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Micro process analysis of maintenance effort: an open source software case study using metrics based on program slicing
Author(s) -
Kula Raula Gaikovina,
Fushida Kyohei,
Yoshida Norihiro,
Iida Hajimu
Publication year - 2013
Publication title -
journal of software: evolution and process
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.371
H-Index - 29
eISSN - 2047-7481
pISSN - 2047-7473
DOI - 10.1002/smr.1572
Subject(s) - software maintenance , maintainability , program slicing , computer science , software engineering , software metric , reliability engineering , software development , software development process , process (computing) , software , change impact analysis , software quality , engineering , operating system
SUMMARY For any software project, most experts regard the maintenance phase as the most effort and cost intensive of all phases in the software development life cycle. This is due to the high maintenance effort , time, and resources needed to effectively address issues during software maintenance (maintenance activities). Mismanagement of these efforts can lead to the degradation of software maintainability. Understanding the assessment of the related software processes can help sustain or improve maintainability during these maintenance activities. Recent studies have shown that current software process assessments are expensive, generic, and complex, especially for smaller organizations. In this paper, we investigate an alternative software process assessment approach performed by analyzing fine‐grained processes (micro processes) of maintenance activities. This approach assesses maintenance efforts based on micro processes in relation to their impact on source code. The approach derives maintenance effort from the complexity and duration of micro processes and uses proposed metrics based on program slicing to measure change impact. In this paper, we investigate an alternative software process assessment approach by analysing fine‐grained processes (micro processes) of maintenance activities. At statistically significant levels, results suggest that the level of the maintenance efforts correlates with its impact on source code. Copyright © 2012 John Wiley & Sons, Ltd.