Software Engineering and Programming Languages

Type migration is a refactoring activity in which an existing type is replaced with another one throughout the source code. Manually performing type migration is tedious as programmers need to find all instances of the type to be migrated, along with its dependencies that propagate over assignment operations, method hierarchies, and subtypes. Existing automated approaches for type migration are...

Organizations have a variety of options to help their software developers become their most productive selves, from modifying office layouts, to investing in better tools, to cleaning up the source code. But which options will have the biggest impact? Drawing from the literature in software engineering and industrial/organizational psychology to identify factors that correlate with...

Maintaining awareness of useful tools is a substantial challenge for developers. Physical newsletters are a simple technique to inform developers about tools. In this paper, we evaluate such a technique, called Testing on the Toilet, by performing a mixed-methods case study. We first quantitatively evaluate how effective this technique is by applying statistical causal inference over six years...

At Google we have found tens of thousands of security and robustness bugs by fuzzing C and C++ libraries. To fuzz a library, a fuzzer requires a fuzz driver—which exercises some library code—to which it can pass inputs. Unfortunately, writing fuzz drivers remains a primarily manual exercise, a major hindrance to the widespread adoption of fuzzing. In this paper, we address this major hindrance...

Programmers spend a substantial amount of time manually repairing code that does not compile. We observe that the repairs for any particular error class typically follow a pattern and are highly mechanical. We propose a novel approach that automatically learns these patterns with a deep neural network and suggests program repairs for the most costly classes of build-time compilation failures....

Continuous Integration traditionally relies on testing every code commit with all impacted tests. This practice requires considerable computational resources, which at Google scale, results in delayed test results and high operational costs. To deal with this issue and provide fast feedback, test selection and prioritization methods aim to execute the tests which are most likely to reveal...

Mutation testing assesses test suite efficacy by inserting small faults into programs and measuring the ability of the test suite to detect them. It is widely considered the strongest test criterion in terms of finding the most faults and it subsumes a number of other coverage criteria. Traditional mutation analysis is computationally prohibitive which hinders its adoption as an industry...

Monolithic source code repositories (repos) are used by several large tech companies, but little is known about their advantages or disadvantages compared to multiple per-project repos. This paper investigates the relative tradeoffs by utilizing a mixed-methods approach. Our primary contribution is a survey of engineers who have experience with both monolithic repos and multiple, per-project...

Growth in Google’s code size and feature churn rate has seen increased reliance on continuous integration (CI) and testing to maintain quality. Even with enormous resources dedicated to testing, we are unable to regression test each code change individually, resulting in increased lag time between code check-ins and test result feedback to developers. We report results of a project that aims to...

Quickly identifying and fixing code changes that introduce regressions is critical to keep the momentum on software development, especially in very large scale software repositories with rapid development cycles, such as at Google. Identifying and fixing such regressions is one of the most expensive, tedious, and time consuming tasks in the software development life-cycle. Therefore, there is a...

Google's monolithic repository provides a common source of truth for tens of thousands of developers around the world. This article outlines the scale of Google’s codebase, describes Google’s custom-built monolithic source repository, and discusses the reasons behind choosing this model. We provide background on the systems and workflows that make managing and working productively with a large...

With the advent of large code repositories and sophisticated search capabilities, code search is increasingly becoming a key software development activity. In this work we shed some light into how developers search for code through a case study performed at Google, using a combination of survey and log-analysis methodologies. Our study provides insights into what developers are doing and trying...

Static analysis tools help developers find bugs, improve code readability, and ensure consistent style across a project. However, these tools can be difficult to smoothly integrate with each other and into the developer workflow, particularly when scaling to large codebases. We present Tricorder, a program analysis platform aimed at building a data-driven ecosystem around program analysis. We...

A (build) target specifies the information that is needed to automatically build a software artifact. This paper focuses on underutilized targets—an important dependency problem that we identified at Google. An underutilized target is one with files not needed by some of its dependents. Underutilized targets result in less modular code, overly large artifacts, slow builds, and unnecessary build...

Building is an integral part of the software development process. However, little is known about the errors occurring in this process. In this paper, we present an empirical study of 26.6 million builds produced during a period of nine months by thousands of developers. We describe the workflow through which those builds are generated, and we analyze failure frequency, error types, and...

Maintaining large codebases can be a challenging endeavour. As new libraries, APIs and standards are introduced, old code is migrated to use them. To provide as clean and succinct an interface as possible for developers, old APIs are ideally removed as new ones are introduced. In practice, this becomes difficult as automatically finding and transforming code in a semantically correct way can be...

We discuss Refaster, a tool that uses normal, compilable before-and-after examples of Java code to specify a Java refactoring. Refaster has been used successfully by the Java Core Libraries Team at Google to perform a wide variety of refactorings across Google's massive Java codebase. Our main contribution is that a large class of useful refactorings can be expressed in pure Java, without a...