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Autori principali: Jovanovic, Ana, Sullivan, Allison
Natura: Preprint
Pubblicazione: 2024
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Accesso online:https://arxiv.org/abs/2402.06624
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author Jovanovic, Ana
Sullivan, Allison
author_facet Jovanovic, Ana
Sullivan, Allison
contents Writing declarative models has numerous benefits, ranging from automated reasoning and correction of design-level properties before systems are built, to automated testing and debugging of their implementations after they are built. Alloy is a declarative modeling language that is well-suited for verifying system designs. A key strength of Alloy is its scenario-finding toolset, the Analyzer, which allows users to explore all valid scenarios that adhere to the model's constraints up to a user-provided scope. However, even with visualized scenarios, it is difficult to write correct Alloy models. To address this, a growing body of work explores different techniques for debugging Alloy models. In order to develop and evaluate these techniques in an effective manor, this paper presents an empirical study of over 97,000 models written by novice users trying to learn Alloy. We investigate how users write both correct and incorrect models in order to produce a comprehensive benchmark for future use as well as a series of observations to guide debugging and educational efforts for Alloy model development.
format Preprint
id arxiv_https___arxiv_org_abs_2402_06624
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Right or Wrong -- Understanding How Novice Users Write Software Models
Jovanovic, Ana
Sullivan, Allison
Software Engineering
Writing declarative models has numerous benefits, ranging from automated reasoning and correction of design-level properties before systems are built, to automated testing and debugging of their implementations after they are built. Alloy is a declarative modeling language that is well-suited for verifying system designs. A key strength of Alloy is its scenario-finding toolset, the Analyzer, which allows users to explore all valid scenarios that adhere to the model's constraints up to a user-provided scope. However, even with visualized scenarios, it is difficult to write correct Alloy models. To address this, a growing body of work explores different techniques for debugging Alloy models. In order to develop and evaluate these techniques in an effective manor, this paper presents an empirical study of over 97,000 models written by novice users trying to learn Alloy. We investigate how users write both correct and incorrect models in order to produce a comprehensive benchmark for future use as well as a series of observations to guide debugging and educational efforts for Alloy model development.
title Right or Wrong -- Understanding How Novice Users Write Software Models
topic Software Engineering
url https://arxiv.org/abs/2402.06624