Paper Info
Title
Are Models Easier To Understand Than Code? An Empirical Study On Comprehension Of Entity-Relationship (Er) Models Vs. Structured Query Language (Sql) Code
Abstract
Models in Software Engineering are considered as abstract representations of software systems. Models highlight relevant details for a certain purpose, whereas irrelevant ones are hidden. Models are supposed to make system comprehension easier by reducing complexity. Therefore, models should play a key role in education, since they would ease the students' learning process. Although these statements are widely accepted, to the best of our knowledge, there is no empirical evidence that supports these hypotheses (beyond practitioners' personal experience). This article aims to contribute to fill this gap by performing an empirical study on how well students understand entity-relationship database models as compared to structured query language (SQL) code. Several ER models and their corresponding SQL code (more specifically, the data definition language (DDL) statements required to create such models) were shown to a heterogeneous group of students, who answered different questions about the database systems represented by these artifacts. Then, we analysed the correctness of the answers to check whether the ER models really improved students' comprehension.
Year
DOI
Venue
2011
10.1080/08993408.2011.630128
COMPUTER SCIENCE EDUCATION
Keywords
Field
DocType
entity-relationship models, SQL, empirical research, software models, abstraction
SQL,Database model,Computer science,Data definition language,Software system,Database design,Query by Example,Artificial intelligence,Natural language processing,Empirical research,Entity–relationship model
Journal
Volume
Issue
ISSN
21
4
0899-3408
Citations 
PageRank 
References 
1
0.35
12
Authors
4
Name
Order
Citations
PageRank
Pablo Sánchez13615.41
Marta E. Zorrilla25116.05
Rafael Duque Medina321.06
Alicia Nieto-Reyes4314.94