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Technical Paper

AnaCov - A novel method for enhancing coverage analysis

One method used for bug detection in software testing is the tracking and analysis of source code coverage, which helps reveal the percentage of original code covered by the software quality assurance (QA) engineer's regression suite. This percentage can help identify any gaps that may exist in testing. We introduce AnaCov, a tool that facilitates this process of code coverage testing. AnaCov automated mapping enables QA personnel to track coverage across time using versioned reports, and more importantly, to quickly test coverage of newly added code. This functionality is invaluable to both developers and QA engineers as it helps ensure better coverage over time, while minimizing time and disk space usage. It also allows users to merge several runs of coverage, creating a combined coverage report that is easy to analyze. By measuring code coverage at critical points in the development workflow, developers and QA engineers can proactively identify and correct any deficiencies. Introducing automated code coverage analysis into the development process enables teams to continually monitor and improve testing strategies, ensuring better code quality and a more robust end product.

AnaCov, a comprehensive code coverage quality assurance tool

The AnaCov tool is designed for ease of use, with a user-friendly single command line interface that provides access to all functionalities, with no suite or product restrictions. Invoking the AnaCov tool allows users to map testcases to source files or functions within the original code, which enhances efficiency when analyzing coverage related to a selected subset of files. The ability to easily query which testcases cover certain source files has a great benefit when it comes to quickly investigating coverage of code newly added to the source files. This knowledge enables better selection of pre-check-in testcases by targeting cases with the largest coverage of functions and source files under test, which reduces the time and disk space overhead necessary for adding and testing new code. Together, these functions result in higher quality code shipped to customers.

The innovative AnaCov tool provides developers and QA engineers with multiple automated capabilities to simplify, speed up, and standardize code coverage analysis. Through its use in production environments, we demonstrate the AnaCov tool successfully simplifies the activities related to code coverage analysis, making the tool invaluable for software testing purposes. Users with any level of expertise can quickly and easily interface with coverage data, perform the necessary analysis, and develop a future plan to provide better code coverage in their test suites, without sacrificing huge amounts of time or disk space.