Maintainability Prediction and Metrics
ROLL NO 17
ROLL NO 20
OUTLINES
1. Introduction
2. Systematic review
2.1. Research questions
2.2. Search strategy used for primary studies
2.3. Inclusion and exclusion criteria for study
Selection
3. Results
4. Discussion
5. Conclusion
6. References
1.Introduction
• Software maintainability, the ease with which a software system can be modified ,it is an important software quality attribute.
• Intrinsically associated with this quality attribute that represent the majority of the costs of a
Software Development Life-Cycle (SDLC)
• Therefore, the maintainability of a software system can significantly impact software costs.
• It is important to be able to forecast a software system’s maintainability so to effectively manage costs. • Research into software maintainability prediction includes proposing and validating maintainability predictors Maintainability: Software maintainability is
defined as “the ease with which a software system or component can be modified to correct faults, improve performance or adapt to a change environment Maintenance: Software maintenance is
defined as “the process of modifying a software system or component after delivery to correct faults, improve performance or other attributes,
or adapt to a changed environment
From the definitions it is clear that maintenance is the process performed as part of the SDLC whereas maintainability is the quality attribute associated with the software product.
Maintenance vs. maintainability represent process vs. quality attribute and their
,
predictions are called process cost prediction vs. quality attribute measurement, respectively.
2.SYSTEMATIC REVIEW: An SR provides the means to identify, evaluate and interpret all available research relevant to a particular research question, topic area, and phenomenon of interest
.
2.1. Research questions
Specifying the right research question is very important for an SR in
References: Y. Ahn, J. Suh, S. Kim, and H. Kim, 2003, “The Software Maintenance Project Effort Estimation Model Based on Function Points”, J Softw Maint Evol, 15, 2, 2003, pp. 71 –85. R. K. Bandi, V. K. Vaishnavi, and D. E. Turk, “Predicting Maintenance Performance Using ObjectOriented Design Complexity Metrics”, IEEE T Software Eng, 29, 1, Jan. 2003, pp. 77 – 87. I.K. Crombie, The Pocket Guide to Appraisal, BMJ Books, 1996.