@article {Simula.simula.742,
	title = {How Does Project Size Affect Cost Estimation Error? Statistical Artifacts and Methodological Challenges},
	journal = {International Journal of Project Management},
	volume = {30},
	number = {7},
	year = {2012},
	pages = {751-862},
	abstract = {Empirical studies differ in what they report as the underlying relation between project size and percent cost overrun. As a consequence, the studies also differ in their project management recommendations. We show that studies with a project size measure based on the actual cost systematically report an increase in percent cost overrun with increased project size, whereas studies with a project size measure based on the estimated cost report a decrease or no change in percent cost overrun with increased project size. The observed pattern is, we argue, to some extent a statistical artifact caused by imperfect correlation between the estimated and the actual cost. We conclude that the previous observational studies cannot be considered as providing reliable evidence in favor of an underlying project size related cost estimation bias. The more robust evidence from controlled experiments, limited to small tasks, suggests an increase in underestimation with increased project size.},
	author = {J{\o}rgensen, Magne and Halkjelsvik, Torleif and Kitchenham, Barbara}
}
@article {Simula.simula.126,
	title = {Interpretation Problems Related to the Use of Regression Models to Decide on Economy of Scale in Software Development},
	journal = {Journal of Systems and Software},
	volume = {85},
	number = {11},
	year = {2012},
	pages = {2494-2503},
	abstract = {Many research studies report an economy of scale in software development, i.e., an increase in productivity with increasing project size. Several software practitioners seem, on the other hand, to believe in a diseconomy of scale, i.e., a decrease in productivity with increasing project size. In this paper we argue that violations of essential regression model assumptions in the research studies to a large extent may explain this disagreement. Particularly illustrating is the finding that the use of the production function (Size = a\bulletEffortb), instead of the factor input model (Effort=a\bulletSizeb), would most likely have led to the opposite result, i.e., a tendency towards reporting diseconomy of scale in the research studies. We conclude that there are good reasons to warn against the use of regression analysis parameters to investigate economies of scale and to look for other analysis methods when studying economy of scale in software development contexts.},
	author = {J{\o}rgensen, Magne and Kitchenham, Barbara}
}
@inproceedings {Simula.SE.208,
	title = {Reflections on 10 Years of Software Process Simulation Modeling: a Systematic Review},
	journal = {International Conference on Software Process (ICSP 2008)},
	year = {2008},
	pages = {345-356},
	publisher = {Springer},
	type = {1},
	isbn = {978-3-540-79587-2},
	author = {Zhang, He and Kitchenham, Barbara and Pfahl, Dietmar},
	editor = {Wang, Q. and Pfahl, D. and Raffo, D.}
}
@inproceedings {Simula.SE.291,
	title = {Software Process Simulation Modeling: Facts, Trends and Directions},
	journal = {Proceedings of the 15th Asia-Pacific Software Engineering Conference (APSEC 2008)},
	year = {2008},
	pages = {59-66},
	publisher = {IEEE Computer Society},
	type = {Conference},
	isbn = {978-0-7695-3446-6},
	author = {Zhang, He and Kitchenham, Barbara and Pfahl, Dietmar},
	editor = {Lin et {al.}}
}
@inproceedings {Simula.SE.285,
	title = {Software Process Simulation Over the Past Decade: Trends Discovery From a Systematic Review},
	journal = {ACM-IEEE International Symposium on Empirical Software Engineering and Measurement (ESEM 2008)},
	year = {2008},
	pages = {345-348},
	publisher = {ACM SIGSOFT \& IEEE CS},
	type = {Conference},
	abstract = {Software Process Simulation (SPS) research has increased since 1998 when the frst ProSim Workshop was held. Thispaper aims to reveal how SPS has evolved during the past 10 years based on the preliminary results from the systematic literature review of SPS publications from 1998 to 2007. Trends over the period showed that interest in continuous modelling was decreasing and interest in micro-processes was increasing. Hybrid models were based primarily on system dynamics and discrete event simulation and were all implemented by vertical integration.},
	isbn = {978-1-59593-971-5},
	author = {Zhang, He and Kitchenham, Barbara and Pfahl, Dietmar},
	editor = {Elbaum, S. and Muench, Juergen}
}
@inbook {Simula.SE.10,
	title = {Documenting Theories},
	booktitle = {Empirical Software Engineering Issues: Critical Assessment and Future Directions},
	series = {LNCS 4336},
	year = {2007},
	pages = {111-114},
	publisher = {Springer},
	organization = {Springer},
	address = {Berlin Heidelberg},
	author = {Sj{\o}berg, Dag Ingar Kondrup},
	editor = {Basili, V.R. and Rombach, D. and Schneider, K. and Kitchenham, Barbara and Pfahl, D. and Selby, R.}
}
@book {Simula.SE.200,
	title = {Empirical Software Engineering Issues - Critical Assessment and Future Directions. International Workshop, Dagstuhl Castle, Germany, June 26-30, 2006, Revised Papers},
	volume = {LNCS 4336},
	year = {2007},
	month = {May},
	publisher = {Springer},
	abstract = {This book constitutes the thoroughly refereed post-proceedings of the International Dagstuhl-Seminar on Empirical Software Engineering, held in Dagstuhl Castle, Germany in June 2006. The purpose of this workshop was to identify the progress of empirical software engineering since 1992, to summarize the state-of-the-art in ESE, to summarize the state-of-the-practice in ESE in industry, and to develop an ESE roadmap for research, practice, education and training.},
	isbn = {978-3-540-71300-5},
	author = {Rombach, Dieter and Basili, Victor and Schneider, Kurt and Kitchenham, Barbara and Pfahl, Dietmar and Selby, Rick}
}
@inbook {Simula.SE.11,
	title = {Knowledge Acquisition in Software Engineering Requires Sharing of Data and Artifacts},
	booktitle = {Empirical Software Engineering Issues: Critical Assessment and Future Directions},
	series = {LNCS 4336},
	year = {2007},
	pages = {77-82},
	publisher = {Springer},
	organization = {Springer},
	address = {Berlin Heidelberg},
	author = {Sj{\o}berg, Dag Ingar Kondrup},
	editor = {Basili, V.R. and Rombach, D. and Schneider, K. and Kitchenham, Barbara and Pfahl, D. and Selby, R.}
}
@inproceedings {Jorgensen.2006.1,
	title = {Prediction of Optimistic Expert Judgment-Based Predictions},
	journal = {EASE 2006},
	year = {2006},
	pages = {40-49},
	publisher = {BCS},
	type = {1},
	address = {UK},
	abstract = {(Paper selected for publication in JSS)},
	isbn = {ISSN 1477-9358},
	author = {J{\o}rgensen, Magne and Faugli, Bj{\o}rn},
	editor = {Kitchenham, Barbara}
}
@article {Dyba.2005.1,
	title = {Evidence-Based Software Engineering for Practitioners},
	journal = {IEEE Software},
	volume = {22},
	number = {1},
	year = {2005},
	pages = {58-65},
	publisher = {-},
	abstract = {Objective: Our objective is to explain how practitioners in industry can use evidencebased software engineering (EBSE) to assist decisions concerning the adoption of new techniques. Rationale: Practitioners may make incorrect technology adoption decisions if they do not consider scientific evidence about the efficacy of techniques. Method: We adapt procedures used for evidence-based medicine to software engineering and discuss how these procedures map to software process improvement. Results: We found EBSE fitted well with current ideas concerning process improvement and that it could be an important means for closing the gap between research and practice. However EBSE presents difficulties for practitioners because current software engineering research is limited and not reported in a manner that assists accumulation and evaluation of evidence. Conclusions: EBSE has potential benefits for software engineering practitioners, but will be hindered without changes to software engineering research. Keywords: Evidence, empirical software engineering, evaluation.}, how these procedures map to software process improvement. Results = {We found EBSE},
	keywords = {empirical software engineering, evaluation., Evidence},
	author = {Dyb{\r a}, Tore and Kitchenham, Barbara and J{\o}rgensen, Magne}
}
@inproceedings {Jorgensen.2005.4,
	title = {Teaching Evidence-Based Software Engineering to University Students},
	journal = {11th IEEE International Software Metrics Symposium, Como, Italy, September 19-22},
	year = {2005},
	month = {September},
	type = {1},
	abstract = {Evidence-based software engineering (EBSE) describes a process of identifying, understanding and evaluating findings from research and practice-based experience. This process aims at improving software engineering decisions. For the last three years, EBSE has been taught to university students at Hedmark University College, Rena, Norway. The motivation for the EBSE-course is that it is essential for the students, as future practitioners, to learn how to base important software engineering decisions on the systematic and critical evaluation of the best available evidence. The main purpose of this paper is to inspire and support other universities in their work on developing their own EBSE-courses. For this purpose we report on how our course has been organized and what lessons have been learned. There are currently no studies available on the effects of teaching EBSE and, as far as we know, only we have gained practice-based experience. To acquire more knowledge about the costs and benefits of teaching EBSE we hope that other universities will develop their own EBSE-courses and report their experience.},
	author = {J{\o}rgensen, Magne and Kitchenham, Barbara and Dyb{\r a}, Tore}
}
@inproceedings {SE.5.Kitchenham.2004,
	title = {Evidence-Based Software Engineering},
	journal = {International Conference on Software Engineering (ICSE{\textquoteright}04)},
	year = {2004},
	month = {23-28 May},
	pages = {273-281},
	publisher = {IEEE Computer Society, Washington DC, USA},
	type = {1},
	address = {Edinburgh},
	abstract = {Objective: Our objective is to describe how software engineering might benefit from an evidence-based approach and to identify the potential difficulties associated with the approach. Method: We compared the organisation and technical infrastructure supporting evidence-based medicine (EBM) with the situation in software engineering. We considered the impact that factors peculiar to software engineering (i.e. the skill factor and the lifecycle factor) would have on our ability to practice evidence-based software engineering (EBSE). Results: EBSE promises a number of benefits by encouraging integration of research results with a view to supporting the needs of many different stakeholder groups. However, we do not currently have the infrastructure needed for widespread adoption of EBSE. The skill factor means software engineering experiments are vulnerable to subject and experimenter bias. The lifecycle factor means it is difficult to determine how technologies will behave once deployed. Conclusions: Software engineering would benefit from adopting what it can of the evidence approach provided that it deals with the specific problems that arise from the nature of software engineering.},
	author = {Kitchenham, Barbara and Dyb{\r a}, Tore and J{\o}rgensen, Magne}
}
