Programming Languages

Apex, the proprietary programming language used on the Salesforce platform, is often praised for its seamless integration with CRM workflows. However, troubleshooting issues in Apex is not trivial. Large-scale enterprise systems that rely heavily on Apex often encounter subtle bugs that go unnoticed until they impact production. From governor limit violations to concurrency conflicts and asynchronous job failures, the language's constraints impose unique challenges for architects and senior developers. This article dives deep into diagnosing and resolving these complex Apex issues, offering both immediate fixes and architectural strategies for long-term stability.

Racket, a descendant of Scheme and part of the Lisp family, offers powerful language-oriented programming capabilities. While it excels in building DSLs, teaching programming, and rapid prototyping, enterprises using Racket in production-scale systems face unique troubleshooting challenges. These include memory management issues, module dependency cycles, concurrency bottlenecks, and performance tuning for long-running applications. Understanding how Racket's runtime system, garbage collector, and module system interact is key to diagnosing and resolving such problems. This article provides deep analysis, practical fixes, and governance practices for senior engineers working with Racket in enterprise environments.

Prolog, a logic programming language, has long been used in academic and enterprise environments for building rule-based systems, expert systems, and AI prototypes. Despite its power, Prolog presents unique troubleshooting challenges in large-scale applications. Problems such as non-terminating queries, unpredictable backtracking, memory exhaustion, and integration bottlenecks with modern architectures often confuse even experienced engineers. This article provides an in-depth troubleshooting guide, focusing on diagnostics, architectural pitfalls, and sustainable solutions for using Prolog in enterprise-level systems.

COBOL, one of the oldest programming languages still in active use, underpins critical enterprise systems in finance, insurance, and government. Despite its age, COBOL remains vital, but maintaining and troubleshooting COBOL applications in modern contexts presents unique challenges. Issues rarely surface in small modules but manifest dramatically at enterprise scale: data corruption in batch jobs, transaction throughput bottlenecks, and integration failures with contemporary APIs. Senior engineers and architects must navigate both legacy constraints and modern infrastructure demands to ensure continuity and reliability. This article explores deep troubleshooting techniques, architectural pitfalls, and long-term modernization strategies for COBOL-based systems.