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Embedding Quality into Software Product Line Variability Artifacts

Mworia Daniel, Nderu Lawrence, Kimwele Michael
2021 International Journal of Software Engineering & Applications  
This work presents an integrated requirement specification template for quality and functional requirements at software product line variation points.  ...  The success of any software product line development project is closely tied to its domain variability management.  ...  [9] observe that feature modeling is the core of software product line engineering and a de facto standard in modeling variability in SPL.  ... 
doi:10.5121/ijsea.2021.12302 fatcat:iufz6hnsyrestejhf563wwofmy

Learning to Support Derivation of Adaptable Products in Software Product Lines

Anissa Benlarabi, Amal Khtira, Bouchra El Asri
2020 Journal of Computer and Communications  
Software product line engineering is a large scale development paradigm based on mass production. It consists in building a common platform from which a set of products can be derived.  ...  Under the constraints of continuous evolution and costs optimization, the derivation process must be able to answer customers' requirements and provide adequate products in a short time without defects  ...  Conflicts of Interest The authors declare no conflicts of interest regarding the publication of this paper.  ... 
doi:10.4236/jcc.2020.84009 fatcat:clmqqfao7jdl7cq3flcahuw6uq

Classification of Meteorological Satellite Ground System Applications

Manyun Lin, Xiangang Zhao, Xieli Zi, Peng Guo, Cunqun Fan
2017 Atmospheric and Climate Sciences  
Meteorological satellite ground application system carries a large number of applications. These applications deal with a variety of tasks.  ...  Firstly, the requirements are abstractly described, and then analyzed by hierarchical clustering algorithm. Finally, the benchmark analysis of resource consumption is given.  ...  [1] [2] give a classification and survey of analysis strategies for software product lines. A software product line is a family of software products that share a common set of features.  ... 
doi:10.4236/acs.2017.73028 fatcat:b66yfoj3vzecfd6j6d4jhfytly

Predictive Analytics for Product Configurations in Software Product Lines

Uzma Afzal, Tariq Mahmood, Raihan ur Rasool, Ayaz H. Khan, Rehan Ullah Khan, Ali Mustafa Qamar
2021 International Journal of Computational Intelligence Systems  
A B S T R A C T A Software Product Line (SPL) is a collection of software for configuring software products in which sets of features are configured by different teams of product developers.  ...  configurations of feature selections (patterns) that lead to inconsistent product configurations, 2) by identifying feature selection patterns that lead to consistent product configurations, and 3) by  ...  INTRODUCTION Software Product Lines (SPLs) [1] [2] [3] are used to configure software products in which different sets of features are configured and then integrated by different teams of product developers  ... 
doi:10.2991/ijcis.d.210620.003 fatcat:lauvc3qn7jc6rcft2jqfojo7pi

A systematic analysis of textual variability modeling languages

Holger Eichelberger, Klaus Schmid
2013 Proceedings of the 17th International Software Product Line Conference on - SPLC '13  
Industrial variability models tend to grow in size and complexity due to ever-increasing functionality and complexity of software systems.  ...  However, traditional variability modeling approaches do not seem to scale adequately to cope with size and complexity of such models.  ...  SXFM is used in the feature model repository Software Product Lines Online Tools (S.P.L.O.T) [30, 31] .  ... 
doi:10.1145/2491627.2491652 dblp:conf/splc/EichelbergerS13 fatcat:25ec6xtqvzd6pnwlnifon56jv4

Striving for Failure: An Industrial Case Study about Test Failure Prediction

Jeff Anderson, Saeed Salem, Hyunsook Do
2015 2015 IEEE/ACM 37th IEEE International Conference on Software Engineering  
Software regression testing is an important, yet very costly, part of most major software projects.  ...  When regression tests run, any failures that are found help catch bugs early and smooth the future development work.  ...  Institute of General Medical Sciences (P20 GM103442) part of the National Institutes of Health.  ... 
doi:10.1109/icse.2015.134 dblp:conf/icse/AndersonSD15 fatcat:cdl6i5cs4zakrkpa2j4dve3xri

A Multi-source Machine Learning Approach to Predict Defect Prone Components

Pasquale Ardimento, Mario Luca Bernardi, Marta Cimitile
2018 Proceedings of the 13th International Conference on Software Technologies  
In the last years several approaches to evaluating the defect proneness of software components are proposed: these approaches exploit products metrics (like the Chidamber and Kemerer metrics suite) or  ...  With respect to the existing approaches, the proposed classifier allows predicting the defect proneness basing on the evolution of these features across the project development.  ...  In this paper, we propose a features model that takes into consideration the software component's history to consider the evolution of a mix of products and process metrics.  ... 
doi:10.5220/0006857803060313 dblp:conf/icsoft/ArdimentoBC18 fatcat:elyfpfcrdveh5pyg3mc76bmi3a

Линь М., Чжао С., Цзы С., Го П., Фань Ц. Классификация программного обеспечения по обработке данных метеорологических спутников

2018 Исследования космоса  
Meteorological satellite ground application system carries a large number of applications. These applications deal with a variety of tasks.  ...  Firstly, the requirements are abstractly described, and then analyzed by hierarchical clustering algorithm. Finally, the benchmark analysis of resource consumption is given.  ...  Статья впервые опубликована: Atmospheric and Climate Sciences. 2017. Vol. 07. No. 3.  ... 
doi:10.7256/2453-8817.2018.1.26055 fatcat:4ldjnmchr5ejlmq5adxc263xqe

Bridging software languages and ontology technologies

Fernando Silva Parreiras, Tobias Walter, Christian Wende, Edward Thomas
2010 Proceedings of the ACM international conference companion on Object oriented programming systems languages and applications companion - SPLASH '10  
Current model-driven development approaches allow for a more productive way of developing software systems.  ...  An interest to strengthen semantics in modeling and metamodeling that gained scientific and commercial attention is the integration of ontology technology and software development.  ...  Ontology-Based Analysis in Variability Modelling In software product lines [13] , feature models are used to capture common and variable features in a family of related software products.  ... 
doi:10.1145/1869542.1869626 dblp:conf/oopsla/ParreirasWWT10 fatcat:kwrui2vz35fy7fu7v2w6pjreea

Manifoldness of Variability Modeling — Considering the Potential for Further Integration [chapter]

Mark-Oliver Reiser, Ramin Tavakoli Kolagari, Matthias Weber
2008 Lecture Notes in Computer Science  
In the paper, various techniques for variability modeling are elaborated and a basic classification scheme is proposed.  ...  In response to this growing practical interest, the scientific community has come up with numerous concepts and techniques for modeling variability.  ...  Based on this, we discussed the potential of integrating them into a single, common technique for variability modeling.  ... 
doi:10.1007/978-3-540-85279-7_23 fatcat:ragxwjubwzeq7i5cqikt4npkw4

Software Effort Classification with Multilayer Perceptron Neural Networks

Ahmed Fawzi Otoom
2020 International Journal of Advanced Trends in Computer Science and Engineering  
We target the problem of software effort estimation from a classification perspective.  ...  In addition, we identify the important features for building the classification models across various data sets. Generally, MLP shows good performance across the six data sets.  ...  the classification model, with the sum of values across all the features is equal to (1.0).  ... 
doi:10.30534/ijatcse/2020/119922020 fatcat:l7z57wds5jaz7ber6ktok2n4ye

A Study on Software Metrics based Software Defect Prediction using Data Mining and Machine Learning Techniques

Manjula.C.M. Prasad, Lilly Florence Florence, Arti Arya3
2015 International Journal of Database Theory and Application  
Software quality is a field of study and practice that describes the desirable attributes of software products.  ...  model helps in early detection of defects and contributes to their efficient removal and producing a quality software system based on several metrics.  ...  This system will analyze the software defect and its integration with software module.  ... 
doi:10.14257/ijdta.2015.8.3.15 fatcat:pk5okarex5g55df2e5uxorhp54

Feature Interaction and Dependencies: Modeling Features for Reengineering a Legacy Product Line [chapter]

Stefan Ferber, Jürgen Haag, Juha Savolainen
2002 Lecture Notes in Computer Science  
We show two examples of feature dependencies and interactions in the context of an engine-control software product line, and we demonstrate how our approach helps to define correct product configurations  ...  Reorganizing the product line assets with respect to new requirements requires more knowledge than what is easily provided by the classical feature-modeling approaches.  ...  Acknowledgments We would like to thank the engine-control domain experts Klaus Hirschmann, Magnus Labbé, and Elmar Pietsch for their patient support of our feature analysis.  ... 
doi:10.1007/3-540-45652-x_15 fatcat:tsd6np3cbvbudf4ooqhwliglq4

Analysis of Features using Feature Model in Software Product Line: A Case Study

Hitesh Yadav, A. Charan Kumari
2018 International Journal of Education and Management Engineering  
Reusability measures the level of frequency of usage of the feature in developing a new software product line and consistency ensures that the core features are consistent in a software product line.  ...  This paper shows an analysis of features of email system using feature model in a Software Product Line (SPL). The core features that can be used by different SPLs are identified using feature model.  ...  This model tells that which features can be used with other to form a product and which ones cannot. So, feature model is used to combine features for software product line.  ... 
doi:10.5815/ijeme.2018.02.06 fatcat:k5je3iia45e6vbmzd24tiu2acq

An Ensemble DeepBoost Classifier for Software Defect Prediction

Sri Kavya K
2020 International Journal of Advanced Trends in Computer Science and Engineering  
The experiment was carried out on 7 PROMISE repository datasets and the results of EDC were compared with similar algorithms.  ...  In this paper an Ensemble DeepBoost Classifier (EDC) is built to predict the software defects effectively by addressing two major issues -curse of dimensionality and class distribution imbalance problem  ...  The number of iterations and the maximum depth of a single decision tree in the model are set to 10 and 6 respectively.  ... 
doi:10.30534/ijatcse/2020/173922020 fatcat:56245ae6mjfydfg7ugjh3bjcpi
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