| dc.contributor.author | Mukunga, Catherine W. | |
| dc.contributor.author | Ndia, John G. | |
| dc.contributor.author | Wambugu, Geoffrey M. | |
| dc.date.accessioned | 2023-09-26T14:37:06Z | |
| dc.date.available | 2023-09-26T14:37:06Z | |
| dc.date.issued | 2022 | |
| dc.identifier.citation | International Journal of Software Engineering (IJSE), Volume (10) : Issue (2) : 2022 22 ISSN: 2180-1320, https://www.cscjournals.org/journals/IJSE/description.php | en_US |
| dc.identifier.issn | 2180-1320 | |
| dc.identifier.uri | https://www.cscjournals.org/manuscript//Journals/IJSE/Volume10/Issue2/IJSE-185.pdf | |
| dc.identifier.uri | http://hdl.handle.net/123456789/6402 | |
| dc.description.abstract | One of the primary areas of software project management is cost estimation. The cost estimation problem remains unsolved today because of the ineffective cost estimation techniques which are unsuitable for handling current development methods. Software maintenance costs can be estimated using a variety of models such as the Construction Cost Model (COCOMO), Software Life Cycle Management (SLIM), Software maintenance project effort estimation model and others but more work needs to be done in developing models that can accommodate programs from new programming paradigms. The primary objective of this research was to identify factors affecting the software maintenance cost of python programs and rank them according to their relevance. To achieve the objective, a literature review study was done to identify factors that influence software maintenance costs followed by an expert opinion survey to ascertain which of the factors were relevant for Python programs. Fifty two (52) Python developers and project managers were identified using snowballing technique and asked to rate the cost drivers in order of relevance using a five point scale. Descriptive statistics were used to carry out the analysis of the results. The results indicated that all the eighteen (18) factors affected the maintenance cost of Python programs. The factors were ranked based on the percentage mean of frequencies. Six additional factors were also identified by the experts and ranked. The factors will be considered as input parameters for a cost estimation model to be developed in the near future for estimating the cost of maintaining python programs. | en_US |
| dc.language.iso | en | en_US |
| dc.subject | Software Maintenance, Cost Drivers, Expert Opinion, Cost Estimation. | en_US |
| dc.title | Factors Affecting Software Maintenance Cost of Python Programs | en_US |
| dc.type | Article | en_US |
