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Abhilash Gupta

dblp:177/9781 · DBLP profile ↗
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2ranked-venue papers
1as first author
2since 2021 · last 2022
—ORCID · none

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

Software engineering, systems software and programming languages · 1 · 1 first-author · 1 since 2021Human-computer interaction and ubiquitous computing · 1 · 1 since 2021

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
Software testing · 100%
Human-computer interaction and pervasive computing
1 paper
Human-AI interaction · 100%
Network and information security
1 paper
Cyber-physical and IoT security · 100%

Topics — the 4 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Software testing
fuzzing
0.612022
CLIFuzzer: mining grammars for command-line invocations · ESEC/SIGSOFT FSE 2022
Software testing
test input generation
0.612022
CLIFuzzer: mining grammars for command-line invocations · ESEC/SIGSOFT FSE 2022
Human-AI interaction
intelligent user interfaces
0.512021
Investigating Car Drivers' Information Demand after Safety and Security Critical Incidents · CHI 2021
Cyber-physical and IoT security
automotive security
0.112021
Investigating Car Drivers' Information Demand after Safety and Security Critical Incidents · CHI 2021

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

thematic analysis · 1.0mixed-methods survey · 1.0correspondence analysis · 1.0grammar mining · 0.6
YearPublicationVenuePosition
2022 CLIFuzzer: mining grammars for command-line invocations
abstract
The behavior of command-line utilities can be very much influenced by passing command-line options and arguments—configuration settings that enable, disable, or otherwise influence parts of the code to be executed. Hence, systematic testing of command-line utilities requires testing them with diverse configurations of supported command-line options.
Abhilash Gupta, Rahul Gopinath, Andreas Zeller
ESEC/SIGSOFT FSE1
2021 Investigating Car Drivers' Information Demand after Safety and Security Critical Incidents
abstract
Modern cars include a vast array of computer systems designed to remove the burden on drivers and enhance safety. As cars are evolving towards autonomy and taking over control, e.g. in the form of autopilots, it becomes harder for drivers to pinpoint the root causes of a car’s malfunctioning. Drivers may need additional information to assess these ambiguous situations correctly. However, it is yet unclear which information is relevant and helpful to drivers in such situations. Hence, we conducted a mixed-methods online survey (N = 60) on Amazon MTurk where we exposed participants to two security- and safety-critical situations with one of three different explanations. We applied Thematic and Correspondence Analysis to understand which factors in these situations moderate drivers’ information demand. We identified a fundamental information demand across scenarios that is expanded by error-specific information types. Moreover, we found that it is necessary to communicate error sources, since drivers might not be able to identify them correctly otherwise. Thereby, malicious intrusions are typically perceived as more critical than technical malfunctions.
Lea Gröber, Matthias Fassl, Abhilash Gupta, Katharina Krombholz
CHI3