Schema Evolution in Interactive Programming Systems

Many improvements to programming have come from shortening feedback loops, for example with Integrated Development Environments, Unit Testing, Live Programming, and Distributed Version Control.A barrier to feedback that deserves greater attention is Schema Evolution.When requirements on the shape of data change then existing data must be migrated into the new shape, and existing code must be modified to suit.Currently these adaptations are often performed manually, or with ad hoc scripts.Manual schema evolution not only delays feedback but since it occurs outside the purview of version control tools it also interrupts collaboration.Schema evolution has long been studied in databases.We observe that the problem also occurs in nondatabase contexts that have been less studied.We present a suite of challenge problems exemplifying this range of contexts, including traditional database programming as well as live front-end programming, modeldriven development, and collaboration in computational documents.We systematize these various contexts by defining a set of layers and dimensions of schema evolution.We offer these challenge problems to ground future research on the general problem of schema evolution in interactive programming systems and to serve as a basis for evaluating the results of that research.We hope that better support for schema evolution will make programming more live and collaboration more fluid.

Authors

Institutions

Publication Details

Journal
The Art Science and Engineering of Programming
Published
2024-10-15
DOI
https://doi.org/10.22152/programming-journal.org/2025/9/2
Citations
1
Primary Topic
Artificial Intelligence in Games
Type
article
Field-Weighted Citation Impact
0.35

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Schema Evolution in Interactive Programming Systems

Geoffrey Litt, Tijs van der Storm, Jonathan Edwards
1 citations
The Art Science and Engineering of Programming
Artificial Intelligence in Games
0.35
article

Schema Evolution in Interactive Programming Systems

Geoffrey Litt, Tijs van der Storm, Jonathan Edwards
article en
1 citations

Abstract

Many improvements to programming have come from shortening feedback loops, for example with Integrated Development Environments, Unit Testing, Live Programming, and Distributed Version Control.A barrier to feedback that deserves greater attention is Schema Evolution.When requirements on the shape of data change then existing data must be migrated into the new shape, and existing code must be modified to suit.Currently these adaptations are often performed manually, or with ad hoc scripts.Manual schema evolution not only delays feedback but since it occurs outside the purview of version control tools it also interrupts collaboration.Schema evolution has long been studied in databases.We observe that the problem also occurs in nondatabase contexts that have been less studied.We present a suite of challenge problems exemplifying this range of contexts, including traditional database programming as well as live front-end programming, modeldriven development, and collaboration in computational documents.We systematize these various contexts by defining a set of layers and dimensions of schema evolution.We offer these challenge problems to ground future research on the general problem of schema evolution in interactive programming systems and to serve as a basis for evaluating the results of that research.We hope that better support for schema evolution will make programming more live and collaboration more fluid.

The Art Science and Engineering of ProgrammingVol. 9(1)
Centrum Wiskunde & Informatica (NL), University of Groningen (NL), Charles University (CZ), Southeastern Wisconsin Information Technology Exchange Consortium (US)
Univerzita Karlova v Praze
Openalex Percentile: Top 31%
Artificial Intelligence in Games
0.35
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.