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S. Jayaprakash

dblp:94/3030 · DBLP profile ↗
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4ranked-venue papers
1as first author
1since 2021 · last 2024
—ORCID · unresolved

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

Software engineering, systems software and programming languages · 2 · 1 first-authorGraphics, computer vision, multimedia, augmented reality and games · 1 · 1 since 2021Applied, interdisciplinary, general and emerging computing · 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
Empirical software engineering · 100%

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

TopicWeightPapersLastEvidence papers
Empirical software engineering › software metrics
control flow complexity
0.011991
Properties of Control-Flow Complexity Measures · IEEE Trans. Software Eng. 1991
Empirical software engineering › software metrics
software complexity metrics
0.011991
Properties of Control-Flow Complexity Measures · IEEE Trans. Software Eng. 1991
Empirical software engineering › software metrics
software metrics validation
0.011991
Properties of Control-Flow Complexity Measures · IEEE Trans. Software Eng. 1991

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

formalization · 0.0composition analysis · 0.0
YearPublicationVenuePosition
2024 Human activity-based anomaly detection and recognition by surveillance video using kernel local component analysis with classification by deep learning techniques
M. D. Anto Praveena, P. Udayaraju, R. Krishna Chaitanya, S. Jayaprakash, M. Kalaiyarasi
Multim. Tools Appl.4
2010 Identification of Cognitive Processes of Effective and Ineffective Students During Computer Programming
abstract
Identifying the set of cognitive processes (CPs) a student can go through during computer programming is an interesting research problem. It can provide a better understanding of the human aspects in computer programming process and can also contribute to the computer programming education in general. The study identified the presence of a set of 42 CPs in computer programming (C language). The study used Verbal Protocol Analysis (VPA) in identifying these CPs. It is a qualitative study on the Verbal Protocols (VPs) of 19 students. Some of the CPs have been inferred by referring to the literature and some have been additionally identified by this study. The additional CPs found are confusion, hypothesis, interrogation, iteration, monitoring, recollection, recurrence, and translation. It is observed that programming involves the interplay of lower and higher CPs and needs various cognitive skills, which increase the processing load on the brain and make the programming process difficult and complex to learn and practice. The same set of CPs was found in both the effective and ineffective subjects. The research results can provide deeper knowledge to teachers on cognitive aspects of programming and the cognitive behavior of students during the programming process.
Renumol V. G, D. Janaki Ram, S. Jayaprakash
ACM Trans. Comput. Educ.3
1996 Critical Analysis of "A Fault-Tolerant Algorithm for Mutual Exclusion in a Distributed System"
S. Jayaprakash, C. R. Muthukrishnan
J. Syst. Softw.1
1991 Properties of Control-Flow Complexity Measures
abstract
The authors attempt to formalize some properties which any reasonable control-flow complexity measure must satisfy. Since large programs are often built by sequencing and nesting of simpler constructs, the authors explore how control-flow complexity measures behave under such compositions. They analyze five existing control flow complexity measures-cyclomatic number, total adjusted complexity, scope ratio, MEBOW, and NPATH. The analysis reveals the strengths and weaknesses of these control flow complexity measures.>
K. B. Lakshmanan, S. Jayaprakash, P. K. Sinha
IEEE Trans. Software Eng.2