-AREA

018630 TO TARGET-AMOUNT IN PREMIUM-TABLE (SUB)

018640 END-IF.

018650

018700 IF TARGET-AMOUNT IN PREMIUM-TABLE (SUB)

018800 NOT EQUAL ZERO

018900 IF WORK-PREMIUM IN WORK-AREA

019000 NOT GREATER THAN

019100 TARGET-AMOUNT IN PREMIUM-TABLE (SUB)

019200 COMPUTE TARGET-LOAD-UNDER

019300 IN WORK-AREA

019400 EQUAL PER-DOLLAR-UNDER-TARGET

019500 IN PREMIUM-TABLE (SUB)

019600 * WORK-PREMIUM IN WORK-AREA

019700 COMPUTE WORK-PREMIUM IN WORK-AREA

019800 EQUAL WORK-PREMIUM IN WORK-AREA

019900 — TARGET-LOAD-UNDER

020000 IN WORK-AREA

020100 ELSE

020200 COMPUTE TARGET-LOAD-UNDER

020300 IN WORK-AREA ROUNDED

020400 EQUAL TARGET-AMOUNT IN PREMIUM-TABLE (SUB)

020500 * PER-DOLLAR-UNDER-TARGET

020600 IN PREMIUM-TABLE (SUB)

020700 COMPUTE TARGET-LOAD-OVER

020800 IN WORK-AREA ROUNDED

020900 EQUAL (WORK-PREMIUM IN WORK-AREA

021000 — TARGET-AMOUNT IN PREMIUM-TABLE (SUB))

021100 * PER-DOLLAR-OVER-TARGET

021200 IN PREMIUM-TABLE (SUB)

021300 COMPUTE WORK-PREMIUM IN WORK-AREA

021400 EQUAL WORK-PREMIUM IN WORK-AREA

021500 — (TARGET-LOAD-OVER

021600 IN WORK-AREA

021700 + TARGET-LOAD-UNDER

021800 IN WORK-AREA).

021900

022000 COMPUTE NET-PREMIUM IN PREMIUM-TABLE (SUB)

022100 ROUNDED

022200 EQUAL WORK-PREMIUM IN WORK-AREA.

022300

022400 IF NET-PREMIUM IN PREMIUM-TABLE (SUB)

022500 LESS THAN ZERO

022600 MOVE ZERO

022700 TO NET-PREMIUM IN PREMIUM-TABLE (SUB).

022800

022900 100000-EXIT.

023000 EXIT.

023100 EJECT

023200 999990-POST-UPDATE-USER-MODULE.

023300

023400 COPY PUUAEJNB.

023500

023600 999990-EXIT.

023700 EXIT.

The next request was to generate documentation of the above COBOL program using Generative AI:

It seems that you’ve provided a COBOL program that calculates net premiums based on certain business rules and calculations. Below, I’ll extract and explain the main business rules and calculations from the provided COBOL code:

Loop through Premium Table:

The main goal of this program is to loop through all occurrences of the Premium Table (PREMIUM-TABLE) and calculate net premiums.

Calculation of Net Premium:

If the PREMIUM-AMOUNT in the PREMIUM-TABLE for a particular occurrence is equal to zero, the program skips the calculations for that occurrence.
Otherwise, the program proceeds with calculations:
WORK-PREMIUM in the WORK-AREA is initially set to PREMIUM-AMOUNT.
Subtract LOAD-AMOUNT from WORK-PREMIUM.
Calculate STATE-TAX as STATE-TAX-PERCENT times WORK-PREMIUM.
Subtract STATE-TAX from WORK-PREMIUM.
Calculate PERCENT-LOAD as WORK-PREMIUM times LOAD-PERCENT.
Subtract PERCENT-LOAD from WORK-PREMIUM.
Subtract TRX-FEE from WORK-PREMIUM.
If TARGET-AMOUNT is not equal to zero:
If WORK-PREMIUM is not greater than TARGET-AMOUNT, calculate TARGET-LOAD-UNDER as PER-DOLLAR-UNDER-TARGET times (WORK-PREMIUM — TARGET-AMOUNT).
If WORK-PREMIUM is greater than TARGET-AMOUNT, calculate TARGET-LOAD-UNDER and TARGET-LOAD-OVER accordingly and subtract them from WORK-PREMIUM.
Finally, set NET-PREMIUM in the PREMIUM-TABLE to the calculated WORK-PREMIUM, and if NET-PREMIUM is less than zero, set it to zero.

Module Exits:

There are three module exits: 000000-MODULE-EXIT, 010000-EXIT, and 100000-EXIT, each ending a specific module’s execution.
After performing the necessary calculations, control is returned to the calling module or program.

These business rules and calculations are the main operations being performed by the COBOL program to calculate net premiums based on given input values. Please note that this is a simplified interpretation and might require additional context or further analysis to fully understand the program’s behavior in a specific context.