Requirements Quality Research Artifacts: Recovery, Analysis, and Management Guideline
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arXiv
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| Main Authors: | , , , , , |
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| Format: | Preprint |
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2024
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| _version_ | 1866915093164326912 |
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| author | Frattini, Julian Montgomery, Lloyd Fucci, Davide Unterkalmsteiner, Michael Mendez, Daniel Fischbach, Jannik |
| author_facet | Frattini, Julian Montgomery, Lloyd Fucci, Davide Unterkalmsteiner, Michael Mendez, Daniel Fischbach, Jannik |
| contents | Requirements quality research, which is dedicated to assessing and improving the quality of requirements specifications, is dependent on research artifacts like data sets (containing information about quality defects) and implementations (automatically detecting and removing these defects). However, recent research exposed that the majority of these research artifacts have become unavailable or have never been disclosed, which inhibits progress in the research domain. In this work, we aim to improve the availability of research artifacts in requirements quality research. To this end, we (1) extend an artifact recovery initiative, (2) empirically evaluate the reasons for artifact unavailability using Bayesian data analysis, and (3) compile a concise guideline for open science artifact disclosure. Our results include 10 recovered data sets and 7 recovered implementations, empirical support for artifact availability improving over time and the positive effect of public hosting services, and a pragmatic artifact management guideline open for community comments. With this work, we hope to encourage and support adherence to open science principles and improve the availability of research artifacts for the requirements research quality community. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2406_01055 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Requirements Quality Research Artifacts: Recovery, Analysis, and Management Guideline Frattini, Julian Montgomery, Lloyd Fucci, Davide Unterkalmsteiner, Michael Mendez, Daniel Fischbach, Jannik Software Engineering Requirements quality research, which is dedicated to assessing and improving the quality of requirements specifications, is dependent on research artifacts like data sets (containing information about quality defects) and implementations (automatically detecting and removing these defects). However, recent research exposed that the majority of these research artifacts have become unavailable or have never been disclosed, which inhibits progress in the research domain. In this work, we aim to improve the availability of research artifacts in requirements quality research. To this end, we (1) extend an artifact recovery initiative, (2) empirically evaluate the reasons for artifact unavailability using Bayesian data analysis, and (3) compile a concise guideline for open science artifact disclosure. Our results include 10 recovered data sets and 7 recovered implementations, empirical support for artifact availability improving over time and the positive effect of public hosting services, and a pragmatic artifact management guideline open for community comments. With this work, we hope to encourage and support adherence to open science principles and improve the availability of research artifacts for the requirements research quality community. |
| title | Requirements Quality Research Artifacts: Recovery, Analysis, and Management Guideline |
| topic | Software Engineering |
| url | https://arxiv.org/abs/2406.01055 |