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Selecting the Appropriate Machine Learning Techniques for the Prediction of Software Development Costs [chapter]

Stamatia Bibi, Ioannis Stamelos
IFIP International Federation for Information Processing  
This paper suggests several estimation guidelines for the choice of a suitable machine learning technique for software development effort estimation.  ...  Finally the study proposes guidelines for choosing the appropriate technique, based on the size of the training data and the desirable features of the extracted estimation model.  ...  The paper is structured as follows: Section 2 shows how machine learning techniques are applied for estimating software development cost.  ... 
doi:10.1007/0-387-34224-9_62 dblp:conf/ifip12/BibiS06 fatcat:huhdg2gxcvherdojsxax6fadga

Progress on Machine Learning Techniques for Software Fault Prediction

Jyoti Goyal, Bal Kishan
2019 International Journal of Advanced Trends in Computer Science and Engineering  
Software fault prediction is a significant part of software engineering. Fault prediction means to identify fault prone modules at the early stage of software development.  ...  This paper also discusses the substantial research performed in software fault prediction using machine learning techniques.  ...  machine learning techniques used by researchers for prediction of faults.  ... 
doi:10.30534/ijatcse/2019/33822019 fatcat:akql63chkzgzhm5azngmceh45i

Automated Software Design Reusability using a Unique Machine Learning Technique

2020 VOLUME-8 ISSUE-10, AUGUST 2019, REGULAR ISSUE  
The era of machine learning (ML) has brought significant advancement into the traditional approaches of software development and services.  ...  The study introduces a novel approach of ML, which can assist inappropriate selection of reusable software components, which in the long run, can optimize the operational cost in the context of development  ...  Automated Software Design Reusability using a Unique Machine Learning Technique P.  ... 
doi:10.35940/ijitee.e3010.039520 fatcat:aqjibljxijhcbffbx5ijzh75me

Software Defect Prediction Using Artificial Neural Networks: A Systematic Literature Review

Muhammad Adnan Khan, Nouh Sabri Elmitwally, Sagheer Abbas, Shabib Aftab, Munir Ahmad, Muhammad Fayaz, Faheem Khan, Shah Nazir
2022 Scientific Programming  
Artificial Neural Network (ANN) is considered as one of the widely used machine learning techniques, which is included in most of the proposed defect prediction frameworks and models.  ...  In the last decade, many machine learning-based approaches for software defect prediction have been proposed to achieve the higher accuracy.  ...  ANN is one of the widely used machine learning techniques for software defect prediction. e nonlinear nature of ANN is capable to effectively extract the hidden patterns in the historical defect data set  ... 
doi:10.1155/2022/2117339 fatcat:nd3vrkpr6fbs5gndnvh5rfbl7i

A Study On Software Engineering Defect Prediction

2022 Data Analytics and Artificial Intelligence  
M any data mining techniques and dataset repository are available to predict the software defects. Bug prediction technique is an important part in software engineering area for last one decade.  ...  Software defects not only reduce the software quality, increase costing but it also suspends the development schedule. Software bugs lead to inaccurate and discrepant results.  ...  Object ives of The Study to select statistical learning and data mining techniques to be applied on historical software data for prediction of software defect.  ... 
doi:10.46632/daai/2/1/1 fatcat:25anbqvp3vg4fjeutyfccly5ya

Software Defect Prediction Using Supervised Machine Learning Techniques: A Systematic Literature Review

Faseeha Matloob, Shabib Aftab, Munir Ahmad, Muhammad Adnan Khan, Areej Fatima, Muhammad Iqbal, Wesam Mohsen Alruwaili, Nouh Sabri Elmitwally
2021 Intelligent Automation and Soft Computing  
SDP can minimize the cost of the testing stage, which can ultimately lead to the development of higher-quality software at a lower cost.  ...  Software defect prediction (SDP) is the process of detecting defectprone software modules before the testing stage.  ...  Funding Statement: The authors received no specific funding for this study. Conflicts of Interest: The authors declare that they have no conflicts of interest to report regarding the present study.  ... 
doi:10.32604/iasc.2021.017562 fatcat:yfai7zo3kzfylltedrleh7sc7i

Performance Evaluation of Machine Learning Techniques using Software Cost Drivers

Manas Gaur
2014 International Journal of Computer Applications  
Using Machine Learning Techniques (MLTs), the research tries to predict the cost, based on the cost drivers. The performance of MLTs was analyzed using root means square error and squared error.  ...  Application of artificial intelligence in software project planning has given a new methodology for Software Cost Estimation (SCE) that has improved, prediction accuracy.  ...  Estimation using machine learning technique focuses on prediction based on rules generated from the training data, back propagation neural network with updates the weights which signifies the importance  ... 
doi:10.5120/15714-4525 fatcat:fdwsgebnsjge3ex4lz7c34jc74

RESEARCH TRENDS IN SOFTWARE ENGINEERING FIELD: A LITERATURE REVIEW

Hiba Al Sghaier
2020 International Journal of Engineering Technologies and Management Research  
The new trends in software engineering are numerous, Cloud Computing, machine learning, deep learning, big Data, mobile Computing.  ...  Software engineering is one of computer science branches, it comprises of building and developing software systems and applications.  ...  Software maintenance operations may cost 60-77% of the overall cost of software system development [13] .  ... 
doi:10.29121/ijetmr.v7.i6.2020.694 fatcat:blgkpwyb3zfxtckv4nn3733nei

Benchmarking Machine Learning Techniques for Software Defect Detection

Saiqa Aleem, Luiz Fernando Capretz, Faheem Ahmed
2015 International Journal of Software Engineering & Applications  
This study used public available data sets of software modules and provides comparative performance analysis of different machine learning techniques for software bug prediction.  ...  Machine learning techniques are proven to be useful in terms of software bug prediction.  ...  ACKNOWLEDGEMENT The authors would like to thank Dr. Jagath Samarabandu for his constructive comments which contributed to the improvement of this article as his course work.  ... 
doi:10.5121/ijsea.2015.6302 fatcat:72kebliurzfehpq775pgjotuye

Feature Subset Selection for Software Cost Modelling and Estimation [article]

Efi Papatheocharous, Harris Papadopoulos, Andreas S. Andreou
2012 arXiv   pre-print
Feature selection has been recently used in the area of software engineering for improving the accuracy and robustness of software cost models.  ...  Finding suitable subset selections that may cater improved predictions may be considered as a pre-processing step of a particular technique employed for cost estimation (filter or wrapper) or an internal  ...  Embedded methods are included as part of a specific machine learning technique and through training they provide subset selection for the specific technique.  ... 
arXiv:1210.1161v1 fatcat:rmhqmk6dfjanhpxqnq4xomoj54

Benchmarking Machine Learning Technologies for Software Defect Detection [article]

Saiqa Aleem, Luiz Fernando Capretz, Faheem Ahmed
2015 arXiv   pre-print
This study used public available data sets of software modules and provides comparative performance analysis of different machine learning techniques for software bug prediction.  ...  Machine learning techniques are proven to be useful in terms of software bug prediction.  ...  ACKNOWLEDGEMENT The authors would like to thank Dr. Jagath Samarabandu for his constructive comments which contributed to the improvement of this article as his course work.  ... 
arXiv:1506.07563v1 fatcat:biorf4fr6fgqrboqe52clucibi

"Analyzing the Effect with Integrated Technique for Feature Selection and Software Defect Prediction"

2019 International journal of recent technology and engineering  
applied math techniques like supply regression [2] and discriminant analysis [3] and techniques of machine learning like svm [4] and ann [5].  ...  software defect prediction (sdp) technique was projected to designate testing assets sanely, decide the testing want of assorted modules of the software system, and improve programming quality.  ...  [12] This study proposed application of feature selection techniques for resolving the problem of curse of dimensionality in predicting software defects.  ... 
doi:10.35940/ijrte.b1625.078219 fatcat:uk4zb3iqsre5toghx3iim3bkla

Survey on Bug Triage with Software Data Reduction Techniques

2015 International Journal of Science and Research (IJSR)  
Many software companies spend their most of cost in dealing with these bugs.  ...  As per literature, need to develop a effective model for doing data reduction on bug data set which will reduce the scale of the data as well as increase the quality of the data., by reducing the time  ...  When a new report arrives, the classifier produced by the supervised machine learning technique offered a small number of developers suitable to resolve the report. C. C. Aggarwal and P.  ... 
doi:10.21275/v4i12.nov152065 fatcat:xf447a5mdfbnff6mz4xi4j5a2a

PERFORMANCEOF HETEROGENEOUS ENSEMBLE APPROACH WITH TRADITIONAL METHODS BASED ON SOFTWARE DEFECT DETECTION MODEL

PVSS GANGADHAR
2022 figshare.com  
Identifying defective modules from the developed software is very much indispensable for constructive management and control of software testing.  ...  In this context several software defect detection modelling has been proposed by using machine learning algorithm.  ...  Researchers have used a combination of statistical and machine learning techniques to predict fault proneness models and reduce software development and maintenance costs in these strategies.  ... 
doi:10.6084/m9.figshare.19289057.v1 fatcat:nb7bqduxgffjhklwn4bcwlc7zq

Implementing Decision Tree for Software Development Effort Estimation of Software Project
english

Sonam Bhatia, Varinder Kaur Attri
2015 International Journal of Innovative Research in Computer and Communication Engineering  
For the forecasting of software effort, it is important to select the correct software effort estimation techniques.  ...  This paper presents M5P decision tree Technique, for effort evaluation in the field of software development. 4024 fit a linear regression to the observations at each leaf rather of allowing a single value  ...  ACKNOWLEDGEMENT We would like to thank acknowledge almighty for his constant blessings. Then we like to thank our family and friends for helping and supporting us throughout the making of this paper  ... 
doi:10.15680/ijircce.2015.0305041 fatcat:npsmvvnxinhsdd6al2jnt53eq4
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