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Yuji Kamayachi

dblp:71/5785 · DBLP profile ↗
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2ranked-venue papers
0as first author
0since 2021 · last 1989
—ORCID · none

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

Software engineering, systems software and programming languages · 2

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
2 papers
Empirical software engineering · 100%

Topics — the 4 heaviest of 5, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Empirical software engineering › software defect prediction
program error prediction
0.021989
An Empirical Study of a Model for Program Error Prediction · IEEE Trans. Software Eng. 1989
An Empirical Study of a Model for Program Error Prediction · ICSE 1985
Empirical software engineering › mining software repositories
defect prediction
0.011989
An Empirical Study of a Model for Program Error Prediction · IEEE Trans. Software Eng. 1989
Empirical software engineering
software analytics
0.011985
An Empirical Study of a Model for Program Error Prediction · ICSE 1985
Empirical software engineering
fault prediction
0.011985
An Empirical Study of a Model for Program Error Prediction · ICSE 1985

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

statistical analysis · 0.0
YearPublicationVenuePosition
1989 An Empirical Study of a Model for Program Error Prediction
abstract
A model is presented for estimating the number of errors remaining in a program at the beginning of the testing phase of development. The relationships between the errors occurring in a program and the various factors that affect software development, such as programmer skill, are statistically analyzed. The model is then derived using the factors significantly identified in the analysis. On the basis of data collected during the development of large-scale software systems, it is shown that factors such as frequency of program specification change, programmer skill, and volume of program design documentation are significant and that the model based on these factors is more reliable than conventional error prediction methods based on program size alone.>
Muneo Takahashi, Yuji Kamayachi
IEEE Trans. Software Eng.2
1985 An Empirical Study of a Model for Program Error Prediction
Muneo Takahashi, Yuji Kamayachi
ICSE2