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Keshav Sharma

dblp:201/5399 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2017
—ORCID · unresolved

Domains — the database's venue-derived domains; a paper can count in several

Computer networks · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Software engineering, system software, and programming languages
1 paper
Operating systems · 44% Program analysis · 44% Software maintenance and evolution · 13%

Topics — the 2 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Program analysis › dynamic analysis › instrumentation
bytecode instrumentation
0.312017
Reptor: Enabling API Virtualization on Android for Platform Openness · MobiSys 2017
Operating systems › mobile systems
mobile operating systems
0.312017
Reptor: Enabling API Virtualization on Android for Platform Openness · MobiSys 2017

Methods — techniques the papers use, named apart from their topics

bytecode instrumentation · 0.3
YearPublicationVenuePosition
2017 Reptor: Enabling API Virtualization on Android for Platform Openness
abstract
This paper proposes a new technique that enables open innovation in mobile platforms. Our technique allows third-party developers to modify, instrument, or extend platform API calls and deploy their modifications seamlessly. The uniqueness of our technique is that it enables modifications completely at the app layer without requiring any platform-level changes. This allows practical openness---third parties can easily distribute their modifications for a platform without the need to update the entire platform. To demonstrate the benefits of our technique, we have developed a prototype on Android called Reptor and used it to instrument real-world apps with novel functionality. Our evaluation in realistic scenarios shows that Reptor has little overhead in performance and energy, and only modest overhead in memory usage that ranges from 0.6% to 10% for the observed worst cases.
Taeyeon Ki, Alexander Simeonov, Bhavika Pravin Jain, Chang Min Park, Keshav Sharma, Karthik Dantu, Steven Y. Ko, Lukasz Ziarek
MobiSys5