Ground truth deficiencies in software engineering: when codifying the past can be counterproductive
Artikel i vetenskaplig tidskrift, 2021

Many software engineering tools build and evaluate their models based on historical data to support development and process decisions. These models help us answer numerous interesting questions, but have their own caveats. In a real-life setting, the objective function of human decision-makers for a given task might be influenced by a whole host of factors that stem from their cognitive biases, subverting the ideal objective function required for an optimally functioning system. Relying on this data as ground truth may give rise to systems that end up automating software engineering decisions by mimicking past sub-optimal behaviour. We illustrate this phenomenon and suggest mitigation strategies to raise awareness.

Tools

Task analysis

Machine learning

Software

Computer bugs

Software engineering

Data models

Författare

Eray Tuzun

Bilkent Universitesi

Hakan Erdogmus

Carnegie Mellon University (CMU)

Maria Teresa Baldassarre

Universita degli Studi di Bari Aldo Moro

Michael Felderer

University of Innsbruck

Robert Feldt

Chalmers, Data- och informationsteknik, Software Engineering, Software Engineering for Testing, Requirements, Innovation and Psychology

Burak Turhan

Monash University

IEEE Software

0740-7459 (ISSN)

Vol. In Press

Ämneskategorier

Programvaruteknik

Systemvetenskap

Datavetenskap (datalogi)

DOI

10.1109/MS.2021.3098670

Mer information

Senast uppdaterat

2021-08-09