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Jacek Jachner

dblp:22/4229 · DBLP profile ↗
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1ranked-venue papers
1as first author
0since 2021 · last 1984
—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

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
Program analysis · 100%

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

TopicWeightPapersLastEvidence papers
Program analysis
data flow analysis
0.011984
Data Flow Anomaly Detection · IEEE Trans. Software Eng. 1984
Program analysis › data flow analysis
data flow anomaly detection
0.011984
Data Flow Anomaly Detection · IEEE Trans. Software Eng. 1984
Program analysis
static analysis
0.011984
Data Flow Anomaly Detection · IEEE Trans. Software Eng. 1984

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

graph-based path analysis · 0.0
YearPublicationVenuePosition
1984 Data Flow Anomaly Detection
abstract
The occurrence of a data flow anomaly is often an indication of the existence of a programming error. The detection of such anomalies can be used for detecting errors and to upgrade software quality. This paper introduces a new, efficient algorithm capable of detecting anomalous data flow patterns in a program represented by a graph. The algorithm based on static analysis scans the paths entering and leaving each node of the graph to reveal anomalous data action combinations. An algorithm implementing this type of approach was proposed by Fosdick and Osterweil [2]. Our approach presents a general framework which not only fillls a gap in the previous algorithm, but also provides time and space improvements.
Jacek Jachner, Vinod K. Agarwal
IEEE Trans. Software Eng.1