What is he best known for?
The fields of study he is best known for:
- Programming language
- Operating system
- The Internet
Benjamin Livshits mainly focuses on JavaScript, Programming language, Static analysis, Web application and Operating system.
His JavaScript study introduces a deeper knowledge of World Wide Web.
His Programming language research is multidisciplinary, incorporating elements of Query language and Theoretical computer science.
His Static analysis research is multidisciplinary, incorporating perspectives in Call graph, Source lines of code, Software engineering and Static program analysis.
The study incorporates disciplines such as Java, Cross-site scripting, Server-side and Database in addition to Web application.
His study explores the link between Operating system and topics such as Embedded system that cross with problems in Web modeling, Web development, Web application security, Address space and Heap.
His most cited work include:
- Finding application errors and security flaws using PQL: a program query language (467 citations)
- DynaMine: finding common error patterns by mining software revision histories (323 citations)
- ZOZZLE: fast and precise in-browser JavaScript malware detection (225 citations)
What are the main themes of his work throughout his whole career to date?
The scientist’s investigation covers issues in Computer security, JavaScript, World Wide Web, Programming language and Web application.
Benjamin Livshits has researched Computer security in several fields, including Software security assurance and Denial-of-service attack.
As a part of the same scientific family, Benjamin Livshits mostly works in the field of JavaScript, focusing on Distributed computing and, on occasion, Scalability.
His Programming language research includes themes of Theoretical computer science and Code.
His research integrates issues of Java, Cross-site scripting, Server-side and Scripting language in his study of Web application.
His research in Static analysis intersects with topics in Call graph, Graph, Software engineering and Static program analysis.
He most often published in these fields:
- Computer security (21.50%)
- JavaScript (18.50%)
- World Wide Web (16.50%)
What were the highlights of his more recent work (between 2017-2021)?
- Computer security (21.50%)
- Blockchain (4.50%)
- Information retrieval (5.50%)
In recent papers he was focusing on the following fields of study:
His primary areas of study are Computer security, Blockchain, Information retrieval, JavaScript and Ad blocking.
His Computer security study combines topics from a wide range of disciplines, such as Software deployment and Denial-of-service attack.
His biological study spans a wide range of topics, including Hit ratio and Artificial intelligence.
His JavaScript study incorporates themes from Classifier, Web application, Pipeline and Overhead.
Benjamin Livshits has included themes like Graph, Data flow diagram, Static analysis and Asynchronous communication, Asynchrony in his Web application study.
His research combines Code and Programming language.
Between 2017 and 2021, his most popular works were:
- SYNODE: Understanding and Automatically Preventing Injection Attacks on NODE.JS. (37 citations)
- EthIR: A Framework for High-Level Analysis of Ethereum Bytecode (23 citations)
- Smart Contract Vulnerabilities: Does Anyone Care? (22 citations)
In his most recent research, the most cited papers focused on:
- Programming language
- Operating system
- The Internet
Blockchain, Computer security, Ad blocking, JavaScript and Information retrieval are his primary areas of study.
He studied Computer security and Denial-of-service attack that intersect with Transfer system and Security token.
His work carried out in the field of JavaScript brings together such families of science as Code injection, Sandbox, Key, Web application and Overhead.
His studies deal with areas such as Security policy, Static analysis, Asynchrony, Asynchronous communication and Callback as well as Web application.
Benjamin Livshits interconnects Classifier, Web page, Deep learning and Rendering in the investigation of issues within Information retrieval.
His work in the fields of Programming language, such as Graph, overlaps with other areas such as Gas consumption.
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