Software Defect Distribution Prediction for BOSS System

2014 ◽  
Vol 701-702 ◽  
pp. 67-70
Author(s):  
Wan Jiang Han ◽  
He Yang Jiang ◽  
Yi Sun ◽  
Tian Bo Lu
Keyword(s):  
Software Development ◽  
Model Experiment ◽  
Development Process ◽  
Distribution Model ◽  
Defect Prediction ◽  
Software Development Process ◽  
Software Defects ◽  
Defect Distribution ◽  
Software Defect ◽  
Important Activity

Effective detection of software defects is an important activity of software development process. In this paper, we propose an approach to predict residual defects for BOSS project, which applies defect distribution model. Experiment results show that this approach can effectively improve the accuracy of defect prediction.

Towards implementing defect prediction in the software development process

2019 ◽  
Vol 37 (6) ◽  
pp. 7223-7238 ◽  
Author(s):  
Marian Jureczko ◽  
Ngoc Trung Nguyen ◽  
Marcin Szymczyk ◽  
Olgierd Unold
Keyword(s):  
Software Development ◽  
Development Process ◽  
Defect Prediction ◽  
Software Development Process

scholarly journals Software Defect Fault Intelligent Location and Identification Method Based on Data Mining

2022 ◽  
Vol 2146 (1) ◽  
pp. 012012
Author(s):  
Fang Wang
Keyword(s):  
Data Mining ◽  
Computer Technology ◽  
Development Process ◽  
Software Defect Prediction ◽  
Software Development Process ◽  
Software Defects ◽  
Identification Methods ◽  
Software Defect ◽  
Error Location ◽  
The Times

Abstract With the advancement of the times, computer technology is also constantly improving, and people’s requirements for software functions are also constantly improving, and as software functions become more and more complex, developers are technically limited and teamwork is not tacitly coordinated. And so on, so in the software development process, some errors and problems will inevitably lead to software defects. The purpose of this paper is to study the intelligent location and identification methods of software defects based on data mining. This article first studies the domestic and foreign software defect fault intelligent location technology, analyzes the shortcomings of traditional software defect detection and fault detection, then introduces data mining technology in detail, and finally conducts in-depth research on software defect prediction technology. Through in-depth research on several technologies, it reduces the accidents of software equipment and delays its service life. According to the experiments in this article, the software defect location proposed in this article uses two methods to compare. The first error set is used as a unit to measure the subsequent error set software error location cost. The first error set 1F contains 19 A manually injected error program, and the average positioning cost obtained is 3.75%.

scholarly journals Are UX Evaluation Methods Providing the Same Big Picture?

Sensors ◽  
2021 ◽  
Vol 21 (10) ◽  
pp. 3480
Author(s):  
Walter Takashi Nakamura ◽  
Iftekhar Ahmed ◽  
David Redmiles ◽  
Edson Oliveira ◽  
David Fernandes ◽  
...  
Keyword(s):  
Software Development ◽  
Decision Process ◽  
Development Process ◽  
Evaluation Methods ◽  
Sentence Completion ◽  
Software Development Process ◽  
Software Application ◽  
Software Products ◽  
Big Picture ◽  
The Impact

The success of a software application is related to users’ willingness to keep using it. In this sense, evaluating User eXperience (UX) became an important part of the software development process. Researchers have been carrying out studies by employing various methods to evaluate the UX of software products. Some studies reported varied and even contradictory results when applying different UX evaluation methods, making it difficult for practitioners to identify which results to rely upon. However, these works did not evaluate the developers’ perspectives and their impacts on the decision process. Moreover, such studies focused on one-shot evaluations, which cannot assess whether the methods provide the same big picture of the experience (i.e., deteriorating, improving, or stable). This paper presents a longitudinal study in which 68 students evaluated the UX of an online judge system by employing AttrakDiff, UEQ, and Sentence Completion methods at three moments along a semester. This study reveals contrasting results between the methods, which affected developers’ decisions and interpretations. With this work, we intend to draw the HCI community’s attention to the contrast between different UX evaluation methods and the impact of their outcomes in the software development process.

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