Mature software systems start as clean, carefully crafted architectural solutions founded on the best modern design techniques and good intentions. Over time, however, the purity of the architectural lines gives way to the practical reality of ad hoc extensions that, for the sake of business expediency, are hastily added to the core system structure. There’s nothing wrong with this; after all, in the real world, IT systems are built to perform requisite business functions and not necessarily to delight the aesthetical sensibilities of their software architects.
Unfortunately, way beyond architectural aesthetics, there’s a point after which these accumulated changes lead to less than efficient application platforms. Like all complex systems, such mature applications need ongoing clean-up and refactoring. From time to time, we need to make adjustments to these applications.
This is particularly true for batch cycles. Batch cycles undergo constant alterations as new jobs are being added to address evolving business requirements, changes in the way programs process data, new incoming or outgoing interfaces, and even dramatic changes in the number of transactions processed. When the batch cycle is first established, it tends to have a generous time window and ample CPU resources to spare. However, small changes accumulate and, after years of deployment, the picture changes.
In situations such as these, you need a well-defined range of preemptive actions. Today’s Job Control Language (JCL) Integrated Development Environments (IDEs) successfully bridge the gap between batch cycle legacy technologies and modern code visualization techniques. Furthermore, these IDEs feature sophisticated analytical tools that are based on studies of underlying code semantics and active simulation of dynamic system behavior. Armed with these IDEs, IT organizations can develop a proactive strategy for addressing their batch cycle needs.
At the core of these IDEs are three types of proactive measures aimed at streamlining your batch cycles. Each measure provides practical value and tangible benefits:
• Visual Knowledge Base
Visual Knowledge Base
There’s an old saying among mainframe programmers: “Nobody ever writes new JCL; one simply copies and modifies existing code.” The reason is that JCL is awkward and hard to understand. Inline comments are useful, but sometimes meaningful details are obscured by the use of JCL procs and symbolic variables. At run-time, symbolic variables are replaced with certain values, but the effect of such replacements isn’t immediately visible to someone looking at the code. The programmer or analyst must mentally perform symbolic variable substitutions, which slows him or her down and increases the probability of mistakes. Imagine the adverse impact on the productivity of a programmer who must analyze business processes with hundreds of jobs, having to go through the mental exercise of symbolic variable substitution for each job.