B

Bavishi, Rohan ; Pradel, Michael ; Sen, Koushik (2017):
Context2Name: A Deep Learning-Based Approach to Infer Natural Variable Names from Usage Contexts.
[Report]

H

Habib, Andrew (2021):
Learning to Find Bugs in Programs and their Documentation. (Publisher's Version)
Darmstadt, Technische Universität,
DOI: 10.26083/tuprints-00017377,
[Ph.D. Thesis]

P

Pradel, Michael ; Sen, Koushik (2017):
Deep Learning to Find Bugs.
[Report]

Patra, Jibesh ; Pradel, Michael (2016):
Learning to Fuzz: Application-Independent Fuzz Testing with Probabilistic, Generative Models of Input Data.
[Report]

S

Staicu, Cristian-Alexandru (2020):
Enhancing the Security and Privacy of Full-Stack JavaScript Web Applications.
Darmstadt, Technische Universität,
DOI: 10.25534/tuprints-00011808,
[Ph.D. Thesis]

Selakovic, Marija (2019):
Actionable Program Analyses for Improving Software Performance.
Darmstadt, Technische Universität,
[Ph.D. Thesis]

Staicu, Cristian-Alexandru ; Pradel, Michael (2017):
Freezing the Web: A Study of ReDoS Vulnerabilities in JavaScript-based Web Servers.
[Article]

Staicu, Cristian-Alexandru ; Pradel, Michael ; Livshits, Benjamin (2016):
Understanding and Automatically Preventing Injection Attacks on Node.js.
[Report]