Debugging threads with HP Wilde Beest

What are threads?
Threads are subsets of ‘Process’, which aid in accelerating the execution of any task.
The usage of threads increases efficiency that results from the intended concurrency
in the threaded-programming practice. Threads share the same resources as Process
and hence do not have resource overheads. This property of threads is important when
processing speed becomes a criterion to measure efficiency and if programmers use
more than one thread to complete a single process.
Today’s hardware comes with multiple processors to support enhanced speed in
processing. Multi-threaded programs which execute on multi-processor systems and
multi-core systems make the best use of Parallelism that the hardware offers.
Understanding complexity in thread programming
The concurrency of threads and the parallelism of the hardware jointly contribute to
the processing speed of programming applications. With threaded programs, ever on
an increase in the industry, it becomes essential to understand the underlying complexity
in implementing the concept. In addition, this understanding helps you interpret the
results of debugging threaded programs.
The following are the most important concepts that attribute to the complexity in
threaded programming:
• Deadlock
• Race condition
• Priority inversion
Mutual exclusion (mutex) is a method which ensures that the threads share program
resources systematically, thereby avoid unintended modification of the data in shared
variables. Program segments attach locks to shared resources. This ensures mutual
exclusion. Improper mutex lock-unlock in threaded applications could result in a
deadlock condition which stops the program execution completely.
Race condition arises when shared data or resources are not accessed in any particular
order thus resulting in inconsistent data in some instances. This possibility occurs when
you write code segments without ensuring serial access to shared resources. Such
threaded programs with inconsistent and random access to shared variables contribute
to the complexity involved in debugging threads.
In addition, when a high-priority thread waits for a lock which a low-priority thread
holds, the priority inversion here results in lesser execution efficiency.
Thread programs, prone to such complexities, are subject to conditions or events that
reduce efficiency or increase the potential for errors.
What are threads? 11