SCA: a semantic conflict analyzer for parallel changes

Parallel changes are becoming increasingly prevalent in the development of large scale software system. To further study the relationship between parallel changes and faults, we have designed and implemented a semantic conflict analyzer (SCA) to detect semantic interference between parallel changes. SCA combines data dependency analysis and program slicing. Data dependency analysis can disclose the semantic structure of the program. And program slicing can identify which semantic structures are impacted by a change. By comparing the overlap between impacts of two changes, SCA can detect if there are semantic interference between the two changes. An experiment with an industrial project shows that SCA can detect a significant portion of the faults in highly parallel changes. SCA is effective in predicting faults (based on "direct" semantic interference detection) in changes made within a short time period. SCA is both efficient (averaging less than two minutes) and scalable (...

• Type: Conference
• Year: 2009
• Where: SIGSOFT
• Authors: Danhua Shao, Sarfraz Khurshid, Dewayne E. Perry
• Keywords: Parallel Changes, Semantic Interference, Semantic Interference Detection, SIGSOFT 2009, Software Engineering