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| AI-Based Software Defect Tracking |
Defects are a fact of life in software development, they cannot be eliminated altogether however they can be
managed and controlled so that their impact is minimized on the quality and
scope of the overall project. The later a bug is detected in the development
lifecycle, the higher the cost, and the required time would be for resolving that
issue. In the worst-case scenario where the defect is found after the
development stage, it is likely to have a negative impact on the consumers and
creates many challenges for the developers as well. Owing to this, the testing
and defect tracking of software tracking alone accounts for around 50 percent
of the total cost of product development.
Artificial intelligence continues
to experience increasing domination across the industries and with its
wide-ranging application, it has not only been able to gain traction in the
software development field but it is also one of the key driving forces behind
the innovation in this sector. Fundamentally, artificial intelligence has been
able to transform the digital world as it takes large volumes of unstructured
data and derives meaningful insights from it which enables the companies to
make better decisions in less time. As the project teams grow and the software
development becomes more complicated, the need for artificial intelligence
becomes more prominent especially when it comes to defect tracking and quality
assurance of the product. The integration of sophisticated artificial
intelligence techniques with defect tracking software
empowers the organization to be more proactive and resolve issues effectively.
Benefits Of Artificial Intelligence
Testing Over Traditional Testing
Organizations are leveraging
artificial intelligence techniques in the defect tracking software to enhance
their ability to detect any problematic issues in the early stages of the
product lifecycle, which enables the teams to proactively adjust their planning
to cater to these issues.
With the use of artificial
intelligence methods, the testers would be able to evaluate the past patterns
of the defects and determine their trends so that they are able to detect any
possible weak nodes or vulnerabilities in the system. As opposed to a traditional form of testing, the employment of artificial intelligence in a
defect tracking system automates the test processes and enables precise and
continuous software
testing to fast track the whole procedure. More often than not, some of the
bugs remain undetected with the traditional bug tracking approach which can
easily snowball into much bigger issues. However, with the use of artificial
intelligence, the testers can not only detect all the pertinent defects in the
system but they are able to evaluate them and keep track of their progress as
well. The incessantly evolving artificial intelligence bots are easily able to
keep up with the changes in the code and learn new application functions. The
quality of the product is much more likely to improve with this approach as the
artificial intelligence bots are constantly updated so they detect any
important changes in the code and evolve with it.
