Software Test Effort Estimation Using Particle Swarm Optimization

被引：0
|
作者：
Bhattacharya, Prasanta [1 ]
Srivastava, Praveen Ranjan [1 ]
Prasad, Bhanu [2 ]
机构：
[1] Birla Inst Technol & Sci, Dept Comp & Informat Syst, Pilani 333031, Rajasthan, India
[2] Florida A&M Univ, Dept Comp & Informat Sci, Tallahassee, FL 32307 USA
来源：
PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON INFORMATION SYSTEMS DESIGN AND INTELLIGENT APPLICATIONS 2012 (INDIA 2012) | 2012年 / 132卷
关键词：
Software testing; software testing effort (STE); particle swarm optimization (PSO); COCOMO; test effort drivers (TED);
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Software testing is a key component in the software development life cycle. This paper presents a modification to the Constructive Cost Model (COCOMO) technique by using particle swarm optimization. The resultant technique significantly increases the accuracy of the COCOMO approach and also incorporates the much needed flexibility related to the software and the development team.
引用
收藏
页码：827 / +
页数：3
相关论文
共 50 条
  • [1] Software Effort Estimation Using Particle Swarm Optimization: Advances and Challenges
    Reddy, Dukka Karun Kumar
    Behera, H. S.
    [J]. COMPUTATIONAL INTELLIGENCE IN PATTERN RECOGNITION, CIPR 2020, 2020, 1120 : 243 - 258
  • [2] Particle Swarm Optimization in Small Case Bases for Software Effort Estimation
    Landeis, Katharina
    Pews, Gerhard
    Minor, Mirjam
    [J]. CASE-BASED REASONING RESEARCH AND DEVELOPMENT, ICCBR 2022, 2022, 13405 : 209 - 223
  • [3] Test Effort Estimation-Particle Swarm Optimization Based Approach
    Aloka, S.
    Singh, Peenu
    Rakshit, Geetanjali
    Srivastava, Praveen Ranjan
    [J]. CONTEMPORARY COMPUTING, 2011, 168 : 463 - 474
  • [4] Software Effort Estimation Using Functional Link Neural Networks Optimized by Improved Particle Swarm Optimization
    Benala, Tirimula Rao
    Mall, Rajib
    Dehuri, Satchidananda
    [J]. SWARM, EVOLUTIONARY, AND MEMETIC COMPUTING, PT II (SEMCCO 2013), 2013, 8298 : 205 - 213
  • [5] Improving the Accuracy in Software Effort Estimation Using Artificial Neural Network Model Based on Particle Swarm Optimization
    Dan, Zhang
    [J]. 2013 IEEE INTERNATIONAL CONFERENCE ON SERVICE OPERATIONS AND LOGISTICS, AND INFORMATICS (SOLI), 2013, : 180 - 185
  • [6] Particle Swarm Optimization for Predicting the Development Effort of Software Projects
    Dayanara Alanis-Tamez, Mariana
    Lopez-Martin, Cuauhtemoc
    Villuendas-Rey, Yenny
    [J]. MATHEMATICS, 2020, 8 (10) : 1 - 21
  • [7] MUCPSO: A Modified Chaotic Particle Swarm Optimization with Uniform Initialization for Optimizing Software Effort Estimation
    Ardiansyah, Ardiansyah
    Ferdiana, Ridi
    Permanasari, Adhistya Erna
    [J]. APPLIED SCIENCES-BASEL, 2022, 12 (03):
  • [8] Particle Swarm Optimization Based Effort Estimation Using Function Point Analysis
    Kaur, Mandeep
    Sehra, Sumeet Kaur
    [J]. PROCEEDINGS OF THE 2014 INTERNATIONAL CONFERENCE ON ISSUES AND CHALLENGES IN INTELLIGENT COMPUTING TECHNIQUES (ICICT), 2014, : 140 - 145
  • [9] Software Effort Estimation Using Functional Link Neural Networks Tuned with Active Learning and Optimized with Particle Swarm Optimization
    Benala, Tirimula Rao
    Mall, Rajib
    Dehuri, Satchidananda
    Swetha, Pala
    [J]. SWARM, EVOLUTIONARY, AND MEMETIC COMPUTING, SEMCCO 2014, 2015, 8947 : 223 - 238
  • [10] Polynomial analogy-based software development effort estimation using combined particle swarm optimization and simulated annealing
    Shahpar, Zahra
    Bardsiri, Vahid Khatibi
    Bardsiri, Amid Khatibi
    [J]. CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE, 2021, 33 (20):
12345