 The QEST model
 Publications on QEST
 The LIME model
 Publications on LIME
 Related Publications
The QEST model
QEST (Quality factor + Economic, Social and Technical dimensions) is a software multidimensional performance measurement model. In the QEST model, the measurement of performance (p) is defined as the integration of an instrumentbased measurement process (expressed in the model by the component RP  Rough Productivity) with a perceptionbased measurement process based on the subjective perception of quality (expressed in the model by the component QF  Quality Factor). The QEST model provides a multidimensional structured shell, which can then be filled according to management objectives for any specific project: it is therefore referred to as an open model. This topology of performance models makes it possible to handle the multiple and distinct viewpoints already discussed, all of which can exist concurrently in any software project.
The basic purpose of the structured shell of the open model is to express performance as the combination of the specific measures (or sets of measures) selected for each of the three dimensions, these values being derived from both an instrumentbased measurement of productivity and a perceptionbased measurement of quality. A threedimensional geometrical representation of a regular tetrahedron was selected as the basis for the model, and is illustrated in Figure 1.
Furthermore:
 the three dimensions (E, S, T) in the space correspond to the corners of the pyramid’s base, and the convergence of the edges to the P vertex, which describes the top performance level;
 when the three sides are of equal length, the solid shape that represents this threedimensional concept is therefore a pyramid with its triangular base and sides of equal length (tetrahedron).
This pyramidtype representation imposes the following constraint: the sides must be equal, and this is achieved through giving equal weights to each of the three different dimensions chosen – and with sides of length exactly equal to 1 (regular tetrahedron); in this way, the dimensions are represented through a normalised value between 0 and 1 for each of them on a ratio scale, for ease of understanding. With this 3D representation it is possible to determine and represent performance considering distinct geometrical concepts (distance, area and volume). In this 3D representation, the ratio between the volume of the lower part of the truncated tetrahedron and the total volume of the tetrahedron represents the normalised performance level of a project being assessed. The geometrical approach permits representation of the measurement of performance in a simple and visual way for immediate impact and optimal understanding. The original selection of the regular tetrahedron was also suggested by the idea that the vertex of the 3D shape represents, from a conceptual viewpoint, the convergence of different viewpoint evaluations into a final, single one. Another important factor to take into account is the use of normalised values in order to give Management greater value readability for taking decisions.
Other key features of the QEST model are:
 Integrated quantitative and qualitative evaluation from three concurrent organisational viewpoints;
 A threedimensional geometrical construction to gather a single SLC phase value for each project;
 The recommendation of using de facto and de jure standards (such as ISO/IEC 9126 standard on Software Product Quality Evaluation).
Currently, the original QEST threedimensional model has been extended to a generic n possible dimensions/perspectives of calculation, using the simplex concept. QEST nD can be therefore used also as a generic ndimensional measurement model, according to the features and advantages above listed.
Another recent developments are about:
its usage for consolidating Balanced Scorecards (BSC) measurement outcomes
as a model for Performance Estimation
Publications on QEST
L.Buglione & A.Abran, A Three Dimensional Software Performance Measurement Model, Atti Conferenza "International Software Benchmarking", Università "La Sapienza"  ISBSG  GUFPI, Roma, Italia, February 12, 1998
L.Buglione & A.Abran, Multidimensional Software Performance Measurement Models: A Tetrahedronbased Design, in "Software Measurement: Current Trends in Research and Practice", R.Dumke/A.Abran (eds.),
Deutscher Universitats Verlag GmbH, ISBN 382446876X, pp. 93107, 1999
L.Buglione & A.Abran, Geometrical and statistical foundations of a threedimensional model of software performance, International Journal of Advances in Engineering Software, Elsevier Science Publisher, Vol. 30 No. 12, December 1999, pp. 913919
L.Buglione & A.Abran, Multidimensionality in Software Performance Measurement: the QEST/LIME models, SSGRR 2001 (2nd International Conference on Advances in
Infrastructure for Electronic Business, Science, and Education on the Internet), L'Aquila, Italy, August 610, 2001
L.Buglione & A.Abran, QEST nD: ndimensional extension and generalisation of a Software Performance Measurement Model, International Journal of Advances in Engineering Software, Elsevier Science Publisher, Vol. 33, No. 1, January 2002, pp.17
A.Abran & L.Buglione, A Multidimensional Performance Model for Consolidating Balanced Scorecards, International Journal of Advances in Engineering Software, Elsevier Science Publisher, Vol. 34, No. 6, June 2003, pp.339349
A.Abran, M.Kunz, R.Dumke & L.Buglione The Prototypical webbased implementation of the QEST model, IWSM2003, in "Investigations in Software Measurement", Proceedings of the 13th International Workshop on Software Measurement (IWSM2003), September 2325, 2003, Montréal (Canada), Shaker Verlag, ISBN 3832218807, pp. 8292
L.Buglione & A.Abran, A Model for Performance Management & Estimation, Proceedings of METRICS 2005, 11^{th} IEEE International Software Metrics Symposium, 1922 September 2005, Como(Italy)
Buglione L. & Abran A., Performance calculation and estimation with QEST/LIME using ISBSG r10 data
, Proceedings of the 5^{th} Software Measurement European Forum (SMEF 2008), Milan (Italy), 2830 May 2008, ISBN 9788870909999, pp. 175192
Buglione L., Damiani E., Frati F., Oltolina S., Ruffatti G.,Improving Quality and Costeffectiveness in Enterprise Software Application Development: an Open, Holistic Approach for Project Monitoring & Control , Proceedings of ICSOB 2011, 2^{nd} International Conference on Software Business, Brussels (Belgium), in B. Regnell, I. van de Weerd, and O. de Troyer (eds.): ICSOB 2011, LNBIP 80, SpringerVerlag Berlin, pp. 125139, 2011, ISBNISSN: 9783642215438
The LIME model
The LIME (LIfecycle MEasurement) model extends the QEST model concepts to a dynamic context, such that the model can be applicable to each step of any topology of SLC selected. For illustrative purposes here only, the LIME model considers a generic 6phase waterfall SLC structure. The intrinsic SLC dynamicity and sequentiality necessarily implies the adoption of a notation to describe the process and its flows. From the various possible notations found in the technical literature, the ETVX (EntryTaskValidationeXit) notation has been chosen. In this notation system, the output of the (n1)^{th} phase represents the input for the n^{th }one; processing produces the n^{th} output, which will be the input for the (n+1)^{th} phase, and so on. It must be noted that the measurement results (I_{1}, ..., I_{6}, O_{1}, ..., O_{6}) can be added since they have been normalised within the QEST model to facilitate an understanding of them and a representation of them in a 3D space. The framework for the LIME model is the following:
The iterative definition, collection and analysis of multidimensional measures at each life cycle phase offers, therefore, the feedback required to make adjustments to the project processes in a timely fashion, both for the next phase and for designing future improvements to the process of the preceding phase. The key features added in the LIME model are:
 Flexibility of distinct relative contributions from the three dimensions (E, S, T) in each phase:
 Flexibility of distinct relative contributions between quantitative and qualitative evaluations in each phase:
 Different sources for QF calculation
 Flexibility in selecting suitable measures and ratios for each SLC phase
Publications on LIME
L.Buglione & A.Abran, LIME: A ThreeDimensional Measurement Model for Lifecycle Project Management, 9th International Workshop on Software Measurement, CIM / Univ. of Magdeburg / COSMIC, September 810, 1999, Mont Tremblant, Québec, Canada
L.Buglione & A.Abran, LIME: A ThreeDimensional Software Performance Measurement Model for Project Management,2nd World Conference on Software Quality, September 2529, 2000, Yokohamaya, Tokyo, Japan
L.Buglione & A.Abran, Multidimensionality in Software Performance Measurement: the QEST/LIME models, SSGRR 2001 (2nd International Conference on Advances in
Infrastructure for Electronic Business, Science, and Education on the Internet), L'Aquila, Italy, August 610, 2001
L.Buglione & A.Abran, A Model for Performance Management & Estimation, Proceedings of METRICS 2005, 11^{th} IEEE International Software Metrics Symposium, 1922 September 2005, Como(Italy)
A.Abran, L.Buglione & D.Girard, RLIME: Improving the Risk dimension in the LIME model, Proceedings of 3WCSQ, 3^{rd} World Conference on Software Quality, 2629 September 2005, Munich (Germany)
Buglione L. & Abran A., Performance calculation and estimation with QEST/LIME using ISBSG r10 data
, Proceedings of the 5^{th} Software Measurement European Forum (SMEF 2008), Milan (Italy), 2830 May 2008, ISBN 9788870909999, pp. 175192
Related Publications
Gotterbarn D., Reducing Software Failures: Addressing the Ethical Risks of the Software Development Lifecycle, Australian Journal of Information Systems (AJIS), Vol.9 No.2, May 2002
Lindholm J., Investigation and Implementation of Support for Balanced Scorecard in an Executive Information System, KTH Royal Institute of Technology, NADA Department, Sweden, Master Thesis, 4 December 2002
Ott A., Pleiten, Pech und Pannen in der Informatik, Seminar, Wintersemester 2001/2002, Fakultät für Informatik, EberhardKarls Universität Tübingen (Germany)
On X. & Peyton L., Visualizing Quality: Issues in Quantifying Results, CUSEC 2004, Montreal (Canada), January 1517 2004
Selection of Papers on Software Measurement by Rebeca Cortazar
M.Ganzha & S.Szejko, Ryzyko etyczne w procesie wytwarzania oprogramowania, eInformatyka.pl
J.Hong, E.Suh, K.Yoo, D.Hong, A Model for Evaluating the Effectiveness of the ASP Service Using Balanced Scorecard, Proceedings of the 9th Pacific Asia Conference on Information Systems (PACIS2005)
Rai Foundation Colleges, Unit III  Lesson 11: Software Project Planning & Design, Rai Courseware, Course of Software Engineering Techniques
K.Khosravi & YG. Guéhéneuc, A Quality Model for Design Pattern, Technical Report, University of Montréal, Summer 2004
J.Momoh & G.Ruhe, A Quality Model for Design Pattern, Proceedings of EuroSPI2005, Industrial Track
Hong J. A Performance System Based on the BSC Approach for Measuring Performance in a Business Environment, POSTECH 2005 Spring Seminar
Amendola LP., Depool T., F., González M. D., Palacios E. Modelo de Implementacion del Cuadro de Mando Integral en una Oficina de Proyectos, PMI Barcelona Chapter (Spain), IX Congreso Internacional De Ingeniería De Proyectos, Málaga (Spain), June 2005
Groff J.E., Pitman M.K., The Balanced Scorecard and Capital Budgeting, American Accounting Association, 2006 Annual Meeting, August 6–9, 2006, Washington, D.C. (USA)
Davila A., Thesis en Calidad de Software, Pontificia Universidad Catolica del Peru, 24 Enero 2006
Nicko M., Cusack B., A Metrics Generation Model for Measuring the Control Objectives of Information Systems Audit, 40^{th} Annual Hawaii International Conference on System Sciences (HICSS'07), p. 235c, 2007
AbuSuleiman A., An Analytical Performance Management Framework Enabling Enterprise Strategy Management, Ph.D. Thesis, University of Texas at Arlington (USA), August 2006
Ganzha M., Multicriterial evaluation of alternative decisions in software development process, ETHICOMP 2005, July 2005
Hong J., Suh E., A Strategic Model for Consolidating BSC Measures Based on the Desirability Function: A Case Study of a Website Company, GESTS Int’l Trans. Computer Science and Engr., Vol.18, No.1, October 2005, pp. 99110
Khosravi K., A Quality Model considering Program Architecture, Ph.D. Thesis, Département d'informatique et de recherche operationnelle Faculté des arts et des sciences, Université de Montréal, August 2005
Tsolas, I., Designing of performance measurement systems at corporate level: Sustainability Balanced Scorecard, 1^{st} conference of Managerial scientists, Conference: Managerial theory and practice  Management and society, University of Athens, October 67, 2005, Athens, Greece
Tawfik1 S.M., AbdElghany M.M. & Green S., A Software Cost Estimation Model Based on Quality Characteristics, MeRep Workshop, 6 November 2007, Palma de Mallorca (Spain)
Theriou N.G., Theriou G.N., Papadopoulos A., The Use of Analytic Hierarchy Process in Integrating The Balanced Scorecard and ActivityBased Costing, Dept. of Business Administration, Technological Educational Institute of Kavala (Greece), Operational Research 4(2), 2004, pp.147165
Salin Monteiro L.F., Definiçao de um Catalogo de Medidas para a Analise de Desempenho de Processo de Software, Dissertaçao de Mestrado, Universidade Catolica de Brasilia (Brazil), 2008
Kalander J., Security management: feedback system requirements and realization, Ph.D. Thesis, Helsinki University of Technology (Finland), December 5 2007
K Khosravi, YG Gueheneuc, A Quality Model for Design Pattern, 2004
M Ganza, S Szejko, Ryzyko etyczne w procesie wytwarzania oprogramowania, eInformatyka.pl, W: „Problemy i metody inzynierii oprogramowania”, WNT 2003, pp. 447454
R AlQutaish, A Abran, A Maturity Model for Software Product Quality, International Journal of Software Engineering and Knowledge Engineering, World Scientific Publishing Company
Lardenoije E.J.H., van Raaij,Arjan E.M., van Weele J., Performance Management Models and Purchasing: Relevance Still Lost, in: Researches in Purchasing and Supply Management, Proceedings of the 14th IPSERA Conference, Archamps, France, March 2023 2005
de Aquino, G.S.; de Lemos Meira, S.R, An Approach to Measure ValueBased Productivity in Software Projects, 9th International Conference on Quality Software (QSIC’09), 2009, pp.383389
de Aquino, G.S.; de Lemos Meira, S.R., Towards Effective Productivity Measurement in Software Projects, 4th International Conference on Software Engineering Advances (ICSEA’09), Sept 20.25 2009, pp.241249
Cohen M.B., Hedonistic pricing models and the valuation of intangible assets, PhD Thesis, Sourthern Cross University, Lismore, NSW, 2009
Hong Yang, Rong Chen, Yaqing Liu, A Metrics Method for Software Architecture Adaptability, Journal of Software, Vol 5, No 10 (2010), 10911098, Oct 2010
last update: September 1, 2012
