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Software Estimation
An Introduction


Prof. David Bernstein
James Madison University

Computer Science Department
bernstdh@jmu.edu

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Motivation
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  • Some Common Planning Tasks:
    • Scheduling
    • Budgeting
  • Required Information:
    • Time estimates (perhaps by task)
    • Cost estimates
  • Some Perspective (Standish, 2001; Kidder 1981)
    • 63% of successful software development projects are late
    • 45% of successful software development projects are over budget
Nerd Humor
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http://imgs.xkcd.com/comics/estimating_time.png
(Courtesy of xkcd)
Using Historical Data
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  • Scope:
    • Industry-standard vs. organization-specific
  • Nature of the Data:
    • Qualitative (small, medium, large) vs. quantitative (LOC or FP)
  • Modeling Technique:
    • Formal (e.g., use regression analysis to estimate parameters of the model from the data) vs. informal (e.g., identify rules-of-thumb)
An Example - Organization-Specific, Quantitative, Informal
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  • Background Information:
    • Function points for earlier products
    • A rule-of-thumb about organization-specific productivity in function points per person-months (e.g., 5 FP/pm)
    • Labor cost in dollars per person-month (e.g., $12,000/pm)
  • Information about the Product:
    • 425 FPs
  • Constructing a Point Estimate:
    • Effort: \(E = 425 / 5 = 85\)pm
    • Cost: \(C = 85 \cdot 12000 = 1020000\)dollars
An Example - Industry-Standard, Quantitative, Formal
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  • KLOC-Based (\(L\)) Log-Linear:
    • Walston and Felix (1977): \(E = 5.2 L^{0.91}\)
    • Basili and Freburger (1981): \(E = 1.38 L^{0.93}\)
    • Boehm (1981): \(E = 3.2 L^{1.05}\)
  • FP-Based (\(F\)) Linear:
    • Albrecht and Gaffney (1983): \(E = -91.4 + 0.255 F\)
    • Kemerer (1987): \(E = -37.0 + 0.96 F\)
    • (Note that the negative \(y\)-intercept means that these models are not appropriate for small values of \(F\).)
An Example - Organization-Specific, Qualitative, Formal
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  • Data Collection (Humphrey, 1995):
    • Classify features from other products as very small, small, medium, large, and very large
    • Collect data from other products on LOC per feature (if done correctly, categories should vary by at least a factor of 2)
  • Estimation:
    • Classify required features
    • Count the features in each classification
    • Multiply
    • Add
Some Common Models
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  • The Software Equation:
    • \(E\) (effort) is a function of \(t\) (project duration) and \(L\) (KLOC)
  • COCOMO II:
    • \(E\) is a function of \(L\), \(F\) (function points), or object points
  • International Software Benchmarking Standards Group:
    • \(E\) is a function of \(F\) and \(N\) (team size) with specific parameters for different physical architectures and languages
The Software Equation (Putnam and Meyers, 1992)
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  • Additional Notation:
    • \(t\) denotes the project duration
    • \(B\) denotes a "special skills factor" (\(B\) is 0.16 for products with fewer than 15 KLOC and increases to 0.39 for products with more than 70 KLOC)
    • \(p\) denotes a "productivity factor" that reflects the process and practices, experience, and product complexity (e.g., 2000 for real-time embedded software, 12000 for scientific software)
  • The Two-Variable (\(L\) and \(t\)) Model:
    • \(E = \frac{L \cdot B^{1/3}}{p^3} \cdot \frac{1}{t^4} \)
  • The One variable Model:
    • \(t = 8.14 \frac{L}{p^{0.43}}\)
    • \(E = 180 B \left(\frac{t}{12}\right)^{3}\)
COCOMO II - Constructive Cost Model (Boehm, 1981/2000)
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  • Collection of Models:
    • Pre-Requirements (Application Composition)
    • Stabilized Requirements (Early Design)
    • Construction (Post-Architecture)
  • Alternative Size Measures:
    • Lines of Code
    • Function Points
    • Object Points
  • Factors to Consider:
    • Scale factors
    • Product factors
    • Platform factors
    • Personnel factors
    • Project factors
COCOMO II (cont.)
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  • Nominal Effort:
    • \(E = 2.94 \cdot L^\beta \cdot \prod_{i=1}^{16} W_i\)
    • where \(W_i\) is an effort multiplier, \(\beta = 0.91 + 0.01 \cdot \sum_{j=1}^{5} \Psi_j\), and \(\Psi_j\) is a scale factor
  • The Scale Factors (\(\Psi_j\)):
    • images/COCOMO_scale.gif
  • Effort Multipliers (\(W_i\)):
    • images/COCOMO_effort.gif
International Software Benchmarking Standards Group (2005)
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  • Additional Notation:
    • \(N\) denotes the (maximum) team size
  • A General Model:
    • \(E = 0.512 \cdot F^{0.392} \cdot N^{0.791}\)
  • Other Models:
    • They have estimated the parameters of this model for products for mainframes, mid-range systems, desktops
    • They have estimated the parameters of this model for different kinds of languages
There's Always More to Learn
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