Search Results for author: Richard Torkar

Found 2 papers, 1 papers with code

Applying Bayesian Analysis Guidelines to Empirical Software Engineering Data: The Case of Programming Languages and Code Quality

no code implementations29 Jan 2021 Carlo A. Furia, Richard Torkar, Robert Feldt

The high-level conclusions of our exercise will be that Bayesian statistical techniques can be applied to analyze software engineering data in a way that is principled, flexible, and leads to convincing results that inform the state of the art while highlighting the boundaries of its validity.

Software Engineering

An empirical study of Linespots: A novel past-fault algorithm

1 code implementation18 Jul 2020 Maximilian Scholz, Richard Torkar

This paper proposes the novel past-faults fault prediction algorithm Linespots, based on the Bugspots algorithm.

Software Engineering Methodology 68W40 (Primary), 62J99 (Secondary) D.2; G.3

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