What is he best known for?
The fields of study he is best known for:
- Programming language
- Algorithm
- Software
Shuvendu K. Lahiri focuses on Programming language, Predicate abstraction, Theoretical computer science, Abstract interpretation and True quantified Boolean formula.
As part of his studies on Programming language, Shuvendu K. Lahiri frequently links adjacent subjects like Reachability.
His work deals with themes such as Control flow, Uninterpreted function, Reachability problem and Modulo, which intersect with Predicate abstraction.
His research in Theoretical computer science intersects with topics in Syntax, First-order logic and Counterexample.
He has included themes like Predicate, Unbounded system, Conjunctive normal form and Syntactic predicate in his Abstract interpretation study.
His study explores the link between Correctness and topics such as Decidability that cross with problems in Model checking.
His most cited work include:
- Feedback-Directed Random Test Generation (613 citations)
- Modeling and Verifying Systems Using a Logic of Counter Arithmetic with Lambda Expressions and Uninterpreted Functions (224 citations)
- SYMDIFF: a language-agnostic semantic diff tool for imperative programs (146 citations)
What are the main themes of his work throughout his whole career to date?
His primary areas of study are Programming language, Theoretical computer science, Predicate abstraction, Set and Model checking.
His Programming language study frequently draws connections to other fields, such as Reachability.
His Theoretical computer science research includes themes of Directed acyclic graph, First-order logic and Concurrency.
His Predicate abstraction study combines topics from a wide range of disciplines, such as Abstract interpretation, True quantified Boolean formula and Predicate.
His Set research also works with subjects such as
- Simple, which have a strong connection to Inference,
- Simplex that connect with fields like Linear form,
- Conjunctive normal form which intersects with area such as Software verification.
The various areas that he examines in his Model checking study include Program analysis, Rule of inference, Datalog, Soundness and Formal verification.
He most often published in these fields:
- Programming language (44.54%)
- Theoretical computer science (36.97%)
- Predicate abstraction (21.01%)
What were the highlights of his more recent work (between 2016-2021)?
- Programming language (44.54%)
- Theoretical computer science (36.97%)
- Software engineering (6.72%)
In recent papers he was focusing on the following fields of study:
His scientific interests lie mostly in Programming language, Theoretical computer science, Software engineering, Static analysis and DevOps.
His work carried out in the field of Programming language brings together such families of science as Automatic inference, Code and Benchmark.
Shuvendu K. Lahiri studies Theoretical computer science, focusing on Model checking in particular.
His Software engineering study also includes fields such as
- Smart contract which connect with Liveness, Class, Domain-specific language and Toolchain,
- Solidity which is related to area like Correctness, Workflow and Formal verification.
His study in Static analysis is interdisciplinary in nature, drawing from both Program analysis, Scalability, Rule of inference, Datalog and Synchronization.
His research integrates issues of Representation and Parsing in his study of DevOps.
Between 2016 and 2021, his most popular works were:
- Formal Specification and Verification of Smart Contracts for Azure Blockchain (38 citations)
- Code vectors: understanding programs through embedded abstracted symbolic traces (31 citations)
- Optimizing test placement for module-level regression testing (15 citations)
In his most recent research, the most cited papers focused on:
- Programming language
- Algorithm
- Software
Shuvendu K. Lahiri mainly focuses on Programming language, Theoretical computer science, Reliability engineering, Benchmark and Linux kernel.
His research on Programming language frequently connects to adjacent areas such as Automatic summarization.
His studies in Theoretical computer science integrate themes in fields like Relation and Concurrency.
His Reliability engineering research is multidisciplinary, incorporating elements of Inference, Robustness and Reference implementation.
His Benchmark research is multidisciplinary, incorporating perspectives in Symbolic execution, Embedding, Word, Representation and Code.
He integrates Linux kernel and Suite in his studies.
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