• Save
The Significance of IFPUG in Effort Estimation Base Functionality Types
Upcoming SlideShare
Loading in...5
×
 

The Significance of IFPUG in Effort Estimation Base Functionality Types

on

  • 732 views

This presentation proposes a refined way to improve estimates using a combination of single Function Types from an historical data repository with IFPUG FPA (valid also for any other FSM method) ...

This presentation proposes a refined way to improve estimates using a combination of single Function Types from an historical data repository with IFPUG FPA (valid also for any other FSM method) estimation models

Statistics

Views

Total Views
732
Views on SlideShare
731
Embed Views
1

Actions

Likes
0
Downloads
0
Comments
0

1 Embed 1

http://www.linkedin.com 1

Accessibility

Categories

Upload Details

Uploaded via as Adobe PDF

Usage Rights

© All Rights Reserved

Report content

Flagged as inappropriate Flag as inappropriate
Flag as inappropriate

Select your reason for flagging this presentation as inappropriate.

Cancel
  • Full Name Full Name Comment goes here.
    Are you sure you want to
    Your message goes here
    Processing…
Post Comment
Edit your comment

The Significance of IFPUG in Effort Estimation Base Functionality Types The Significance of IFPUG in Effort Estimation Base Functionality Types Presentation Transcript

  • ISMA 5 – 5° IFPUG International Software BLEKINGE INSTITUTE OF TECHNOLOGY Measurement & Analysis Conference Sao Paulo (Brazil), Sept. 13-15 2010The Significance of IFPUG Base An Empirical Study Functionality Types in Effort Estimation Luigi Buglione, Ph.D. Buglione Proc. Improv. & Measur. Specialist Industry Business Unit Engineering.IT Cigdem Gencel, Ph.D. Gencel Assistant Professor Systems & Software Department Blekinge Institute of Technology (BTH) www.eng.it
  • Engineering At a glance _ The first Italian ICT player _ more than 730 M/€ revenues Research and PA & HC Finance Industry TELCO Utilities Development _ 1000 clients _ 6,300 IT specialists System Int. & Consultancy % 46 70 54 80 80 Outsourcing % 35 10 27 10 Software % 19 20 19 10 20 ERP IT Security ECM Plant Management Managed Operations Broadband & Media System www.eng.it www.eng.it
  • BFC Types Goals of the presentation G1. Help project managers and estimators to obtain better estimates usingthe same historical data G2. Propose a list of filtering criteria helping in obtaining betterhomogeneous clusters for data analysis and process improvements G3. Identify and manage not visible outliers in your own historical data G4. Go into a deeper detail when gathering more granular data in yourhistorical database, that help in consolidating CMMI ML2 goals and achievingfaster ML3 ones with better PALs (Process Asset Libraries) G5. Stimulate improvements in your organization supporting more and moreexperience by quantitative data 3 ISMA5 – Sao Paulo, Sept. 14, 2010 – © 2010 L.Buglione, C.Gencel www.eng.it
  • BFC Types Agenda• Introduction – A FSM History – Estimation Techniques – Top 10 Measurement problems – Estimation and SPI• Related works• Empirical Study – Data Collection – Data Preparation – Statistical Analysis & Results• Conclusions & Prospects• Q&A4 ISMA5 – Sao Paulo, Sept. 14, 2010 – © 2010 L.Buglione, C.Gencel www.eng.it
  • Introduction A FSM HistorySource: FSM webpage: http://www.semq.eu/leng/sizestfsm.htm5 ISMA5 – Sao Paulo, Sept. 14, 2010 – © 2010 L.Buglione, C.Gencel www.eng.it
  • Introduction Estimation TechniquesSource: Briand L., Wieczorek I., Resource Estimation in Software Engineering, ISERNTechnical Report 00-05, International Software Engineering Research Network, 2000, URL:http://isern.iese.de/moodle/ 6 ISMA5 – Sao Paulo, Sept. 14, 2010 – © 2010 L.Buglione, C.Gencel www.eng.it
  • Introduction Top-10 Problems in Measurement1. Betting the Measurement Program on a Single Metric;2. Trying to Find a Single Metric that Solves All Problems and Has No Evils3. The Quest for an Industry Standard Set of Measures4. Not Linking Measures to Behaviour; Failing to Realize that the Measures Are the System5. Assuming that One Set of Measures Will Be Good for "All Time"6. Measuring the Wrong IT Output7. Measuring in Business Terms, but the Wrong Business Terms8. Failure to Quantify in Business Terms; Failure to Plan for Benefits9. Neglecting the Full Range of IT-Related Outcomes10. Lack of Commitment; Treating Measurement As a Non-Value-Added Add-OnSource: Rubin H.A., The Top 10 Mistakes in IT Measurement, IT Metrics Strategies, Vol.II,No.11, November 1996, URL:http://web.archive.org/web/20030119070257/www.cutter.com/benchmark/1996toc.htm 7 ISMA5 – Sao Paulo, Sept. 14, 2010 – © 2010 L.Buglione, C.Gencel www.eng.it
  • Introduction Estimation and SPI (CMMI-DEV, ML2)MA – Measurement & Analysis PP – Project Planning SG1 Establish Planning Data Estimates Measurement Data SG2 Develop a Project Plans Project Plan An agreed-to set of requirements SG3 Obtain Committment to the Plan REQM – Requirement Mgmt PMC – Project Monitoring & Control8 ISMA5 – Sao Paulo, Sept. 14, 2010 – © 2010 L.Buglione, C.Gencel www.eng.it
  • Introduction Estimation and SPI (CMMI-DEV, ML3) n’s izatio d O rgan eeds anSenior Management es s n es proc bjectiv o Organization’s business objectives Training for projects and support OT Org. groups in std process and assets Training Tra i nin g ne ed s Std processes and other assets Std process, work environment std, OPF Org. OPD Org. and other assets Project Mgmt, Process Process Support & Focus Resources and Coordination Definition Improvement Information (e.g. Engineering PAs lessons learned, data, artifacts) Process Improvement proposals; participation in definining, assessing, and deploying processes 9 ISMA5 – Sao Paulo, Sept. 14, 2010 – © 2010 L.Buglione, C.Gencel www.eng.it
  • Introduction Estimation and SPI (CMMI-DEV, ML3 - OPD) Create Org. Make Supporting Process Assets Process Assets SP1.2 Available Lifecycle models Establish lifecycle model description s Org. Standard Processes SP1.4 Establish SP1.1 Org. Meas. Establish Repository Standard Processes Org. Measur. Repository SP1.3 SP1.5 Establish Establish Tailoring Org. PAL Org. Library of Process Doc Criteria & GL SP1.6 Establish Tailoring Guidelines Work Env. Std10 ISMA5 – Sao Paulo, Sept. 14, 2010 – © 2010 L.Buglione, C.Gencel www.eng.it
  • Related Works Analysis on the use of single BFC typesUse more independent variables• when using FSM methods, e.g. use combinations of 2+ BFC types  IFPUG BFC (EI, EO, EQ, ILF, EIF)  COSMIC BFC (E, X, R, W)• Results: increased R2 using the same datasetNW _ Effort = B0 + B1 ( EI ) + B2 ( EO) + B3 ( EQ) + B4 ( ILF ) + B5 ( EIF )Preconditions• Historicize project data at the proper level of granularity. E.g.  FSU at the BFC type level (by frequencies and – eventually – weigthed values)  Effort at the SLC phase and/or by ReqType and/or…  Defects by severity/priority class and/or resolution time by phase, and/or…• Skill people – not only estimators – a bit more on Statistics• Use something more than averages!Source: Gencel C. & Buglione L., Do Different Functionality Types Affect the Relationshipbetween Software Functional Size and Effort?, Proceedings of IWSM/MENSURA 2007, Palmade Mallorca (Spain), November 5-8 2007, pp. 235-246 11 ISMA5 – Sao Paulo, Sept. 14, 2010 – © 2010 L.Buglione, C.Gencel www.eng.it
  • Related Works Analysis on the use of single BFC typesStudy/Year Obs Source FSMM Filters R2 R2 Diff. w/CFP w/BFC %Buglione- 34 ISBSG r10 COSMIC DQR/NewDev 0.7639 0.8919 +16.7 Gencel v2+ (2008) 30 ISBSG r10 COSMIC DQR/Enh 0.7086 0.8755 +23.6 v2+ Bajwa- 24 ISBSG r10 COSMIC DQR/ApplType 0.29 0.78 +64.1 Gencel v2+ (2) (2009) 24 ISBSG r10 COSMIC DQR/ApplType 0.29 0.86 +66.3 v2+ (3) Ferrucci- 15 Company’s COSMIC Web-based 0.824 0.875 +5.82 Gravino- data v2.2 portals (all) Buglione (2010) 8 Company’s COSMIC Web-based 0.910 0.966 +5.79 data v2.2 portals (subset 1) 7 Company’s COSMIC Web-based Inf. 0.792 0.831 +4.69 data v2.2 Utilities (subset 2)12 ISMA5 – Sao Paulo, Sept. 14, 2010 – © 2010 L.Buglione, C.Gencel www.eng.it
  • Empirical Study Data Collection (ISBSG r11, 2009) FSMM No. Projects % of the projects IFPUG 3.799 75% FISMA 496 10% COSMIC 345 7% Others (LOC, Dreger, etc.) 221 4% NESMA 155 3% Mark-II 36 1% Total 5.052 100%13 ISMA5 – Sao Paulo, Sept. 14, 2010 – © 2010 L.Buglione, C.Gencel www.eng.it
  • Empirical Study Data Collection (ISBSG r11, 2009) Entity Attribute Definition Product Count Approach The description of the technique that was used to size the project (e.g. IFPUG, COSMIC, etc.) Product Functional Size The count of unadjusted FP. The unit is based on the measurement method that is used to measure the functional size. Product Application Type The type of the application (e.g. MIS). Project Normalized Work Effort The effort used during the full life cycle. For those projects that have covered less than a complete life cycle effort, this value is an estimate. For those projects covering the full life cycle and those projects whose development life cycle coverage is not known, this value and value of summary work effort is same. Project Development Type This field tells that whether the development is new, enhanced or re-developed Project Business Area Type This identifies the subset within the organisation being addressed by the project. It may be different to the organisation type or the same. (e.g.: Manufacturing, Personnel, Finance). Project Programming The primary language used for the Language Type development: JAVA, C++, PL/1, Natural, Cobol etc.14 ISMA5 – Sao Paulo, Sept. 14, 2010 – © 2010 L.Buglione, C.Gencel www.eng.it
  • Empirical Study Data PreparationStep Attribute Filter Projects Remaining Excluded Projects 0 --- --- --- 5052 1 Count Approach = IFPUG 1,253 3,799 2 Data Quality Rating (DQR) = {A | B} 3,799 3,614 3 Quality Rating for Unadjusted = {A | B} 3,614 2,879 Function Points (UFP) 4 BFC Types = {Not Empty} 1,482 1,397Four subsets derived:ID # Dev Application Type Bus. Type Prog.Lang. projects Type 1 37 NewDev Fin trans. Process/accounting Insurance All 2 14 NewDev Fin trans. Process/accounting Insurance COBOL 3 15 NewDev Fin trans. Process/accounting Insurance Visual Basic 4 16 NewDev Fin trans. Process/accounting Banking COBOL15 ISMA5 – Sao Paulo, Sept. 14, 2010 – © 2010 L.Buglione, C.Gencel www.eng.it
  • Empirical Study Statistical Analysis & Results - UFPA typical elaboration (subset #3) only with UFP… #3 Linear Regression Statistics R 0.817 R Square 0.667 Stand. Error 2911.091 Total Number Of Cases 15ANOVA             d.f. SS MS F p-levelRegression 1. 220,988,529.59 220988529.59 26.08 0.00Residual 13. 110,167,824.81 8474448.06Total 14. 331,156,354.40         Coeff. Std Err LCL UCL t Stat p- H0 (2%) level rejected?Intercept 2149.62 849.57 -102.01 4401.26 2.53 0.03 No Total 3.97 0.78 1.91 6.03 5.11 0.00 Yes (IFPUG FP)T (2%) 2.65            16 ISMA5 – Sao Paulo, Sept. 14, 2010 – © 2010 L.Buglione, C.Gencel www.eng.it
  • Empirical Study Statistical Analysis & Results – BFC+..and applying more BFCs Linear Regression Statistics R 0.932 R Square 0.868 Stand. Error 2205.569 Total Number Of Cases 15ANOVA             d.f. SS MS F p-levelRegression 5. 287375530.43 57475106.09 11.82 0.00Residual 9. 43780823.97 4864536.00Total 14. 331156354.40      17 ISMA5 – Sao Paulo, Sept. 14, 2010 – © 2010 L.Buglione, C.Gencel www.eng.it
  • Empirical Study Statistical Analysis & Results – BFC+..and applying more BFCs (…next)   Coeff. Std LCL UCL t Stat p-level H0 (2%) Error rejected? Intercept 2076.14 878.79 -403.31 4555.59 2.36 0.04 No EI -14.74 39.13 -125.16 95.67 -0.38 0.72 No EO 4.67 36.98 -99.67 109.01 0.13 0.90 No EQ 26.25 9.81 -1.44 53.93 2.67 0.03 Yes ILF -24.26 12.58 -59.76 11.23 -1.93 0.09 No EIF 34.85 14.23 -5.29 74.99 2.45 0.04 Yes T (2%) 2.90            18 ISMA5 – Sao Paulo, Sept. 14, 2010 – © 2010 L.Buglione, C.Gencel www.eng.it
  • Empirical Study Statistical Analysis & ResultsSummary Data Subset # prj R2 Is Total FP R2 w/FP Diff% Which BFC w/Total significant? for each (R2) Types are FP BFC Type significant? #1 37 0.290 Yes 0.369 +21% No #2 14 0.057 No 0.838 +93% Yes (ILF) #3 15 0.667 Yes 0.868 +23% Yes (EQ, EIF) #4 16 0.720 Yes 0.893 +19% Yes (EO)% distribution of BFC types by value Data set # points EI EO EQ ILF EIF Subset1 37 16.9% 24.6% 19.3% 21.7% 17.6% Subset2 14 19.8% 39.0% 6.3% 14.4% 20.6% Subset3 15 17.0% 21.6% 22.8% 23.4% 15.3% Subset4 16 18.7% 31.0% 11.4% 27.7% 11.2%19 ISMA5 – Sao Paulo, Sept. 14, 2010 – © 2010 L.Buglione, C.Gencel www.eng.it
  • BFC Types Conclusions & Perspectives• FSM Methods  Born with the goal to provide more objectivity in sizing FUR for a software system  The IFPUG method has the heritage of the Albrecht’s FPA and evolves it from 1986  Current version is v4.3.1 (Jan 2010) and is also an ISO standard (20926:2009)  Several methods have arisen and share common principles and background (ISO 14143-x)• BFC Types  Each FSM method has a series of basic countable elements contributing to the final fsu value, generically called by ISO “BFC”  IFPUG FPA has 5 BFC: EI, EO, EQ, ILF, EIF  Regression analysis with ANOVA Sizing & Estimation issues  R2 values increased in 3 out of 4 cases (from +19% till +93%)  Programming language (no set in subset #1) can impact in absolute terms on predictability Some lessons learned  Positive Effects: using that approach yet at lower maturity levels (e.g. ML2) can improve significantly estimates, helping in saving resources to be reinvested in other project activities, anticipating also the achievement of ML3 concepts (e.g. PAL)  Precondition: gather historical FSM data at that level of granularity Precondition  …let’s remember when estimating anyway that any fsu is a product size for software FURs (and not a project size)  deal with NFR and their impact on the overall project effort within the defined project scope20 ISMA5 – Sao Paulo, Sept. 14, 2010 – © 2010 L.Buglione, C.Gencel www.eng.it
  • BFC Types Q&A Obrigado pela sua atenção! Thanks for your attention!21 ISMA5 – Sao Paulo, Sept. 14, 2010 – © 2010 L.Buglione, C.Gencel www.eng.it
  • Thanks for your Attention ! We care of your problems and we have in mind a solution Luigi Buglione Cigdem Gencel Industry, Services & Infrastructures Blekinge Institute of Technology Via R.Morandi 32 Tel. +39-06.8307.4472 SE-371 79 Karlskrona Tel. +46 -455-385736 00148 Roma Fax +39-06.8307.4200 Sweden Fax +46 -455 38 50 57 Cell. +39 -335.1214813 www.eng.it luigi.buglione@eng.it www.bth.se cigdem.gencel@bth.se22 ISMA5 – Sao Paulo, Sept. 14, 2010 – © 2010 L.Buglione, C.Gencel www.eng.it