Latin Square Design: A Guide to Its Use in Software Engineering Experiments

Table of Links

Abstract and 1. Introduction

2. Experiment Definition

3. Experiment Design and Conduct

3.1 Latin Square Designs

3.2 Subjects, Tasks and Objects

3.3 Conduct

3.4 Measures

4. Data Analysis

4.1 Model Assumptions

4.2 Analysis of Variance (ANOVA)

4.3 Treatment Comparisons

4.4 Effect Size and Power Analysis

5. Experiment Limitations and 5.1 Threats to the Conclusion Validity

5.2 Threats to Internal Validity

5.3 Threats to Construct Validity

5.4 Threats to External Validity

6. Discussion and 6.1 Duration

6.2 Effort

7. Conclusions and Further Work, and References

3. Experiment Design and Conduct

The previous hypotheses will be tested through different measures that we will collect from subjects during the experiment. In a general way, measures belong to two subject groups: Those who perform a task in pairs and those who perform it individually. With these measures, we will perform statistical analyses given an experimental design.

\ At the beginning of the DOE course, we decided to conduct the experiment at the midterm (semester) in order to students had certain knowledge of DOE and that they had sufficient time to write a report before the semester ended.

\ The experimental design to use was selected according to the designs listed in the DOE course syllabus. Specifically, we chose the Latin square design because it was scheduled in the course syllabus at midterm, just a few days before the experiment was conducted.

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:::info Authors:

(1) Omar S. Gómez, full time professor of Software Engineering at Mathematics Faculty of the Autonomous University of Yucatan (UADY);

(2) José L. Batún, full time professor of Statistics at Mathematics Faculty of the Autonomous University of Yucatan (UADY);

(3) Raúl A. Aguilar, Faculty of Mathematics, Autonomous University of Yucatan Merida, Yucatan 97119, Mexico.

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:::info This paper is available on arxiv under CC BY-NC-ND 4.0 DEED license.

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