International Advanced School of Empirical Software Engineering


Replication and Aggregation of Software Engineering Experiments

In its early days, Empirical SE (ESE) focused on studying the application of the principles of the laboratory and experiment to SE. Twenty years later, running lab experiments in ESE is a fairly well understood task. But running isolated experiments is just one step of the experimental paradigm. Other principles of experimentalism remain to be analysed and adapted to SE: Experiment reporting; Replication; Systematic reviews; Aggregation, etc.

This year, the International Advanced School on ESE (IASESE'08) focuses in two of these aspects that are much related: Replication and Aggregation. That is, how to aggregate the results to combine the findings of replications. The School will be formed of three parts:

  • Part I. Aggregation Methods for ESE
  • Part II. Different Types of Replications, Different Goals of Aggregation
  • Part III. Students Exercises

Learning Objectives

Participants in the School will:
  • Understand basic principles of aggregation and replication.
  • Learn aggregation methods adapted to the current state of ESE.
  • Be able to combine aggregation methods in order to extract evidences from aggregating the results of several experiments.
  • Understand the potential of inexact (differentiated) replications.
  • Be able to generate new variables from aggregating differentiated replications.

The goal of the International Advanced School on Empirical Software Engineering (IASESE) is to provide attendees with the opportunity to learn and practice advanced empirical software engineering techniques from leaders in the empirical software engineering community. The course is of interest to researchers interested in deepening their knowledge and skills in empirical research.

Who should attend?

Anyone with a basic knowledge of software engineering and empirical studies of software engineering, who is interested in increasing his/her repertoire of empirical methods. Basic concepts of experiment design and software engineering measurement will not be covered.

What will participants take away?

Participants will gain a basic knowledge of new techniques that they may not have been aware of or applied previously, a general idea of when they would be appropriate (and when not), and pointers to resources to be used and how to get started if they wish to apply the techniques on their own.

This year, IASESE chair is:

Natalia Juristo
Natalia Juristo
Universidad Politécnica de Madrid
International Advanced School of Empirical Software Engineering 2008 - Kaiserslautern