After an operating system failure, multilevel performance issues
may emerge. The signs of such problems can become apparent gradually through
the side effects of complex processes within the system. Observers may struggle
to interpret these facts and make informed decisions based on the unfolding
scenarios. Consequently, system behavior cannot be quickly predicted
post-failure. Analyzing source code to identify the cause of the failure is
essential before restarting system operations.
Observation:
Developers concentrate on system issues
to interpret behavioral scenarios. Beyond the side effects, the primary issues
often reflect the underlying, unseen problem. System owners may be reluctant to
investigate these hidden issues due to constant global variables' high costs
and complexity. Many functional systems today are not fully optimized, and
numerous IT projects fail to achieve their objectives.
Observation:
The scenario illustrates a series of data,
actions, and events. Each structure within this framework is identifiable and
modifies the history of certain invisible entities. Observers can distinguish
between two types of scenarios in their research: static and dynamic.
1. Static Scenarios: These
scenarios display data, actions, and events without linking to global variable
instances. They are not sensitive and do not involve multiple variables.
Observers can easily interpret these scenarios since the qualitative pattern
remains consistent across a range of simulated actions.
2. Dynamic Scenarios: These
scenarios are sensitive, contingent, and involve multiple threads linked to
global variables. Many observers face difficulty detecting significant threads
for possible interpretation and analysis. Analyzing such scenarios requires
time, capital investment, and sophisticated methods. Observers must identify
hierarchical paths and complex threads that refer to global variables within
system environments.
