AI Software Bugs Segregation System: DSF

Software bugs fixing always will be expensive. A complex software solution usually consists of multiple sub-components or combinations of multiple software solutions. The more software sub-components integrated; the more Software bugs occur. Most of the time it is exceedingly difficult to identify which sub-component breaks the end-to-end functionality. Data-Search-Fix (DSF) is an AI software bugs segregation system that search and analyze the historical data in a smart way. Recommend a solution to narrow down debugging scope and reduce debugging cost. DSF consists of 3 major blocks - "Data Collection', 'Search Algorithm', and 'Fix's recommendation' on Dot net and MSSQL (Microsoft SQL). The data and search algorithm are designed in a form that can be easily swapped with other data or algorithms to fulfill the specific needs for different software communities. This paper will explain DSF software bugs segregation system detail end-to-end flow with a deep dive example. With the implementation of DSF shows productivity improvement by demonstrating quick turnaround time to identify the issue owner and root cause the issue.

Paper | Presentation

Mei Chen Ooi

Ooi Mei Chen has been in software engineering for over 12 years and has held many roles spanning code development, design and project management. She currently serves as a senior System Software Quality Engineer at Intel Corporation based in Penang, Malaysia. She holds a Degree in Computer Science from University Tunku Abdul Rahman, MY.