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15,499
Survey on Software Defect Prediction
"... Software defect prediction is one of the most active research areas in software engineering. Defect prediction results provide the list of defect-prone source code artifacts so that quality assurance teams can effectively allocate limited resources for validating software products by putting more ef ..."
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Cited by 1 (0 self)
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Software defect prediction is one of the most active research areas in software engineering. Defect prediction results provide the list of defect-prone source code artifacts so that quality assurance teams can effectively allocate limited resources for validating software products by putting more
A Critique of Software Defect Prediction Models
- IEEE TRANSACTIONS ON SOFTWARE ENGINEERING
, 1999
"... Many organizations want to predict the number of defects (faults) in software systems, before they are deployed, to gauge the likely delivered quality and maintenance effort. To help in this numerous software metrics and statistical models have been developed, with a correspondingly large literatur ..."
Abstract
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Cited by 292 (21 self)
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Many organizations want to predict the number of defects (faults) in software systems, before they are deployed, to gauge the likely delivered quality and maintenance effort. To help in this numerous software metrics and statistical models have been developed, with a correspondingly large
Improved Software Defect Prediction
"... Although a number of approaches have been taken to quality prediction for software, none have achieved widespread applicability. This paper describes a single model to combine the diverse forms of, often causal, evidence available in software development in a more natural and efficient way than done ..."
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Cited by 4 (1 self)
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Philips internationally). The resulting model (packaged within a commercial software tool, AgenaRisk, usable by project managers) is now being used to predict defect rates at various testing and operational phases. The results of the validation confirm that the approach is scalable, robust and more
The Effect of Locality Based Learning on Software Defect Prediction
, 2010
"... Software defect prediction poses many problems during classification. A common solution used to improve software defect prediction is to train on similar, or local, data to the testing data. Prior work [12, 64] shows that locality improves the performance of classifiers. This approach has been commo ..."
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Cited by 1 (0 self)
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Software defect prediction poses many problems during classification. A common solution used to improve software defect prediction is to train on similar, or local, data to the testing data. Prior work [12, 64] shows that locality improves the performance of classifiers. This approach has been
Using Class Imbalance Learning for Software Defect Prediction
- IEEE TRANSACTIONS ON RELIABILITY
"... To facilitate software testing and save testing cost, a wide range of machine learning methods have been studied to predict defects in software modules. Unfortunately, the imbalanced nature of this type of data increases the learning difficulty of such a task. Class imbalance learning specializes in ..."
Abstract
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Cited by 8 (2 self)
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To facilitate software testing and save testing cost, a wide range of machine learning methods have been studied to predict defects in software modules. Unfortunately, the imbalanced nature of this type of data increases the learning difficulty of such a task. Class imbalance learning specializes
Software Defects Prediction using Operating Characteristic Curves
"... We present a software defect prediction model using operating characteristic curves. The main idea behind our proposed technique is to use geometric insight in helping construct an efficient and fast prediction method to accu-rately predict the cumulative number of failures at any given stage during ..."
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We present a software defect prediction model using operating characteristic curves. The main idea behind our proposed technique is to use geometric insight in helping construct an efficient and fast prediction method to accu-rately predict the cumulative number of failures at any given stage
Software Defect Prediction Tool based on Neural Network
"... There has been a tremendous growth in the demand for software fault prediction during recent years. In this paper, Levenberg-Marquardt (LM) algorithm based neural network tool is used for the prediction of software defects at an early stage of the software development life cycle. It helps to minimiz ..."
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There has been a tremendous growth in the demand for software fault prediction during recent years. In this paper, Levenberg-Marquardt (LM) algorithm based neural network tool is used for the prediction of software defects at an early stage of the software development life cycle. It helps
AN EXPLORATION OF CHALLENGES LIMITING PRAGMATIC SOFTWARE DEFECT PREDICTION
, 2012
"... Software systems continue to play an increasingly important role in our daily lives, making the quality of software systems an extremely important issue. Therefore, a significant amount of recent research focused on the prioritization of software quality assurance efforts. One line of work that has ..."
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been receiving an increasing amount of attention is Software Defect Prediction (SDP), where predictions are made to determine where future defects might appear. Our survey showed that in the past decade, more than 100 papers were published on SDP. Nevertheless, the adoption of SDP in practice to date
A Probabilistic Model for Software Defect Prediction
, 2001
"... Although a number of approaches have been taken to quality prediction for software, none have achieved widespread applicability. Our aim here is to produce a single model to combine the diverse forms of, often causal, evidence available in software development in a more natural and efficient way tha ..."
Abstract
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Cited by 18 (2 self)
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for Philips Software Centre (PSC), using expert knowledge from Philips Research Labs. The model is used especially to predict defect rates at various testing and operational phases. To make the model usable by software quality managers we have developed a tool (AID) and have used it to validate the model
SOFTWARE DEFECT PREDICTION: HEURISTICS FOR WEIGHTED NAÏVE BAYES
"... Abstract: Defect prediction is an important topic in software quality research. Statistical models for defect prediction can be built on project repositories. Project repositories store software metrics and defect information. This information is then matched with software modules. Naïve Bayes is a ..."
Abstract
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Cited by 3 (0 self)
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Abstract: Defect prediction is an important topic in software quality research. Statistical models for defect prediction can be built on project repositories. Project repositories store software metrics and defect information. This information is then matched with software modules. Naïve Bayes is a
Results 1 - 10
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15,499
