![](https://dblp1.uni-trier.de/img/logo.ua.320x120.png)
![](https://dblp1.uni-trier.de/img/dropdown.dark.16x16.png)
![](https://dblp1.uni-trier.de/img/peace.dark.16x16.png)
Остановите войну!
for scientists:
![search dblp search dblp](https://dblp1.uni-trier.de/img/search.dark.16x16.png)
![search dblp](https://dblp1.uni-trier.de/img/search.dark.16x16.png)
default search action
PROMISE 2010: Timisoara, Romania
- Tim Menzies, Günes Koru:
Proceedings of the 6th International Conference on Predictive Models in Software Engineering, PROMISE 2010, Timisoara, Romania, September 12-13, 2010. ACM 2010, ISBN 978-1-4503-0404-7
Keynote
- Mark Harman
:
The relationship between search based software engineering and predictive modeling. 1
Search-based software engineering
- Gregory Gay:
A baseline method for search-based software engineering. 2 - Adam Brady, Tim Menzies:
Case-based reasoning vs parametric models for software quality optimization. 3
Search-based software engineering & methodology
- Anna Corazza
, Sergio Di Martino
, Filomena Ferrucci, Carmine Gravino
, Federica Sarro
, Emilia Mendes:
How effective is Tabu search to configure support vector regression for effort estimation? 4 - Thilo Mende:
Replication of defect prediction studies: problems, pitfalls and recommendations. 5
Effort estimation
- Luigi Lavazza
, Gabriela Robiolo
:
The role of the measure of functional complexity in effort estimation. 6 - Nikolaos Mittas
, Makrina Viola Kosti, Vasiliki Argyropoulou, Lefteris Angelis:
Modeling the relationship between software effort and size using deming regression. 7
Categorization for defect prediction I
- Bora Caglayan, Ayse Tosun
, Andriy V. Miranskyy, Ayse Basar Bener
, Nuzio Ruffolo:
Usage of multiple prediction models based on defect categories. 8 - Marian Jureczko, Lech Madeyski
:
Towards identifying software project clusters with regard to defect prediction. 9
Testing & quality
- Gul Calikli
, Ayse Basar Bener
:
Empirical analyses of the factors affecting confirmation bias and the effects of confirmation bias on software developer/tester performance. 10 - Burak Turhan
, Çetin Meriçli, Tekin Meriçli:
Better, faster, and cheaper: what is better software? 11
Operational profile & data quality
- Rui Abreu
, Alberto González-Sanchez, Arjan J. C. van Gemund:
Exploiting count spectra for Bayesian fault localization. 12 - Marta Fernández-Diego
, Mónica Martínez-Gómez
, José-María Torralba-Martínez:
Sensitivity of results to different data quality meta-data criteria in the sample selection of projects from the ISBSG dataset. 13
Categorization for defect prediction II
- Hongyu Zhang
, Adam Nelson, Tim Menzies:
On the value of learning from defect dense components for software defect prediction. 14 - Youngki Hong, Wondae Kim, Jeongsoo Joo:
Prediction of defect distribution based on project characteristics for proactive project management. 15
Cost modeling
- Thomas Schulz, Lukasz Radlinski
, Thomas Gorges, Wolfgang Rosenstiel:
Defect cost flow model: a Bayesian network for predicting defect correction effort. 16 - Ralf Gitzel, Simone Krug, Manuel Brhel:
Towards a software failure cost impact model for the customer: an analysis of an open source product. 17
Developer-based fault prediction
- Shinsuke Matsumoto, Yasutaka Kamei, Akito Monden
, Ken-ichi Matsumoto, Masahide Nakamura:
An analysis of developer metrics for fault prediction. 18 - Thomas J. Ostrand, Elaine J. Weyuker, Robert M. Bell:
Programmer-based fault prediction. 19
![](https://dblp1.uni-trier.de/img/cog.dark.24x24.png)
manage site settings
To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.