NDLI: Data Sets and Data Quality in Software Engineering: Eight Years On

Please wait, while we are loading the content...

Forecasting Communication Behavior in Student Software Projects

Estimating Story Points from Issue Reports

Search Based Training Data Selection For Cross Project Defect Prediction

On the Terms Within- and Cross-Company in Software Effort Estimation

Measuring the Stylistic Inconsistency in Software Projects using Hierarchical Agglomerative Clustering

An Empirical Evaluation of Distribution-based Thresholds for Internal Software Measures

Data Sets and Data Quality in Software Engineering: Eight Years On

Hidden Markov Models for the Prediction of Developer Involvement Dynamics and Workload

Predicting the Popularity of GitHub Repositories

A Manually Validated Code Refactoring Dataset and Its Assessment Regarding Software Maintainability

Data Sets and Data Quality in Software Engineering: Eight Years On

Content Provider	ACM Digital Library
Author	Shepperd, Martin Liebchen, Gernot
Abstract	Context: We revisit our review of data quality within the context of empirical software engineering eight years on from our PROMISE 2008 article. Objective: To assess the extent and types of techniques used to manage quality within data sets. We consider this a particularly interesting question in the context of initiatives to promote sharing and secondary analysis of data sets. Method: We update the 2008 mapping study through four subsequently published reviews and a snowballing exercise. Results: The original study located only 23 articles explicitly considering data quality. This picture has changed substantially as our updated review now finds 283 articles, however, our estimate is that this still represents perhaps 1% of the total empirical software engineering literature. Conclusions: It appears the community is now taking the issue of data quality more seriously and there is more work exploring techniques to automatically detect (and sometimes repair) noise problems. However, there is still little systematic work to evaluate the various data sets that are widely used for secondary analysis; addressing this would be of considerable benefit. It should also be a priority to work collab-oratively with practitioners to add new, higher quality data to the existing corpora.
Starting Page	1
Ending Page	4
Page Count	4
File Format	PDF
ISBN	9781450347723
DOI	10.1145/2972958.2972967
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2016-09-09
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Empirical software engineering Mapping study Data quality
Content Type	Text
Resource Type	Article

Central Library (ISO-9001:2015 Certified)
Indian Institute of Technology Kharagpur
Kharagpur, West Bengal, India | PIN - 721302

See location in the Map
03222 282435
Mail: support@ndl.gov.in

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in