186 citations · 592 across the 23 of their papers we have counts for
7 papers · 1 filter
TypeWriter: Neural Type Prediction with Search-based Validation
Michael Pradel, Georgios Gousios, Jason Liu +1
Maintaining large code bases written in dynamically typed languages, such as JavaScript or Python, can be challenging due to the absence of type annotations: simple data compatibil…
Type Safety with JSON Subschema
Andrew Habib, Avraham Shinnar, Martin Hirzel +1
JSON is a popular data format used pervasively in web APIs, cloud computing, NoSQL databases, and increasingly also machine learning. JSON Schema is a language for declaring the st…
IdBench: Evaluating Semantic Representations of Identifier Names in Source Code
Yaza Wainakh, Moiz Rauf, Michael Pradel
Identifier names convey useful information about the intended semantics of code. Name-based program analyses use this information, e.g., to detect bugs, to predict types, and to im…
An Empirical Study of Information Flows in Real-World JavaScript
Cristian-Alexandru Staicu, Daniel Schoepe, Musard Balliu +2
Information flow analysis prevents secret or untrusted data from flowing into public or trusted sinks. Existing mechanisms cover a wide array of options, ranging from lightweight t…
Neural Bug Finding: A Study of Opportunities and Challenges
Andrew Habib, Michael Pradel
Static analysis is one of the most widely adopted techniques to find software bugs before code is put in production. Designing and implementing effective and efficient static analy…
Small World with High Risks: A Study of Security Threats in the npm Ecosystem
Markus Zimmermann, Cristian-Alexandru Staicu, Cam Tenny +1
The popularity of JavaScript has lead to a large ecosystem of third-party packages available via the npm software package registry. The open nature of npm has boosted its growth, p…