Software cost estimation
TL;DR: An overview of the state of the art of software cost estimation (SCE), and what can software project management expect from SCE models, how accurate are estimations which are made using these kind of models, and what are the pros and cons of cost estimation models.
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Abstract: The paper gives an overview of the state of the art of software cost estimation (SCE). The main questions to be answered in the paper are: (1) What are the reasons for overruns of budgets and planned durations? (2) What are the prerequisites for estimating? (3) How can software development effort be estimated? (4) What can software project management expect from SCE models, how accurate are estimations which are made using these kind of models, and what are the pros and cons of cost estimation models?
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Citations
A Systematic Review of Software Development Cost Estimation Studies
Magne Jørgensen,Martin Shepperd +1 more
TL;DR: A systematic review of previous work identifies 304 software cost estimation papers in 76 journals and classifies the papers according to research topic, estimation approach, research approach, study context and data set to provide a basis for the improvement of software-estimation research.
A review of studies on expert estimation of software development effort
TL;DR: An extensive review of studies related to expert estimation of software development effort suggests that expert estimation is the most frequently applied estimation strategy for software projects, that there is no substantial evidence in favour of use of estimation models, and that there are situations where the authors can expect expert estimates to be more accurate than formal estimation models.
700
Systematic literature review of machine learning based software development effort estimation models
TL;DR: A systematic literature review of empirical studies on ML model published in the last two decades finds that eight types of ML techniques have been employed in SDEE models, and overall speaking, the estimation accuracy of these ML models is close to the acceptable level and is better than that of non-ML models.
543
A review of software surveys on software effort estimation
Kjetil Moløkken,Magne Jørgensen +1 more
- 30 Sep 2003
TL;DR: Estimation knowledge is summarized through a review of surveys on software effort estimation that most projects (60-80%) encounter effort and/or schedule overruns and there is no evidence that formal estimation models lead to more accurate estimates.
448
References
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Software Engineering Economics
Barry Boehm
- 01 Jan 1981
TL;DR: In this article, the authors provide an overview of economic analysis techniques and their applicability to software engineering and management, including the major estimation techniques available, the state of the art in algorithmic cost models, and the outstanding research issues in software cost estimation.
6K
Software engineering economics
Barry Boehm
- 04 Oct 1993
TL;DR: In this paper, the authors provide an overview of economic analysis techniques and their applicability to software engineering and management, including the major estimation techniques available, the state of the art in algorithmic cost models, and the outstanding research issues in software cost estimation.
5.9K
Software Function, Source Lines of Code, and Development Effort Prediction: A Software Science Validation
A.J. Albrecht,J.E. Gaffney +1 more
TL;DR: In this paper, the equivalence between Albrecht's external input/output data flow representative of a program (the function points" metric) and Halstead's [2] "software science" or "software linguistics" model of a programming program as well as the "soft content" variation of Halsteads model suggested by Gaffney [7] was demonstrated.
1.6K