I have 10 years of experience building tools and processes for other engineers in the biggest software engineering enterprise in the world. I have built cutting edge tools that scale to tens of thousands of engineers and billions of lines of code. I have extensive experience developing planetary scale distributed systems.
I am a world class expert in code coverage, mutation testing, large scale code analysis, large scale refactoring and machine learning.
I manage an organization of ~25 engineers, leading multiple teams focused on improving the internal developer experience at Google.
Senior Staff Software Engineer at Google (2020. - present)
- Technical lead in the Engineering Productivity group. Technical equivalent to Senior Engineering Manager.
Staff Software Engineer at Google (2016. - 2020.)
- Technical lead in the Engineering Productivity group. Technical equivalent to Engineering Manager.
Senior Software Engineer, Tools and Infrastructure at Google (2014. - 2016.)
- Technical lead in the Ads Engineering Productivity group. Conceptualized, designed, implemented and owned code coverage infrastructure for the whole company. Implemented large scale code analysis infrastructure.
Software Engineer, Tools and Infrastructure at Google (2011. - 2014.)
- Implemented bespoke developer infrastructure for Google Shopping teams.
Intern, Software Engineer at Google (2010.)
- Implemented a load and performance testing framework including result visualization.
IOI 2007 - Evaluation Committee (2007.)
- One of the two authors of the IOI 2007 evaluation system.
Croatian Open Competition in Informatics - Scientific Committee (2007. - 2011.)
- One of the key developers of the evaluation system that was used for more than a decade for the Croatian Open Competition in Informatics. I organized task authors and contributed many tasks myself. As the chief of the committee I was the person ultimately responsible for the integrity of both the international open competition and the national proctored competition.
- Practical Mutation Testing at Scale: A view from Google (IEEE TSE 2021.)
- Automatically Generating Machine Learning Models for Software Tools That Operate on Source Code (Us Pat. Application No. 20210132915)
- Does mutation testing improve testing practices? (ICSE 2021.)
- Use of Machine Learning To Generate Estimates of Code Review Time and Effort (TD Commons)
- Identification of Low-value Code to Improve Efficiency of Automated Code Analysis (TD Commons)
- Techniques For Easy and Efficient Manipulations of Large Codebases (TD Commons)
- Code coverage at Google (ESEC/FSE 2019.)
- State of Mutation Testing at Google (ICSE - SEIP 2018.)
- An Industrial Application of Mutation Testing: Lessons, Challenges, and Research Directions (ICSTW - Mutation 2018.)
- Process for displaying test coverage data during code reviews (US Pat. No. 9,405,662)
- Universität Passau, Faculty of Computer Science and Mathematics - Doctor of Science (2018. - ongoing)
- University of Zagreb, Faculty of electrical engineering and computing - Master of Science (2010. - 2011.)
- University of Zagreb, Faculty of electrical engineering and computing - Bachelor of Science (2010. - 2011.)