Exploring the Role of Automation in Duplicate Bug Report Detection: An Industrial Case Study
Paper i proceeding, 2024

Duplicate bug reports can increase technical debt and tester work-load in long-running software projects. Many automated techniques have been proposed to detect potential duplicate reports. However, such techniques have not seen widespread industrial adoption. Our objective in this study is to better understand how automated techniques could effectively be employed within a tester's duplicate detection workflow. We are particularly interested in exploring the potential of a human-in-The-loop scenario where tools and humans work together to make duplicate determinations.We have conducted an industrial case study where we characterize the current tester workflow. Based on this characterization, we have developed Bugle-An automated technique based on a complex language model that suggests potential duplicates to testers based on an input bug description that can be freely reformulated if the initial suggestions are irrelevant. We compare the assessments of Bugle and testers of varying experience, capturing how often-And why-opinions might differ between the two, and comparing the strengths and limitations of automated techniques to the current tester workflow. We additionally examine the influence of knowledge and biases on accuracy, the suitability of language models, and the limitations affecting duplicate detection techniques.

software testing

natural language processing

duplicate bug reports

bug reports

automated duplicate bug report detection

Författare

Malte Götharsson

Göteborgs universitet

Karl Stahre

Göteborgs universitet

Gregory Gay

Göteborgs universitet

Software Engineering 1

Francisco Gomes de Oliveira Neto

Göteborgs universitet

Proceedings - 2024 IEEE/ACM International Conference on Automation of Software Test, AST 2024

193-203
9798400705885 (ISBN)

5th ACM/IEEE International Conference on Automation of Software Test, AST 2024, co-located with the 46th International Conference on Software Engineering, ICSE 2024
Lisbon, Portugal,

Ämneskategorier

Datavetenskap (datalogi)

Datorsystem

DOI

10.1145/3644032.3644450

Mer information

Senast uppdaterat

2024-08-02