Why Do We not Learn from Defects? Towards Defect-Driven Software Process Improvement
Paper i proceeding, 2013

In this paper, we put forth the thesis that state-of-the-art defect classification schemes – such as ODC and IEEE Std. 1044 – have failed to meet their target; limited industrial adoption is taken as part of the evidence combined with published studies on model driven software development. Notwithstanding, a number of publications show that defect reports can provide valuable information about common, important, or dangerous problems with software products. In this paper, we present the synthesis of two industrial case studies that illustrate that even expert judgement can be deceptive; demonstrating the need for more objective evidence to allow project stakeholder to make informed decisions, and that defect classification is one effective means to that end. Finally, we propose a roadmap that will contribute to improving the defect classification approach, which in consequence will lead to a wider industrial adoption.

software engineering

defect classification

software quality



Niklas Mellegård

Chalmers, Data- och informationsteknik, Software Engineering

Miroslaw Staron

Göteborgs universitet

Fredrik Törner

Volvo Cars

MODELSWARD 2013 - Proceedings of the 1st International Conference on Model-Driven Engineering and Software Development


1st International Conference on Model-Driven Engineering and Software Development, MODELSWARD
Barcelona, Spain,


Data- och informationsvetenskap


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