An empirical validation of software cost estimation models
Communications of the ACM
ACM SIGSOFT Software Engineering Notes
A recursive introduction to the theory of computation
A recursive introduction to the theory of computation
Why does software cost so much?: and other puzzles of the information age
Why does software cost so much?: and other puzzles of the information age
An introduction to Kolmogorov complexity and its applications (2nd ed.)
An introduction to Kolmogorov complexity and its applications (2nd ed.)
Process assessment considered wasteful
Communications of the ACM
Software project cost schedule estimating: best practices
Software project cost schedule estimating: best practices
Software quality lessons from the quality experts
Handbook of software quality assurance (3rd ed.)
Rapid Development: Taming Wild Software Schedules
Rapid Development: Taming Wild Software Schedules
A Critical Look at Software Capability Evaluations
IEEE Software
Enough About Process: What We Need are Heroes
IEEE Software
Are We Developers Liars or Just Fools?
IEEE Software
Algorithmic complexity of recursive and inductive algorithms
Theoretical Computer Science - Super-recursive algorithms and hypercomputation
Predictive accuracy comparison of fuzzy models for software development effort of small programs
Journal of Systems and Software
What went wrong? A survey of problems in game development
Computers in Entertainment (CIE) - SPECIAL ISSUE: Media Arts and Games
Towards analysis-driven scientific software architecture: The case for abstract data type calculus
Scientific Programming - Complexity in Scalable Computing
Universality, reducibility, and completeness
MCU'07 Proceedings of the 5th international conference on Machines, computations, and universality
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Algorithmic (KCS) complexity results can be interpreted as indicating some limits to software estimation. While these limits are abstract they nevertheless contradict enthusiastic claims occasionally made by commercial software estimation advocates. Specifically, if it is accepted that algorithmic complexity is an appropriate definition of the complexity of a programming project, then claims of purely objective estimation of project complexity, development time, and programmer productivity are necessarily incorrect.