Journal of Computer Applications ›› 2023, Vol. 43 ›› Issue (11): 3568-3573.DOI: 10.11772/j.issn.1001-9081.2022101600
• Computer software technology • Previous Articles Next Articles
Jiahao ZHU1,2(), Wei ZHENG1,2, Fengyu YANG1,2, Xin FAN1,2, Peng XIAO1,2
Received:
2022-10-25
Revised:
2022-12-17
Accepted:
2022-12-26
Online:
2023-11-14
Published:
2023-11-10
Contact:
Jiahao ZHU
About author:
ZHU Jiahao, born in 1998, M.S. candidate. His research interests include software reliability, software quality prediction.Supported by:
朱嘉豪1,2(), 郑巍1,2, 杨丰玉1,2, 樊鑫1,2, 肖鹏1,2
通讯作者:
朱嘉豪
作者简介:
朱嘉豪(1998—),男,江西丰城人,硕士研究生,CCF会员,主要研究方向:软件可靠性、软件质量预测 zhujiahao_nchu@126.com基金资助:
CLC Number:
Jiahao ZHU, Wei ZHENG, Fengyu YANG, Xin FAN, Peng XIAO. Software quality prediction based on back propagation neural network optimized by ant colony optimization algorithm[J]. Journal of Computer Applications, 2023, 43(11): 3568-3573.
朱嘉豪, 郑巍, 杨丰玉, 樊鑫, 肖鹏. 基于蚁群算法优化反向传播神经网络的软件质量预测[J]. 《计算机应用》唯一官方网站, 2023, 43(11): 3568-3573.
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URL: https://www.joca.cn/EN/10.11772/j.issn.1001-9081.2022101600
指标序列 | 指标名称 | 指标序列 | 指标名称 |
---|---|---|---|
Index1 | 模块数 | Index7 | 代码审查问题数 |
Index2 | 行数>200模块数 | Index8 | 静态分析问题数 |
Index3 | 圈复杂度>10模块数 | Index9 | 动态测试问题数 |
Index4 | 扇出>7模块数 | Index10 | 首轮动态测试用例通过率 |
Index5 | 有效代码率 | Index11 | 回归测试次数 |
Index6 | 文档审查问题数 | Index12 | 回归测试问题总数 |
Tab. 1 Indexes of software quality
指标序列 | 指标名称 | 指标序列 | 指标名称 |
---|---|---|---|
Index1 | 模块数 | Index7 | 代码审查问题数 |
Index2 | 行数>200模块数 | Index8 | 静态分析问题数 |
Index3 | 圈复杂度>10模块数 | Index9 | 动态测试问题数 |
Index4 | 扇出>7模块数 | Index10 | 首轮动态测试用例通过率 |
Index5 | 有效代码率 | Index11 | 回归测试次数 |
Index6 | 文档审查问题数 | Index12 | 回归测试问题总数 |
参数名 | 编码 |
---|---|
结构参数 | ST |
第一隐含层神经元连接权值 | h1w1,h1w2,…,h1w192 |
第一隐含层神经元阈值 | h1b1,h1b2,…,h1b16 |
第二隐含层神经元连接权值 | h2w1,h2w2,…,h2w512 |
第二隐含层神经元阈值 | h2b1,h2b2,…,h2b32 |
第三隐含层神经元连接权值 | h3w1,h3w2,…,h2w512 |
第三隐含层神经元阈值 | h3b1,h3b2,…,h3b16 |
输出层神经元连接权值 | ow1,ow2,…,ow64 |
输出层神经元阈值 | ob1, ob2,…, ob4 |
Tab. 2 Structure parameters of BP neural network
参数名 | 编码 |
---|---|
结构参数 | ST |
第一隐含层神经元连接权值 | h1w1,h1w2,…,h1w192 |
第一隐含层神经元阈值 | h1b1,h1b2,…,h1b16 |
第二隐含层神经元连接权值 | h2w1,h2w2,…,h2w512 |
第二隐含层神经元阈值 | h2b1,h2b2,…,h2b32 |
第三隐含层神经元连接权值 | h3w1,h3w2,…,h2w512 |
第三隐含层神经元阈值 | h3b1,h3b2,…,h3b16 |
输出层神经元连接权值 | ow1,ow2,…,ow64 |
输出层神经元阈值 | ob1, ob2,…, ob4 |
蚂蚁数量 | 最优路径长度 | 迭代次数 |
---|---|---|
10 | 1.67 | 39 |
30 | 1.54 | 43 |
50 | 1.29 | 47 |
70 | 1.34 | 53 |
90 | 1.32 | 64 |
Tab. 3 Influence of ant numbers on ACO
蚂蚁数量 | 最优路径长度 | 迭代次数 |
---|---|---|
10 | 1.67 | 39 |
30 | 1.54 | 43 |
50 | 1.29 | 47 |
70 | 1.34 | 53 |
90 | 1.32 | 64 |
信息素挥发因子 | 最优路径长度 | 迭代次数 |
---|---|---|
0.3 | 1.63 | 31 |
0.5 | 1.31 | 46 |
0.7 | 1.35 | 54 |
0.9 | 1.41 | 73 |
Tab. 4 Influence of pheromone evaporation factors on ACO
信息素挥发因子 | 最优路径长度 | 迭代次数 |
---|---|---|
0.3 | 1.63 | 31 |
0.5 | 1.31 | 46 |
0.7 | 1.35 | 54 |
0.9 | 1.41 | 73 |
信息启发式因子 | 期望启发式因子 | 最优路径长度 | 迭代次数 |
---|---|---|---|
0.1 | 0.1 | 1.72 | 121 |
0.1 | 0.5 | 1.64 | 73 |
0.5 | 1.0 | 1.62 | 61 |
1.0 | 2.0 | 1.33 | 40 |
1.5 | 3.0 | 1.36 | 43 |
1.5 | 5.0 | 1.39 | 51 |
Tab. 5 Influence of heuristic factors on ACO
信息启发式因子 | 期望启发式因子 | 最优路径长度 | 迭代次数 |
---|---|---|---|
0.1 | 0.1 | 1.72 | 121 |
0.1 | 0.5 | 1.64 | 73 |
0.5 | 1.0 | 1.62 | 61 |
1.0 | 2.0 | 1.33 | 40 |
1.5 | 3.0 | 1.36 | 43 |
1.5 | 5.0 | 1.39 | 51 |
模型编号 | 网络层数 | 网络结构 | CE | F |
---|---|---|---|---|
1 | 4 | (12,15,10,4) | 1.218 | 2.01 |
2 | 5 | (12,10,16,12,4) | 1.766 | 1.94 |
3 | 4 | (12,15,12,4) | 1.377 | 1.91 |
4 | 5 | (12,12,12,10,4) | 1.322 | 1.88 |
5 | 5 | (12,10,18,8,4) | 1.832 | 1.86 |
6 | 3 | (12,16,4) | 1.331 | 1.84 |
7 | 4 | (12,10,10,4) | 1.368 | 1.82 |
8 | 3 | (12,15,4) | 1.325 | 1.81 |
9 | 4 | (12,10,8,4) | 1.384 | 1.78 |
10 | 3 | (12,14,4) | 1.329 | 1.77 |
Tab. 6 Structure results of network models
模型编号 | 网络层数 | 网络结构 | CE | F |
---|---|---|---|---|
1 | 4 | (12,15,10,4) | 1.218 | 2.01 |
2 | 5 | (12,10,16,12,4) | 1.766 | 1.94 |
3 | 4 | (12,15,12,4) | 1.377 | 1.91 |
4 | 5 | (12,12,12,10,4) | 1.322 | 1.88 |
5 | 5 | (12,10,18,8,4) | 1.832 | 1.86 |
6 | 3 | (12,16,4) | 1.331 | 1.84 |
7 | 4 | (12,10,10,4) | 1.368 | 1.82 |
8 | 3 | (12,15,4) | 1.325 | 1.81 |
9 | 4 | (12,10,8,4) | 1.384 | 1.78 |
10 | 3 | (12,14,4) | 1.329 | 1.77 |
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