Zobrazeno 1 - 10
of 119
pro vyhledávání: '"Wilhelm Meding"'
Publikováno v:
IEEE Software. 37:76-85
This article presents a novel method for determining the factual adoption of new processes in software R&D organizations. We use a DNA-inspired analysis (motifs) to categorize parts and find similarities between projects using defect-inflow profiles.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6b0c3426d9e5f2834bfad912fa8567b1
https://doi.org/10.1109/ms.2020.2971894
https://doi.org/10.1109/ms.2020.2971894
Publikováno v:
Software Quality: The Next Big Thing in Software Engineering and Quality ISBN: 9783031041143
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7b4b11ebe6bcfef1d26c74cc86614bc9
https://doi.org/10.1007/978-3-031-04115-0_3
https://doi.org/10.1007/978-3-031-04115-0_3
Publikováno v:
2021 28th Asia-Pacific Software Engineering Conference (APSEC).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::729adf6f03f8cdcf03b17f73719eea1d
https://doi.org/10.1109/apsec53868.2021.00047
https://doi.org/10.1109/apsec53868.2021.00047
Publikováno v:
SEAA
As technology has allowed us to collect large amounts of industrial data, it has become critical to analyze and understand the data collected, in particular to find data anomalies. Anomaly analysis allows a company to detect, analyze and understand a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c278b315e33c48c4a985ba5f30c0ee4b
https://doi.org/10.1109/seaa53835.2021.00024
https://doi.org/10.1109/seaa53835.2021.00024
Publikováno v:
Empirical Software Engineering. 25:220-265
Software developers in big and medium-size companies are working with millions of lines of code in their codebases. Assuring the quality of this code has shifted from simple defect management to proactive assurance of internal code quality. Although
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7d27485155dbd3464362ad6f4d04d6ba
https://doi.org/10.1007/s10664-019-09769-8
https://doi.org/10.1007/s10664-019-09769-8
Publikováno v:
Information and Software Technology. 115:131-147
Background Profiling software development projects, in order to compare them, find similar sub-projects or sets of activities, helps to monitor changes in software processes. Since we lack objective measures for profiling or hashing, researchers ofte
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::202de74e4ae6e97588f781bd89373ea7
https://doi.org/10.1016/j.infsof.2019.06.003
https://doi.org/10.1016/j.infsof.2019.06.003
Publikováno v:
Foundations of Computing and Decision Sciences, Vol 43, Iss 4, Pp 281-303 (2018)
Continuous integration and continuous software deployment depend on the mix of automated and manual activities. The automated build and test processes are often intertwined with manual reviews and bug-fixing activities. In this paper, we set o to stu
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::195a01d5f4d47f3a6001a46cf7ee57e9
https://doi.org/10.1515/fcds-2018-0015
https://doi.org/10.1515/fcds-2018-0015
Publikováno v:
Software Quality: Future Perspectives on Software Engineering Quality ISBN: 9783030658533
SWQD
SWQD
Machine learning is used increasingly frequent in software engineering to automate tasks and improve the speed and quality of software products. One of the areas where machine learning starts to be used is the analysis of software code. The goal of t
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4a1e596c9f78e8d55b55f64cb0cc7976
https://doi.org/10.1007/978-3-030-65854-0_7
https://doi.org/10.1007/978-3-030-65854-0_7
Publikováno v:
ICST Workshops
Regression testing is a necessary activity in continuous integration (CI) since it provides confidence that modified parts of the system are correct at each integration cycle. CI provides large volumes of data which can be used to support regression
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::51775ed350babffe37917dcd69904500
https://doi.org/10.1109/icstw50294.2020.00058
https://doi.org/10.1109/icstw50294.2020.00058
Publikováno v:
SEAA
Big data and machine learning models have been increasingly used to support software engineering processes and practices. One example is the use of machine learning models to improve test case selection in continuous integration. However, one of the
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2b39163c693171c001c27b4812d1894a
https://doi.org/10.1109/seaa51224.2020.00042
https://doi.org/10.1109/seaa51224.2020.00042