Binary Oriented Feature Selection for Valid Product Derivation in Software Product Line  

作　　者：Muhammad Fezan Afzal Imran Khan Javed Rashid Mubbashar Saddique Heba G.Mohamed 

机构地区：[1]Department of CS&SE,International Islamic University,Islamabad,44000,Pakistan [2]Information Technology Services,University of Okara,Okara,56300,Pakistan [3]Departmet of Computer Science,MLC Lab,Okara,56300,Pakistan [4]Department of Computer Science&Engineering,University of Engineering&Technology Lahore,Narowal Campus,Narowal,51601,Pakistan [5]Department of Electrical Engineering,College of Engineering,Princess Nourah bint Abdulrahman University,P.O.Box 84428,Riyadh,11671,Saudi Arabia

出　　处：《Computers, Materials & Continua》2023年第9期3653-3670,共18页计算机、材料和连续体（英文）

基　　金：Princess Nourah bint Abdulrahman University Researchers Supporting Project Number(PNURSP2023TR140);Princess Nourah bint Abdulrahman University,Riyadh,Saudi Arabia.

摘　　要：Software Product Line(SPL)is a group of software-intensive systems that share common and variable resources for developing a particular system.The feature model is a tree-type structure used to manage SPL’s common and variable features with their different relations and problem of Crosstree Constraints(CTC).CTC problems exist in groups of common and variable features among the sub-tree of feature models more diverse in Internet of Things(IoT)devices because different Internet devices and protocols are communicated.Therefore,managing the CTC problem to achieve valid product configuration in IoT-based SPL is more complex,time-consuming,and hard.However,the CTC problem needs to be considered in previously proposed approaches such as Commonality VariabilityModeling of Features(COVAMOF)andGenarch+tool;therefore,invalid products are generated.This research has proposed a novel approach Binary Oriented Feature Selection Crosstree Constraints(BOFS-CTC),to find all possible valid products by selecting the features according to cardinality constraints and cross-tree constraint problems in the featuremodel of SPL.BOFS-CTC removes the invalid products at the early stage of feature selection for the product configuration.Furthermore,this research developed the BOFS-CTC algorithm and applied it to,IoT-based feature models.The findings of this research are that no relationship constraints and CTC violations occur and drive the valid feature product configurations for the application development by removing the invalid product configurations.The accuracy of BOFS-CTC is measured by the integration sampling technique,where different valid product configurations are compared with the product configurations derived by BOFS-CTC and found 100%correct.Using BOFS-CTC eliminates the testing cost and development effort of invalid SPL products.

关 键 词：Software product line feature model internet of things crosstree constraints variability management 

分 类 号：TP3[自动化与计算机技术—计算机科学与技术]