Boren Zang

• Implemented Kotlin unit tests for the Android GUI testing project to ensure the functionalities of each component. • Investigated ARSC file format and contributed to the parser of ARSC file format by using Java and Kotlin, improving the performance, accuracy, and precision of the static analysis in the automated Android GUI testing project. • Benchmarked Apache Commons Exec library and ProcessBuilder API in both Java and Kotlin with JUnit framework.

• Developed a static analysis tool to detect data races and deadlock bugs for projects in the Go programming language. • Investigated synchronization mechanism in the Go programming language to eliminate false positives in the tool. • Benchmarked the static analysis tool against open-sourced real-world applications to disclose potential bugs.

• Implemented the multi-scanning feature of the analysis product in Go, reducing time consumption for large code bases. • Resolved the scalability problem of the analysis product, supporting compilation in multiple Linux environments. • Collected real-world software and created Python/Perl scripts to improve regression tests for the analysis product. • Created Docker file and configure running environment uniformly for the analysis product to be easily delivered. • Refined and decorated HTML bug reports generated by the analysis product to improve user experience.

Investigated efficiency of ROS intra-process communications.

• Analyzed and improved the data transfer efficiency of the Global Track and Trace web microservices which involved Tomcat server configuration, resulting in an over 90% reduced HTTP response size during RESTful requests. • Configured and established a sample backend system of the Global Track and Trace web service by using ABAP programming language to facilitate the sales department to demonstrate the product to potential customers. • Tested backend RESTful services of the Global Track and Trace web microservices by using jQuery API in JavaScript.

• Developed a Python project which scraps the latest finance and insider trading data of public companies from the U.S Security and Exchange Commission's official website, generating more than 1,000,000 data points. • Organized financial data into an Excel file and established comparable models to analyze financial information.

Work on project for web data downloading, processing and analyzing in the software development team of investment company in China • Wrote Python program to download, extract and process financial data from large public domains such as, Yahoo and Google Finance websites. Built large public companies comparable models based on such financial data in Excel. • Tools, Algorithms and Major accomplishments: − Utilized various modules, such as Beautifulsoup, and data types such as dictionary, list to extracted financial and market information, such as financial statements, trading prices, volumes, valuation multiples; − Output such information to Excel file and calculated additional business operating parameters; − Generated large amount of data: over 1,000,000 data points were downloaded and processed when companies > 500 over single session. Worked on connection issues when servers refused for long time connections; • Communicated with online software development community to get help on various technical issues. • Finished the project on schedule; Codes were used as based version for as additional improvement and enhancement.