Name
Abstract | ||
|---|---|---|
Modern software projects consist of more than just code: teams follow development processes, the code runs on servers or mobile phones and produces run time logs and users talk about the software in forums like StackOverflow and Twitter and rate it on app stores. Insights stemming from the real-time analysis of combined software engineering data can help software practitioners to conduct faster decision-making. With the development of CodeFeedr, a Real-time Software Analytics Platform, we aim to make software analytics a core feedback loop for software engineering projects. CodeFeedr's vision entails: (1) The ability to unify archival and current software analytics data under a single query language, and (2) The feasibility to apply new techniques and methods for high-level aggregation and summarization of near real-time information on software development. In this paper, we outline three use cases where our platform is expected to have a significant impact on the quality and speed of decision making; dependency management, productivity analytics, and run-time error feedback.
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Year | DOI | Venue |
|---|---|---|
2018 | 10.1145/3183399.3183417 | ICSE (NIER) |
Keywords | Field | DocType |
software analytics,real time feedback,streaming data | Automatic summarization,Use case,Software engineering,Software analytics,Computer science,Server,Software,Analytics,Software development,Search-based software engineering | Conference |
ISBN | Citations | PageRank |
978-1-4503-5662-6 | 5 | 0.45 |
References | Authors | |
9 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Enrique Larios Vargas | 1 | 5 | 0.45 |
| Joseph Hejderup | 2 | 5 | 1.13 |
| Maria Kechagia | 3 | 74 | 8.36 |
| Magiel Bruntink | 4 | 383 | 24.25 |
| Georgios Gousios | 5 | 1333 | 67.86 |