Software Integration Test Report Analysis Automation Using Python

Automation in software testing is proliferating in a multitude of technical fields, predominantly in the automotive industry. With the escalation in features provided by the vehicle, the complexity of embedded software increases. It subsequently entails an increase in the software modules of the product. The software integration testing of the entire project has become a rigorous task since building multiple test-environments is required to test the interactions amongst all software modules. Analysis of test reports generated by these environments is performed manually to calculate the function coverage, call coverage, and detect dead code. The process of coverage calculation and error isolation is time-consuming. This paper presents a method of automatic analysis of the test reports generated after software integration testing by utilizing text mining techniques. Text mining is a data analysis technique employed to elicit high-quality information from textual sources like full-text documents, emails, and HTML files. The use of Python tool for text mining is explored in this paper. Software integration testing at Varroc is performed using VectorCAST tool that generates test reports in HTML format. A python script is developed that reads and scrutinizes all the reports and provides output in excel sheet.