Name
Abstract | ||
|---|---|---|
Many risk factors affect software development and risk management has become one of the major activities in software development. Discovering causal directions among risk factors and project performance are important support for risk management. The Additive Noise Model (ANM) is an effective algorithm for discovering the direction on one-to-one causalities, but ineffective on many-to-one causalities which are frequent in software project risk analysis (SPRA) process. Thus we proposed a modified ANM with Conditional Probability Table (ANMCPT) to discover the causal direction among risk factors and project performance. The experimental results show our proposed algorithm is effective to discover the many-to-one causalities in SPRM on 498 collected software project data, and it performs better than other algorithms in the prediction with discovered causes of project performance, such as logistic regression, C4.5, Naïve Bayes, and general BNs. This study firstly presents an approach using ANM for many-to-one causality discovery in SPRA and then proves that it is an effective algorithm for analyzing the risk in software project. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1109/3PGCIC.2014.133 | 3PGCIC |
Keywords | Field | DocType |
logistic regression,conditional probability table,software development management,project risk management,anm algorithm,spra process,software project risk analysis,causal direction discovery,software development,risk factors,risk analysis,naive bayes algorithm,many-to-one causality discovery,project management,risk management,additive noise model,data mining,causality discovery,c4.5 algorithm,project risk management, causality discovery, additive noise model,anmcpt algorithm,probability,algorithm design and analysis | Project risk management,Data mining,Causality,Algorithm design,Naive Bayes classifier,Computer science,Risk management,Software,Artificial intelligence,Conditional probability table,Machine learning,Software development | Conference |
Citations | PageRank | References |
1 | 0.35 | 16 |
Authors | ||
7 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Weiqi Chen | 1 | 20 | 4.79 |
| Kang Liu | 2 | 1 | 0.69 |
| Lijun Su | 3 | 1 | 0.35 |
| Mei Liu | 4 | 334 | 19.84 |
| Zhifeng Hao | 5 | 653 | 78.36 |
| Yong Hu | 6 | 89 | 12.08 |
| Xiangzhou Zhang | 7 | 103 | 8.26 |