This latest release features Topaz Runtime Visualizer (Topaz RV), which provides unprecedented visibility into the often-complex interactions between mainframe programs. This visibility makes it dramatically easier for veteran and novice developers alike to quickly understand, modify and troubleshoot even the oldest, most complex and/or poorly documented mainframe code.
Topaz RV’s capabilities are extraordinarily valuable to companies as they face the challenge of more frequently updating their business-critical mainframe applications in response to ever-changing business requirements. Without Topaz RV, discovering and understanding the calls mainframe programs make to other applications and databases during runtime can be an extremely slow, difficult and error-prone process—especially for inexperienced mainframe developers faced with applications that may have little or no documentation.
With Topaz RV, in stark contrast, developers can generate an intuitive map of the external calls a program executes during any specified runtime within minutes—without the need to refer to source code—saving them hours or days of painstaking work, while ensuring the accuracy and completeness of their results.
Topaz RV also enables developers to drill down into a program’s external calls to see how often programs call each other during a runtime and/or the specific datasets a program accesses at each point in its execution. This insight helps them better pinpoint potential performance bottlenecks, inefficiencies and inter-program impacts.
Topaz RV is an ideal complement to traditional source-code parsing, which itemizes all out-of-program calls written into an application’s code. By discovering and mapping only the program-to-program calls that actually occur during a live runtime of any developer-specified task—such as placing an order or running a monthly report—Topaz RV gives developers a clear and accurate “snapshot” of a program’s real behavior in the production environment under present conditions.
The new Topaz release also enables developers of all skill levels to more quickly and accurately perform impact analyses by creating Java-like “projects”—logical collections of data sources—that allow them to discover and investigate dependencies across programs and copybooks, without having to move code off the mainframe.
