Two key design characteristics of machine learning (ML) systems---their ever-improving nature, and learning-based emergent functional behavior---create a moving target, posing new challenges for authoring/maintaining functional regression tests. We ...

Traditional methods for performance appraisal are not suitable for agile fast-paced software companies. This has been a realization in the software industry since the early adoption of agile methodologies. Nonetheless, software companies are still ...

Modern code review is a common and essential practice employed in both industrial and open-source projects to improve software quality, share knowledge, and ensure conformance with coding standards. During code review, developers may inspect and discuss ...

Availability issues of industrial microservice systems (e.g., drop of successfully placed orders and processed transactions) directly affect the running of the business. These issues are usually caused by various types of service anomalies which ...

As an infrastructure for data persistence and analysis, Database Management Systems (DBMSs) are the cornerstones of modern enterprise software. To improve their correctness, the industry has been applying blackbox fuzzing for decades. Recently, the ...

Fuzzing is a technique widely used in vulnerability detection. The process usually involves writing effective fuzz driver programs, which, when done manually, can be extremely labor intensive. Previous attempts at automation leave much to be desired, in ...

With over 500,000 commits and more than 700 contributors, the Android platform is undoubtedly one of the largest industrial-scale software projects. This project provides the Android API, and developers heavily rely on this API to develop their Android ...

Open source software has drawn more and more attention from researchers, developers and companies nowadays. Meanwhile, many Chinese technology companies are embracing open source and choosing to open source their projects. Nevertheless, most previous ...

Despite engineering workflows that aim to prevent buggy code from being deployed, bugs still make their way into the Facebook app. When symptoms of these bugs, such as user submitted reports and automatically captured crashes, are reported, finding ...

Agile and DevOps are widely adopted by the industry. Hence, integrating security activities with industrial practices, such as continuous integration (CI) pipelines, is necessary to detect security flaws and adhere to regulators' demands early. In this ...

Traditionally, mutation testing generates an abundance of small deviations of a program, called mutants. At industrial systems the scale and size of Facebook's, doing this is infeasible. We should not create mutants that the test suite would likely fail ...

Security is critical to the adoption of open source software (OSS), yet few automated solutions currently exist to help detect and prevent malicious contributions from infecting open source repositories. On GitHub, a primary host of OSS, repositories ...

Background: Data errors are a common challenge in machine learning (ML) projects and generally cause significant performance degradation in ML-enabled software systems. To ensure early detection of erroneous data and avoid training ML models using bad ...

API developers have been working hard to evolve APIs to provide more simple, powerful, and robust API libraries. Although API evolution has been studied for multiple domains, such as Web and Android development, API evolution for deep learning ...

With the promise of reliability in cloud, more enterprises are migrating to cloud. The process of continuous integration/deployment (CICD) in cloud connects developers who need to deliver value faster and more transparently with site reliability ...

The move from boxed products to services and the widespread adoption of cloud computing has had a huge impact on the software development life cycle and DevOps processes. Particularly, incident management has become critical for developing and operating ...

Program analysis can assist software development but its use is limited by a number of usability issues, including false positives and integration issues. Previous systems have show significant progress addressing these by using a data-driven approach ...

We explore the application of Information Retrieval (IR) based bug localization methods at a large industrial setting, Facebook. Facebook's code base evolves rapidly, with thousands of code changes being committed to a monolithic repository every day. ...

Engineering software to be inclusive of all those that might/could/should use the software is important. However, today, data used to engineer software can have inherent biases (e.g. gender identity) with inclusiveness concerns. While much attention has ...

ML-driven software is heralded as the next major advancement in software engineering; existing software today can benefit from being evolved to be ML-driven. In this paper, we contribute practical knowledge about evolving software to be ML-driven, ...