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Cost estimation in software engineering is typically concerned with the financial spend on the effort to develop and test the software, this can also include requirements review, maintenance, training, managing and buying extra equipment, servers and software. Many methods have been developed for estimating software costs for a given project.
Software researchers and practitioners have been addressing the problems of effort estimation for software development projects since at least the 1960s; see, e.g., work by Farr [8] [9] and Nelson. [10] Most of the research has focused on the construction of formal software effort estimation models.
Because software, unlike a major civil engineering construction project, is often easy and cheap to change after it has been constructed, a piece of custom software that fails to deliver on its objectives may sometimes be modified over time in such a way that it later succeeds—and/or business processes or end-user mindsets may change to accommodate the software.
SEER for Software (SEER-SEM) is composed of a group of models working together to provide estimates of effort, duration, staffing, and defects. These models can be briefly described by the questions they answer: Sizing. How large is the software project being estimated (Lines of Code, Function Points, Use Cases, etc.) Technology.
The constructive cost model was developed by Barry W. Boehm in the late 1970s [1] and published in Boehm's 1981 book Software Engineering Economics [2] as a model for estimating effort, cost, and schedule for software projects. It drew on a study of 63 projects at TRW Aerospace where
These topics are more concerned, typically, with estimating the effort of software engineering, rather than the actual execution of it. Pages in category "Software engineering costs" The following 20 pages are in this category, out of 20 total.
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The Putnam model is an empirical software effort estimation model [1] created by Lawrence H. Putnam in 1978. Measurements of a software project is collected (e.g., effort in man-years, elapsed time, and lines of code) and an equation fitted to the data using regression analysis .