Software development effort estimation: Difference between revisions

Revision as of 11:25, 16 August 2023

Revision as of 16:14, 22 August 2023

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}}</ref> and Nelson.<ref>Nelson, E. A. (1966). Management Handbook for the Estimation of Computer Programming Costs. AD-A648750, Systems Development Corp.</ref>

Most of the research has focused on the construction of formal software effort estimation models. The early models were typically based on [[regression analysis]] or mathematically derived from theories from other domains. Since then a high number of model building approaches have been evaluated, such as approaches founded on [[case-based reasoning]], classification and [[regression trees]], [[simulation]], [[neural networks]], [[Bayesian statistics]], [[lexical analysis]] of requirement specifications, [[genetic programming]], [[linear programming]], economic production models, [[soft computing]], [[fuzzy logic]] modeling, statistical [[bootstrapping]], and combinations of two or more of these models. The perhaps most common estimation methods today are the parametric estimation models [[COCOMO]], [[SEER-SEM]] and SLIM. They have their basis in estimation research conducted in the 1970s and 1980s and are since then updated with new calibration data, with the last major release being COCOMO II in the year 2000. The estimation approaches based on functionality-based size measures, e.g., [[function points]], is also based on research conducted in the 1970s and 1980s, but are re-calibrated with modified size measures and different counting approaches, such as the [[Use Case Points|use case points]]<ref>{{cite journalbook

| author = Anda, B. Angelvik, E. Ribu, K.

| title = ImprovingProduct EstimationFocused PracticesSoftware byProcess Applying Use Case ModelsImprovement

| chapter = Improving Estimation Practices by Applying Use Case Models

| doi=10.1007/3-540-36209-6_32

| journalseries = Lecture Notes in Computer Science

| doi=10.1007/3-540-36209-6_32

| year=2002

| journal=Lecture Notes in Computer Science

| volume = 2559

| pages=383–397

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==Psychological issues==

There are many psychological factors potentially explaining the strong tendency towards over-optimistic effort estimates. These factors are essential to consider even when using formal estimation models, because much of the input to these models is judgment-based. Factors that have been demonstrated to be important are [[wishful thinking]], [[Anchoring (cognitive bias)|anchoring]], [[planning fallacy]] and [[cognitive dissonance]].<ref>{{cite webjournal

| author = Jørgensen, M. Grimstad, S.

| title = How to Avoid Impact from Irrelevant and Misleading Information When Estimating Software Development Effort

| journal = IEEE Software

| url = https://www.simula.no/publications/avoiding-irrelevant-and-misleading-information-when-estimating-development-effort }}

| date = 2008

| pages = 78–83

| url = https://www.simula.no/publications/avoiding-irrelevant-and-misleading-information-when-estimating-development-effort }}

</ref>

* It's easy to estimate what is known.