Abstract | ||
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The ISO/IEC 14764 standard specifies four types of software maintenance activities spanning the different motivations that software engineers have while performing changes to an existing software system. Undoubtedly, this classification has helped in organizing the workflow within software projects, however for planning purposes the relative time differences for the respective tasks remains largely unexplored. In this empirical study, we investigate the influence of the maintenance type on issue resolution time. From GitHub's issue repository, we analyze more than 14000 issue reports taken from 34 open source projects and classify them as corrective, adaptive, perfective or preventive maintenance. Based on this data, we show that the issue resolution time depends on the maintenance type. Moreover, we propose a statistical model to describe the distribution of the issue resolution time for each type of maintenance activity. Finally, we demonstrate the usefulness of this model for scheduling the maintenance workload. |
Year | DOI | Venue |
---|---|---|
2014 | 10.1145/2639490.2639506 | Promise |
Keywords | Field | DocType |
process metrics,software maintenance,issue repository,measurement,empirical software engineering,issue resolution-time | Data mining,Software engineering,Computer science,Workload,Software system,Software,Empirical process (process control model),Software maintenance,Workflow,Preventive maintenance,Empirical research | Conference |
Citations | PageRank | References |
9 | 0.57 | 13 |
Authors | ||
6 |
Name | Order | Citations | PageRank |
---|---|---|---|
Alessandro Murgia | 1 | 246 | 16.20 |
Giulio Concas | 2 | 424 | 44.83 |
Roberto Tonelli | 3 | 145 | 19.35 |
Marco Ortu | 4 | 267 | 16.83 |
Serge Demeyer | 5 | 2250 | 291.74 |
Michele Marchesi | 6 | 807 | 120.28 |