Project Data Incorporating Qualitative Facts for Improved Software Defect Prediction
Fenton, Norman, Neil, Martin, Marsh, William, Hearty, Peter, Radlinski, Lukasz and Krause, Paul (2007) Project Data Incorporating Qualitative Facts for Improved Software Defect Prediction In: Third International Workshop on Predictor Models in Software Engineering (PROMISE'07: ICSE Workshops 2007).
To make accurate predictions of attributes like defects found in complex software projects we need a rich set of process factors. We have developed a causal model that includes such process factors, both quantitative and qualitative. The factors in the model were identified as part of a major collaborative project. A challenge for such a model is getting the data needed to validate it. We present a dataset, elicited from 31 completed software projects in the consumer electronics industry, which we used for validation. The data were gathered using a questionnaire distributed to managers of recent projects. The dataset will be of interest to other researchers evaluating models with similar aims. We make both the dataset and causal model available for research use.
|Item Type:||Conference or Workshop Item (UNSPECIFIED)|
|Additional Information:||Third International Workshop on Predictor Models in Software Engineering (PROMISE'07), pp. 2-2.© 2007 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.|
|Divisions:||Faculty of Engineering and Physical Sciences > Computing Science|
|Depositing User:||Mr Adam Field|
|Date Deposited:||27 May 2010 14:46|
|Last Modified:||23 Sep 2013 18:36|
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