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Why Do We not Learn from Defects? Towards Defect-Driven Software Process Improvement

Niklas Mellegård (Institutionen för data- och informationsteknik, Software Engineering (Chalmers)) ; Miroslaw Staron ; Fredrik Törner
1st International Conference on Model-Driven Engineering and Software Development, MODELSWARD 2013; Barcelona; Spain; 19 February 2013 through 21 February 2013 p. 297-303. (2013)
[Konferensbidrag, övrigt]

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.

Nyckelord: Software Engineering: Software Quality: Metrics/Measurement: Defect classification



Denna post skapades 2012-12-20. Senast ändrad 2016-11-09.
CPL Pubid: 168496

 

Institutioner (Chalmers)

Institutionen för data- och informationsteknik, Software Engineering (Chalmers)
Institutionen för data- och informationsteknik (GU) (GU)

Ämnesområden

Programvaruteknik

Chalmers infrastruktur

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