scholarly journals Implementasi Manajemen Bandwidth dengan Metode Hierarchical Token Bucket (HTB) dan Per Connection Queue (PCQ) pada STMIK Antar Bangsa

2021 ◽  
Vol 7 (2) ◽  
pp. 69-73
Author(s):  
Subhiyanto
Keyword(s):  
Software Product Line ◽  
User Acceptance ◽  
Product Line ◽  
Test Cases ◽  
Acceptance Test ◽  
Mapping Study ◽  
Software Product ◽  
Token Bucket ◽  
Traffic Rate

Intisari—Penggunaan internet saat ini sangat dibutuhkan untuk kelancaran dan kemudahan sebuah pekerjaaan diperusahaan yang umumnya menggunakan internet secara bersamaan. Semakain bertambahnya pengguna internet semakin berkurangnya performa kemampuan internet. Cara yang dapat ditempuh untuk mengurangi penurunan performansi jaringan yaitu dengan melakukan manajemen Bandwidth. Manajemen Bandwidth sangat penting dalam pengaturan alokasi Bandwidth yang akan diberikan kepada user untuk menghindari perebutan alokasi Bandwidth yang ada di jaringan. Pada penelitian ini manajemen Bandwidth menggunakan dua metode, yaitu Per Connection Queue (PCQ) dan Hierarchical Token Bucket (HTB). PCQ pada queue type adalah salah satu fitur dari MikroTik untuk membantu memanage traffic rate dan traffic packet sedangkan Hiearachical Token Bucket (HTB) merupakan jenis aplikasi yang digunakan untuk membatasi akses menuju ke port/IP tertentu tanpa mengganggu trafik Bandwidth pengguna lain. Hasil yang didapatkan bahwa kualitas jaringan dengan menggunakan metode antrian HTB (Hierarchical Token Bucket) dan metode PCQ (Peer Connection Queue) lebih optimal, hal ini dikarenakan semua client akan mendapatkan kuota Bandwidth sesuai dengan rule yang diterapkan pada Bandwidth manajemen. Kata Kunci—QoS, HTB, PCQ, Mikrotik Referensi : [1] A. Hafiz Kamrullah, “Penerapan Metode Qquality Of Service pada jaringan Traffic yang padat,” J. Jar. Komput. Univ. Sriwij., 2009. [2] A. I. dkk Wijaya, “MANAJEMEN BANDWIDTH DENGAN METODE HTB ( HIERARCHICAL TOKEN BUCKET ) PADA SEKOLAH MENENGAH PERTAMA NEGERI 5 SEMARANG,” pp. 5–7, 2007. [3] Mirsantoso, T. U. Kalsum, and R. Supardi, “Implementasi Dan Analisa Per Connection Queue ( Pcq ) Sebagai,” J. Media Infotama, vol. 11, no. 2, pp. 139–148, 2015. [4] K. R. P. H. Leung and W. L. Yeung, “Generating User Acceptance Test Plans from Test Cases,” 31st Annu. Int. Comput. Softw. Appl.Conf.-Vol. 2-(COMPSAC 2007), no. Compsac, pp. 737–742, Jul.2007. [5] E. Engström and P. Runeson, “Software product line testing– Asystematic mapping study,” Inf. Softw. Technol., vol. 53, no. 1, pp.2–13, Jan. 2011. [6] At all Hardiman, “Analisis perbandingan QoS (Quality Of Service) Pada Manajemen Bandwidth Dengan Metode PCQ (Per Connection Queue) Dan HTB (Hierarchical Token Bucket),” semanTIK, vol. 4, no. 1, pp. 121–128, 2018. [7] P. D. Roger, S. Pressman, Rekayasa Perangkat Lunak (Pendekatan Praktisi). Yogyakarta: Andi, 2012.

Software Product Line Testing Based on Feature Model Mutation

2017 ◽  
Vol 27 (05) ◽  
pp. 817-839 ◽  
Author(s):  
Johnny Maikeo Ferreira ◽  
Silvia Regina Vergilio ◽  
Marcos Quinaia
Keyword(s):  
Software Product Line ◽  
Product Line ◽  
Experimental Results ◽  
Feature Model ◽  
Test Case ◽  
Test Cases ◽  
Mutation Operators ◽  
Software Product ◽  
Pairwise Testing ◽  
Feature Management

The Feature Model (FM) is a fundamental artifact of the Software Product Line (SPL) engineering, used to represent commonalities and variabilities, and also to derive products for testing. However, the test of all features combinations (products) is not always possible in practice. Due to the growing complexity of the applications, only a subset of products is usually selected. The selection is generally based on combinatorial testing, to test features interactions. This kind of selection does not consider different classes of faults that can be present in the FM. The application of a fault-based approach, such as mutation-based testing, can increase the probability of finding faults and the confidence that the SPL products match the requirements. Considering that, this paper introduces a mutation approach to select products for the feature testing of SPLs. The approach can be used similarly to a test criterion in the generation and assessment of test cases. It includes (i) a set of mutation operators, introduced to describe typical faults associated to the feature management and to the FM; and (ii) a testing process to apply the operators. Experimental results show the applicability of the approach. The selected test case sets are capable to reveal other kind of faults, not revealed in the pairwise testing.

scholarly journals SIMILARITY DISTANCE MEASURE AND PRIORITIZATION ALGORITHM FOR TEST CASE PRIORITIZATION IN SOFTWARE PRODUCT LINE TESTING

2018 ◽  
Author(s):  
Shahliza Abd Halim ◽  
Dayang Norhayati Abang Jawawi ◽  
Muhammad Sahak
Keyword(s):  
Fault Detection ◽  
Distance Measure ◽  
Software Product Line ◽  
Product Line ◽  
Test Case ◽  
Test Cases ◽  
Test Case Prioritization ◽  
Software Product ◽  
String Distance ◽  
Similarity Distance

To achieve the goal of creating products for a specific market segment, implementation of Software Product Line (SPL) is required to fulfill specific needs of customers by managing a set of common features and exploiting the variabilities between the products. Testing product-by-product is not feasible in SPL due to the combinatorial explosion of product number, thus, Test Case Prioritization (TCP) is needed to select a few test cases which could yield high number of faults. Among the most promising TCP techniques is similarity-based TCP technique which consists of similarity distance measure and prioritization algorithm. The goal of this paper is to propose an enhanced string distance and prioritization algorithm which could reorder the test cases resulting to higher rate of fault detection. Comparative study has been done between different string distance measures and prioritization algorithms to select the best techniques for similarity-based test case prioritization. Identified enhancements have been implemented to both techniques for a better adoption of prioritizing SPL test cases. Experiment has been done in order to identify the effectiveness of enhancements done for combination of both techniques. Result shows the effectiveness of the combination where it achieved highest average fault detection rate, attained fastest execution time for highest number of test cases and accomplished 41.25% average rate of fault detection. The result proves that the combination of both techniques improve SPL testing effectiveness compared to other existing techniques.  

RISK MANAGEMENT IN SOFTWARE PRODUCT LINE ENGINEERING: A MAPPING STUDY

2013 ◽  
Vol 23 (04) ◽  
pp. 523-558 ◽  
Author(s):  
LUANNA LOPES LOBATO ◽  
THIAGO JABUR BITTAR ◽  
PAULO ANSELMO DA MOTA SILVEIRA NETO ◽  
IVAN DO CARMO MACHADO ◽  
EDUARDO SANTANA DE ALMEIDA ◽  
...  
Keyword(s):  
Risk Management ◽  
Software Reuse ◽  
Management Practices ◽  
Negative Impact ◽  
Software Product Line ◽  
Product Line ◽  
Mitigation Strategies ◽  
Mapping Study ◽  
Software Product ◽  
Managing Risk

Software Product Line (SPL) Engineering focuses on systematic software reuse, which has benefits such as reductions in time-to-market and effort, and improvements in the quality of products. However, establishing a SPL is not a simple matter, and can affect all aspects of the organization, since the approach is complex and involves major investment and considerable risk. These risks can have a negative impact on the expected ROI for an organization, if SPL is not sufficiently managed. This paper presents a mapping study of Risk Management (RM) in SPL Engineering. We analyzed a set of thirty studies in the field. The results points out the need for risk management practices in SPL, due to the little research on RM practices in SPL and the importance of identifying insight on RM in SPL. Most studies simply mention the importance of RM, however the steps for managing risk are not clearly specified. Our findings suggest that greater attention should be given, through the use of industrial case studies and experiments, to improve SPL productivity and ensure its success. This research is a first attempt within the SPL community to identify, classify, and manage risks, and establish mitigation strategies.

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