2nd International Symposium on Search Based Software Engineering最新文献

Genetic Programming for Effort Estimation: An Analysis of the Impact of Different Fitness Functions 遗传规划的努力估计:不同适应度函数的影响分析

2nd International Symposium on Search Based Software Engineering Pub Date : 2010-09-07 DOI: 10.1109/SSBSE.2010.20

F. Ferrucci, C. Gravino, R. Oliveto, Federica Sarro

{"title":"Genetic Programming for Effort Estimation: An Analysis of the Impact of Different Fitness Functions","authors":"F. Ferrucci, C. Gravino, R. Oliveto, Federica Sarro","doi":"10.1109/SSBSE.2010.20","DOIUrl":"https://doi.org/10.1109/SSBSE.2010.20","url":null,"abstract":"Context: The use of search-based methods has been recently proposed for software development effort estimation and some case studies have been carried out to assess the effectiveness of Genetic Programming (GP). The results reported in the literature showed that GP can provide an estimation accuracy comparable or slightly better than some widely used techniques and encouraged further research to investigate whether varying the fitness function the estimation accuracy can be improved. Aim: Starting from these considerations, in this paper we report on a case study aiming to analyse the role played by some fitness functions for the accuracy of the estimates. Method: We performed a case study based on a publicly available dataset, i.e., Desharnais, by applying a 3-fold cross validation and employing summary measures and statistical tests for the analysis of the results. Moreover, we compared the accuracy of the obtained estimates with those achieved using some widely used estimation methods, namely Case-Based Reasoning (CBR) and Manual Step Wise Regression (MSWR). Results: The obtained results highlight that the fitness function choice significantly affected the estimation accuracy. The results also revealed that GP provided significantly better estimates than CBR and comparable with those of MSWR for the considered dataset.","PeriodicalId":309806,"journal":{"name":"2nd International Symposium on Search Based Software Engineering","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129241030","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 70

Using Search Methods for Selecting and Combining Software Sensors to Improve Fault Detection in Autonomic Systems 基于搜索方法的软件传感器选择与组合改进自主系统故障检测

2nd International Symposium on Search Based Software Engineering Pub Date : 2010-09-07 DOI: 10.1109/SSBSE.2010.23

M. Shevertalov, Kevin Lynch, E. Stehle, C. Rorres, S. Mancoridis

{"title":"Using Search Methods for Selecting and Combining Software Sensors to Improve Fault Detection in Autonomic Systems","authors":"M. Shevertalov, Kevin Lynch, E. Stehle, C. Rorres, S. Mancoridis","doi":"10.1109/SSBSE.2010.23","DOIUrl":"https://doi.org/10.1109/SSBSE.2010.23","url":null,"abstract":"Fault-detection approaches in autonomic systems typically rely on runtime software sensors to compute metrics for CPU utilization, memory usage, network throughput, and so on. One detection approach uses data collected by the runtime sensors to construct a convex-hull geometric object whose interior represents the normal execution of the monitored application. The approach detects faults by classifying the current application state as being either inside or outside of the convex hull. However, due to the computational complexity of creating a convex hull in multi-dimensional space, the convex-hull approach is limited to a few metrics. Therefore, not all sensors can be used to detect faults and so some must be dropped or combined with others. This paper compares the effectiveness of genetic-programming, genetic-algorithm, and random-search approaches in solving the problem of selecting sensors and combining them into metrics. These techniques are used to find 8 metrics that are derived from a set of 21 available sensors. The metrics are used to detect faults during the execution of a Java-based HTTP web server. The results of the search techniques are compared to two hand-crafted solutions specified by experts.","PeriodicalId":309806,"journal":{"name":"2nd International Symposium on Search Based Software Engineering","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114756952","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 6

An Optimization-based Approach to Software Development Process Tailoring 基于优化的软件开发过程裁剪方法

2nd International Symposium on Search Based Software Engineering Pub Date : 2010-09-07 DOI: 10.1109/SSBSE.2010.15

A. Magdaleno

引用次数: 12

Search-based Resource Scheduling for Bug Fixing Tasks 基于搜索的Bug修复任务资源调度

2nd International Symposium on Search Based Software Engineering Pub Date : 2010-09-07 DOI: 10.1109/SSBSE.2010.24

Junchao Xiao, W. Afzal

{"title":"Search-based Resource Scheduling for Bug Fixing Tasks","authors":"Junchao Xiao, W. Afzal","doi":"10.1109/SSBSE.2010.24","DOIUrl":"https://doi.org/10.1109/SSBSE.2010.24","url":null,"abstract":"The software testing phase usually results in a large number of bugs to be fixed. The fixing of these bugs require executing certain activities (potentially concurrent) that demand resources having different competencies and workloads. Appropriate resource allocation to these bug-fixing activities can help a project manager to schedule capable resources to these activities, taking into account their availability and skill requirements for fixing different bugs. This paper presents a multi-objective search-based resource scheduling method for bug-fixing tasks. The inputs to our proposed method include i) a bug model, ii) a human resource model, iii) a capability matching method between bug-fixing activities and human resources and iv) objectives of bug-fixing. A genetic algorithm (GA) is used as a search algorithm and the output is a bug-fixing schedule, satisfying different constraints and value objectives. We have evaluated our proposed scheduling method on an industrial data set and have discussed three different scenarios. The results indicate that GA is able to effectively schedule resources by balancing different objectives. We have also compared the effectiveness of using GA with a simple hill climbing algorithm. The comparison shows that GA is able to achieve statistically better fitness values than hill-climbing.","PeriodicalId":309806,"journal":{"name":"2nd International Symposium on Search Based Software Engineering","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121557540","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 22

Ant Colony Optimization for the Next Release Problem: A Comparative Study 下一次释放问题的蚁群优化:比较研究

2nd International Symposium on Search Based Software Engineering Pub Date : 2010-09-07 DOI: 10.1109/SSBSE.2010.18

J. del Sagrado, I. M. Del Águila, F. J. Orellana

{"title":"Ant Colony Optimization for the Next Release Problem: A Comparative Study","authors":"J. del Sagrado, I. M. Del Águila, F. J. Orellana","doi":"10.1109/SSBSE.2010.18","DOIUrl":"https://doi.org/10.1109/SSBSE.2010.18","url":null,"abstract":"The selection of the enhancements to be included in the next software release is a complex task in every software development. Customers demand their own software enhancements, but all of them cannot be included in the software product, mainly due to the existence limited resources. In most of the cases, it is not feasible to develop all the new functionalities suggested by customers. Hence each new feature competes against each other to be included in the next release. This problem of minimizing development effort and maximizing customers’ satisfaction is known as the next release problem (NRP). In this work we study the NRP problem as an optimisation problem. We use and describe three different meta-heuristic search techniques for solving NRP: simulated annealing, genetic algorithms and ant colony system (specifically, we show how to adapt the ant colony system to NRP). All of them obtain good but possibly sub optimal solution. Also we make a comparative study of these techniques on a case study. Furthermore, we have observed that the sub optimal solutions found applying these techniques include a high percentage of the requirements considered as most important by each individual customer.","PeriodicalId":309806,"journal":{"name":"2nd International Symposium on Search Based Software Engineering","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115265279","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 43

Search Based Optimization of Requirements Interaction Management 基于搜索的需求交互管理优化

2nd International Symposium on Search Based Software Engineering Pub Date : 2010-09-07 DOI: 10.1109/SSBSE.2010.16

Yuanyuan Zhang, M. Harman

引用次数: 39

Sophisticated Testing of Concurrent Programs 并发程序的复杂测试

2nd International Symposium on Search Based Software Engineering Pub Date : 2010-09-07 DOI: 10.1109/SSBSE.2010.14

Zdenek Letko

引用次数: 3

A Search-Based Approach to Functional Hardware-in-the-Loop Testing 基于搜索的功能性硬件在环测试方法

2nd International Symposium on Search Based Software Engineering Pub Date : 2010-09-07 DOI: 10.1109/SSBSE.2010.22

Felix F. Lindlar, Andreas Windisch

引用次数: 19

Concept Location with Genetic Algorithms: A Comparison of Four Distributed Architectures 概念定位与遗传算法:四种分布式架构的比较

2nd International Symposium on Search Based Software Engineering Pub Date : 2010-09-07 DOI: 10.1109/SSBSE.2010.26

F. Asadi, G. Antoniol, Yann-Gaël Guéhéneuc

{"title":"Concept Location with Genetic Algorithms: A Comparison of Four Distributed Architectures","authors":"F. Asadi, G. Antoniol, Yann-Gaël Guéhéneuc","doi":"10.1109/SSBSE.2010.26","DOIUrl":"https://doi.org/10.1109/SSBSE.2010.26","url":null,"abstract":"Genetic algorithms are attractive to solve many search-based software engineering problems because they allow the easy parallelization of computations, which improves scalability and reduces computation time. In this paper, we present our experience in applying different distributed architectures to parallelize a genetic algorithm used to solve the concept identification problem. We developed an approach to identify concepts in execution traces by finding cohesive and decoupled fragments of the traces. The approach relies on a genetic algorithm, on a textual analysis of source code using latent semantic indexing, and on trace compression techniques. The fitness function in our approach has a polynomial evaluation cost and is highly computationally intensive. A run of our approach on a trace of thousand methods may require several hours of computation on a standard PC. Consequently, we reduced computation time by parallelizing the genetic algorithm at the core of our approach over a standard TCP/IP network. We developed four distributed architectures and compared their performances: we observed a decrease of computation time up to 140 times. Although presented in the context of concept location, our findings could be applied to many other search-based software engineering problems.","PeriodicalId":309806,"journal":{"name":"2nd International Symposium on Search Based Software Engineering","volume":"5 5","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132791966","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 28

Applying Elementary Landscape Analysis to Search-Based Software Engineering 基础景观分析在基于搜索的软件工程中的应用

2nd International Symposium on Search Based Software Engineering Pub Date : 2010-09-07 DOI: 10.1109/SSBSE.2010.10

Guanzhou Lu, R. Bahsoon, X. Yao

引用次数: 17