چکیده (انگلیسی):

With the increase in the need and demand for evolving Web services, the rate at which changes are
made to the services has increased. In case of importunate change requests, there arise critical
situations where the business analysts are subjected to make changes by themselves without the aid of
the developers because of the time and cost factors. However, there are high chances that an analyst
makes a bug introducing change and injects incorrect statements into the logic and hence there are fair
chances for the changed service to exhibit an undesired behavior. Though the impact of the changes is
analyzed and recorded every time a change is made and the bug report is generated, it is often done
many months after the initial injection of the bug which is time consuming and ultimately results in the
failure to meet the business outcome. This process is repeated even when similar change requests are
encountered which is absurd in the current scenario and acts as a challenge to the success of a business
which is the motivation behind this study. This study address this challenge by focusing on an efficient
prediction system which would analyze the recorded incidents, filter the incidents which match with
the current incident and predict the level of risk and accuracy involved in committing the change. The
implication is that the system performs automated verification of composition patterns and detection of
violations in the business policies if any and aids in change management.