Imagine you’re a translator fluent in English, but you’ve been tasked with converting a complex legal document written in ancient Latin into modern legal jargon that still retains the original intent. That’s the challenge we face when moving COBOL to modern languages. It’s not just about changing syntax; it’s about preserving the business logic that has been meticulously crafted and refined over decades.
This chapter is your Rosetta Stone for translating legacy COBOL code to the cloud. We’ll explore how to map COBOL structures to object-oriented paradigms, tackle data migration challenges, weigh automated versus manual translation approaches, avoid creating ‘JaBOL’ (Java code that looks like COBOL), and implement robust testing strategies. By the end, you’ll have a clear roadmap for transforming your legacy code into a modern, cloud-ready application while preserving its valuable business logic.
This section explains how to translate COBOL’s structured data and procedures into object-oriented constructs in languages like Java, C#, or Python. We’ll cover representing COBOL data as classes, COBOL verbs as methods, and handling COBOL-specific data types. Refer to Chapter 2 for a refresher on COBOL Divisions and PIC clauses.
The COBOL Data Division defines data structures through sections like WORKING-STORAGE (for variables), FILE SECTION (for external files), and LINKAGE SECTION (for data passed between programs).
COBOL data types (PIC clauses) map to corresponding Java data types:
PIC X(10)
(10-character alphanumeric) → String
in JavaPIC 9(5)
(5-digit numeric) → int
in JavaPIC 9(7)V99
(numeric with decimal places) → BigDecimal
in Java for accurate decimal representation01 CUSTOMER-RECORD.
05 CUSTOMER-ID PIC X(10).
05 CUSTOMER-NAME PIC X(30).
05 BALANCE PIC 9(7)V99.
This COBOL record translates into a Java class with Lombok to reduce boilerplate:
import java.math.BigDecimal;import lombok.Getter;import lombok.Setter;@Getter@Setterpublic class Customer { private String customerId; private String customerName; private BigDecimal balance; public Customer(String customerId, String customerName,
BigDecimal balance) { this.customerId = customerId; this.customerName = customerName; this.balance = balance; }}
@Getter
and @Setter
annotations automatically generate getter and setter methodsBigDecimal
ensures precise financial calculations, avoiding float/double errorsIn Python, we can use data classes:
from dataclasses import dataclass
from decimal import Decimal
@dataclassclass Customer:
customer_id: str customer_name: str balance: Decimal
# No need for explicit getters and setters in Python
Python’s Decimal
type ensures accurate handling of decimal values, while the @dataclass
decorator generates boilerplate code automatically.