Approach to practical COTS component customization processes for office software

Summary

The paper presents a practical example of customization of Commercial Off-The-Shelf (COTS) components office software for a given decision problem. The COTS office software evaluation and customization process is difficult due to the large number of existing products and different functionalities. The literature analysis identifies a number of methodologies that support COTS evaluation and customization processes. An adaptation of COTS methodology for Multi-Criteria Decision Analysis (MCDA) provides a ranking of alternatives including decision-maker preferences. Based on this, a decision-maker can make a reasonable choice and select the most suitable office software.

Keywords: COTS, office software, MCDA, Promethee method 1. Introduction

The growing popularity of Commercial Off-The-Shelf (COTS) components and the large number available in the marketplace causes data and information redundancy for a decision-maker. It is worth emphasizing that the knowledge about them is relatively low. Another problem is the COTS customization process. A decision-maker has to review a long list of COTS products to find a set of solutions that fulfil pre-defined requirements. However, this does not guarantee a sound choice.

The choice of appropriate office software from any number of available solutions is one of the most important issues for a company. It is worth noting that there are many differences between office software products available on the marketplace. The most popular solutions that support the office sector are COTS and OSS (Open Source Software) products. Apart from traditional office software, the increasing role of web-based office solutions (e.g. MS Office 365) has been observed.

The general aim of this paper is to present a practical example of COTS office software customization for a given decision problem. The literature analysis identifies a number of methodologies that support the COTS evaluation and customization processes. Most of them are based on the MCDA approach (e.g. IusWare [14], PORE [9], SCARLET [10]). The analysis of the decision situation context suggests the Promethee method as the best approach to a given decision problem. The general aim of application of the Promethee method is to evaluate several possible alternatives according to the multiple sets of criteria and identify the best possible solution. Next, the Promethee method was adopted for building a ranking of alternatives of analyzed MS Office 365 solution on the basis of decision-maker preferences.

2. COTS products

The term ‘COTS’ refers to a wide range of products. The COTS market offers a wide range of software components supporting the enterprise functions in different domains (e.g. operating systems, database management systems, antivirus spyware, e-mail packages, mobile operating systems etc. – Fig. 1).

Fig. 1. Exemplary types of COTS products Source: own elaboration.

Based on the literature research, COTS is described as a term with broad coverage [1, 3, 7, 12]. COTS products are defined as ready-made products. COTS are offered by a vendor, who has total control and who retains the intellectual property rights [3, 13]. The customers have no control over specifications, schedule, source code and evolution. COTS products are available in multiple, identical copies [3, 13]. According to the COTS definition, it is possible to classify the office software as a COTS product. Hence, (COTS) office software can be classified as product available in many identical or similar copies. The entirely vendor-controlled development disables any user to alternate the source code. Moreover, COTS office software can be integrated with many different systems (e.g. MS Office).

It is worth noting that different types of software components on the marketplace exist. It is a common view that the most popular are COTS components, but OSS (Open Source Software) components play an important role as well. Based on the definition, OSS is a type of software that is freely redistributable. What is more, an OSS user is permitted to access and modify the source code [2, 8]. All changes to the code must be made freely available (e.g. Open Office). In the literature, COTS and OSS components are very often defined as OTS (Off-The-Shelf) components. The OTS market is still developing, offering some new OTS systems and reusing existing solutions [1].

3. The analysis of selected COTS office software

There are many differences between COTS office software products available in the marketplace both in terms of the functionalities and the economical aspects. On the basis of the available characteristics of office software products, the ontology for office software was created. The ontology was built using the Protégé application (http://www.semanticweb.org/ ontologies/2012/9/Ontology1350845481563.owl). The language supporting building the ontology is OWL (Ontology Web Language). It is supposed that a decision-maker is looking for office software that can be applied as web-based office software and that the producer is Microsoft. The application of office software ontology (Fig. 2) provides a set of results (MS Office 365 email, MS Office 365 P1, MS Office 365 E1, MS Office 365 E2, MS Office 365 E3, MS Office 365 E4).

Fig. 2. An example of the ontology for office software application – selected MS Office 365 In this paper, the analysis is concentrated on the group of office products provided by Microsoft. Apart from traditional office software, Microsoft offers MS Office 365 products, bringing together several features, otherwise not available in traditional office software (e.g. file sharing, web conferencing, managing projects, mobility etc.). Next, six MS Office 365 products were selected. On the basis of the information provided by a vendor, the specified analysis of selected MS Office 365 software was presented in Table 1. The analysis encompasses the following solutions: MS Office 365 email, MS Office 365 P1, MS Office 365 E1, MS Office 365 E2, MS Office 365 E3, MS Office 365 E4.

Table 1. The analysis of selected MS Office 365 software Type of of-fice software MS Office 365 email MS Office 365 P1 MS Office 365 E1 MS Office 365 E2 MS Office 365 E3 MS Office 365 E4 Criteria: Application area Email Small business Midsize businesses and enterprises Midsize businesses and enterprises Midsize businesses and enterprises Midsize businesses and enterprises Cost 3.57 € 5.25 € 7.25 € 12.50 € 19.00 € 20.75 € User maximum 50 000+ 50 50 000+ 50 000+ 50 000+ 50 000+ Email inbox size 25GB 25GB 25GB 25GB 25GB 25GB Included drive storage 25GB 25GB 25GB 25GB 25GB 25GB 24/7 customer suport

yes - yes yes yes yes

Create and edit Word, PowerPoint, Excel and OneNote files online

no yes view only yes yes yes

Intranet site for your team 0 1 300 sub-sites 300 sub-sites 300 sub-sites 300 sub-sites Configurable anti-spam filtering

yes - yes yes yes yes

Email archiving capabilities, 'legal hold' and unlimited email storage - - - - yes yes Enterprise voice capabilities - - - yes

Source: own elaboration on basis of: http://www.microsoft.com/pl-pl/office365/office-online-ser-vices.aspx.

4. Approach to practical COTS component customization processes for office software The existence of repeatable and organized methodologies for software evaluation enhances the entire decision-making process of software selection and alleviates eventual negative consequences. The literature analysis identifies a number of methodologies that support COTS evaluation and customization processes. Most of them are based on the MCDA approach (e.g. IusWare [14], PORE [9], SCARLET [10] etc.). The analysis of the decision situation context suggests the Promethee method as the best approach to a given decision problem. A specified description of the Promethee method is available in [4, 5, 6,11]. The general aim of application of the Promethee method is to evaluate several possible alternatives according to multiple sets of criteria and identify the best possible solution. Furthermore, the ranking of possible alternatives is provided.

The case study presents a practical example of selection COTS office software from MS Office available versions. The case study encompasses the following steps: (1) defining a set of criteria, (2) defining weights for each of criteria (eigenvector) using AHP method (3) using the Promethee method to define a ranking of alternatives (4) selection the most preferable MS Office 365 from the 6 versions available, including decision-maker preferences.

The case study encompasses an analysis of 6 solutions (MS Office 365 email, MS Office 365 P1, MS Office 365 E1, MS Office 365 E2, MS Office 365 E3, MS Office 365 E4). The specified analysis of the selected COTS office solutions is presented in Table X. On the basis of the available characteristics (http:), 10 criteria were defined: (C1) cost, (C2) user maximum, (C3) inbox size, (C4) included drive storage, (C5) 24/7 customer support, (C6) email, calendar, docs and team sites/Create and edit Word, PowerPoint, Excel and OneNote files online, (C7) Intranet site for your team, (C8) configurable anti-spam filtering, (C9) email archiving capabilities, 'legal hold' and unlimited email storage, (C10) enterprise voice capabilities. Application of the AHP method allows one to indicate the weights for each of the analyzed criteria (eigenvector) [15]. These weights reflect the preferences pre-defined by a decision-maker. On the basis of that, the following weights were defined (Table 2).

Table 2. Computed criteria weights based on AHP method (eigenvector).

C1 C2 C3 C4 C5 C6 C7 C8 C9 C10

0.14 0.11 0.07 0.06 0.08 0.26 0.08 0.08 0.06 0.06 The Promethee diagram (Fig. 3) presents all of the analyzed MS Office 365 products (MS Office 365 email, MS Office 365 P1, MS Office 365 E1, MS Office 365 E2, MS Office 365 E3, MS Office 365 E4). It shows a set of pre-defined values for each of the analyzed criteria including preferences defined by a decision-maker, preference thresholds and indifference thresholds. Only the cost criterion (C1) should be minimized. Other criteria (C2-C10) should be maximized.

Fig. 3. Promethee general diagram

On the basis of obtaining results, the preference flows (positive (Phi+), negative (Phi-) and net to (Phi)) were calculated for each alternative. The positive flow expresses how much an alternative is dominating the other ones, and the negative flow shows how much the others have dominated it. The analysis of positive preference flow results informs us that the best solution is MS Office 365 email. If the economical aspect (cost) is excluded, the best scores have 3 solutions: MS Office 365 E2, MS Office 365 E3 and MS Office E4 (Table 3).

Table 3. Preference flows (a) for all of analyzed criteria (b) with the exclusion of the economical aspect (a)

Action Phi Phi+ Phi- MS Office 365 email 0.0979 0.1612 0.0633 MS Office 365 P1 0.0422 0.1333 0.0911 MS Office 365 E2 0.0258 0.1093 0.0835 MS Office 365 E3 -0.0298 0.0815 0.1113 MS Office 365 E1 -0.0507 0.1151 0.1658 MS Office 365 E4 -0.0855 0.0537 0.1391 (b)

Action Phi Phi+ Phi- MS Office 365 E2 0.0623 0.0623 0.0000 MS Office 365 E3 0.0623 0.0623 0.0000 MS Office 365 E4 0.0623 0.0623 0.0000 MS Office 365 email -0.0479 0.0256 0.0735 MS Office 365 P1 -0.0479 0.0256 0.0735 MS Office 365 E1 -0.0912 0.0367 0.1279 Figure 3 illustrates a graphical presentation of the Promethee II complete ranking (for all criteria and excluding the economical aspect). At the bottom, the Promethee II complete ranking is MS Office 365 E4 (on the left side of Fig. 4), but when the economical criterion is not considered, the

worst result is MS Office 365 E1 (on the right side of Fig. 3). In the first case, three solutions have negative scores (MS Office E3, MS Office 365 E1, MS Office E4). A different situation is when the cost is not visible: negative scores have (other) alternatives: MS Office 365 email, MS Office 365 P1 and MS Office 365 E1. It is worth noting that MS Office email has the best score in the first case.

(a) (b)

Fig. 4. Promethee II complete ranking (a) for all of analyzed criteria (b) with the exclusion of the economical aspect

Another figure (Fig. 5) presents the Promethee Diamond ranking. The Promethee Diamond is an alternative two-dimensional joint representation of both Promethee I and Promethee II rankings. The square presented in Figure 5 corresponds to the preference flows (Phi+ and Phi-) plane where each of the analyzed MS Office solutions is represented by a point. The plane is angled 45° so that the vertical dimension gives the net to preference flow (Phi).

(a) (b)

Fig. 5. Promethee diamond ranking (a) for all of analyzed criteria (b) exclusion of the economical aspect

The Promethee-Gaia visual analysis presents a multidimensional analysis of a decision problem of selection the most preferable MS Office 365 (Fig. 6). A number of dimensions determine a number of criteria. A mathematical method called the ‘Principal Components Analysis’ is used to reduce the number of dimensions while minimizing the loss of information. As a next step, three dimensions are computed: U, V and W. The U dimension determines the maximum possible quantity of information. Next, the V dimension provides the maximum additional information orthogonal to U. The last dimension, W, contains the maximum additional information orthogonal to both U and V. The best possible view is the U-V view, which gathers 97.8% of information (quality level) in the first case including all criteria and 100% of information (quality level) when the economical aspect is excluded.

(a) (b)

Fig. 6. Promethee-GAIA Visual analysis (a) for all of analyzed criteria (b) exclusion of the economical aspect

Figure 7 presents an example of the visual stability intervals for the cost criterion. It provides the information on how the net value changes for each analyzed MS Office 365 when the weight of the criterion is modified.

On the basis of the presented table 3(a) and figures: 4-6(a) and 7, the most preferable solution for a decision-maker is MS Office 365 email. It is worth noting that MS Office 365 email is not the best solution with respect to the offered functionalities of Office software. Thus, the second analysis (Table 3(b) and Figures: 3–5(b)) excludes the economical aspect from the decision process. In this case, it can be seen that the most preferable solutions with maximal usability for a decision-maker are: MS Office 365 E2, MS Office 365 E3, MS Office 365 E4.

5. Conclusion

In this paper, a practical example of the MS Office software customization process was presented with respect to the individual decision-maker preferences. Based on the analysis of COTS product definitions, it was possible to define MS Office 365 software as a type of COTS software. Next, the adaptation of the selected method (based on MCDA) supporting COTS evaluation and customization was possible. The evaluation process provides a set of alternatives on the basis of decision-maker preferences. On the basis of experimental research, it can be seen that MS Office 365 enables a wide spectrum of adaptation possibilities for the individual preferences of a decision-maker and an end-user. However, proper evaluation and selection of the most suitable version of MS Office software requires construction and exploitation of a decision model. Although the applied form of a decision model is available for selection, the Promethee method is the suggested technique. Bibliography

[1] Ayala C., Franch X., Assessing What Information Quality Means in OTS Selection References 186 Processes, International Conference on Composite-Based Software Systems (ICCBSS 2008), IEEE Society Press, 2008.

[2] Ayala C., Sorensen C.F., Conradi R., Franch X., Li J., Open Source Collaboration for Forresting Off-The-Shelf Components Selection, [w:] Open Source Development, Adoption and Innovation, IFIP International Federation for Information Processing, Vol. 234/2007, 2007, pp. 7–30.

[3] Ayala C., Systematic Construction of Goal-Oriented COTS Taxonomies, In Proceedings of the 3rd Doctoral Consortium at the 18th Conference on Advanced Information Systems Engineering (CAISE 2006), 5–9 June 2006, Luxembourg.

[4] Brans J.P, Mareschal B.: Promethee Methods, [in]: Multiple Criteria Decision Analysis: State of the Art, J. Figueira, S. Greco, M. Ehrgott (ed.), Springer, 2005.

[5] Brans J.P., Mareschal B.: How to Decide with PROMETHEE, Available at: http://www.visualdecision.com, 2000.

[6] Brans J.P., Mareschal B.: The Promcalc and Gaia decision-support system for multi-criteria decision aid, Decision Support Systems, Vol. 12(4–5), 1994, pp. 297–310.

[7] Carney D., Long F., What Do You Mean by COTS? Finally a Useful Answer, IEEE Software, Vol. 17 (2), March/April 2000.

[8] Hauge1 O., Ayala C., Conradi R., Adoption of Open Source Software in Software-Intensive Organizations – A Systematic Literature Review, Information & Software Technology, Vol. 52 (11), 2010, pp. 1133–1154.

[9] Maiden C.N., Ncube A.M., PORE: Procurement-Oriented Requirements Engineering Method for the Component-Based Systems Engineering Development Paradigm, 2nd

International Workshop on Component-Based Software Engineering, Los Angeles, USA 1998.

[10] Maiden N., Kim H., Ncube C., Rethinking process guidance for Software Component Selection, LNCS 2255, Dean J.C., Gravel A. (red.), Springer-Verlag, New York, 2002. [11] Mareschal B., De Smet Y., Nemery P.: Rank Reversal in the PROMETHEE II Method: Some

New Results, 978-1-Proceedings of the 2008 IEEE, IEEM4244-2630-0/08, 2008.

[12] Mohamed A., Ruhe G., Eberlein A., COTS Selection: Past, Present and Future, Proceedings of the 14th Annual IEEE International Conference and Workshops on the Engineering of Computer-Based Systems (ECBS´07), 2007.

[13] Morisio M., Torchiano M., Definition and classification of COTS: a proposal, Accepted at ICCBSS, Orlando (FL) February 4–6, 2002.

[14] Morisio M., Tsoukias A., Iusware: a methodology for the evaluation and selection of software products, IEEE Proceedings-Software Engineering, Vol. 144 (3), 1997.

[15] Saaty Thomas L.. How to make a decision: The analytic hierarchy process. "European Journal of Operational Research". Volume 48, No _{1, pp. 9–26, 1990.}

[16] Microsoft Office: http://www.microsoft.com/pl-pl/office365/office-online-services.aspx ALGORYTM KASTOMIZACJI OPROGRAMOWANIA BIUROWEGO

Streszczenie

W artykule podjto problem dostosowania oprogramowania uytkowego do indy-widualnych potrzeb uytkownika. W tym celu zaproponowano procedur opart na konceptualizacji wiedzy dla rozwaanej dziedziny oraz wykorzystaniu aparatu wielo-kryterialnego dla potrzeb dalszej oceny oprogramowania. Podej
cie zweryfikowane zostało praktycznie przyjmujc posta eksperymentu badawczego dla potrzeb dosto-sowania oprogramowania biurowego klasy Office. Artykuł kocz wnioski z przepro-wadzonych bada.

Słowa kluczowe: składniki COTS, AHP, MS Office

Agnieszka Konys

Katedra InĪynierii Systemów Informacyjnych Wydział Informatyki

Zachodniopomorski Uniwersytet Technologiczny ĩołnierska 49, 71-210 Szczecin, Poland