Functional Size Measurement Method Research Articles

Deep learning model for end-to-end approximation of COSMIC functional size based on use-case names

COSMIC is a widely used functional size measurement (FSM) method that supports software development effort estimation. The FSM methods measure functional product size based on functional requirements. Unfortunately, when the description of the product’s functionality is often abstract or incomplete, the size of the product can only be approximated since the object to be measured is not yet fully described. Also, the measurement performed by human-experts can be time-consuming, therefore, it is worth considering automating it. Our objective is to design a new prediction model capable of approximating COSMIC-size of use cases based only on their names that is easier to train and more accurate than existing techniques. Several neural-network architectures are investigated to build a COSMIC size approximation model. The accuracy of models is evaluated in a simulation study on the dataset of 437 use cases from 27 software development projects in the Management Information Systems (MIS) domain. The accuracy of the models is compared with the Average Use-Case approximation (AUC), and two recently proposed two-step models—Average Use-Case Goal-aware Approximation (AUCG) and Bayesian Network Use-Case Goal AproxImatioN (BN-UCGAIN). The best prediction accuracy was obtained for a convolutional neural network using a word-embedding model trained on Wikipedia+Gigaworld. The accuracy of the model outperformed the baseline AUC model by ca. 20%, and the two-step models by ca. 5–7%. In the worst case, the improvement in the prediction accuracy is visible after estimating 10 use cases. The proposed deep learning model can be used to automatically approximate COSMIC size of software applications for which the requirements are documented in the form of use cases (or at least in the form of use-case names). The advantage of the model is that it does not require collecting historical data other than COSMIC size and names of use cases.

Assessing the effectiveness of approximate functional sizing approaches for effort estimation

Context: Functional Size Measurement (FSM) methods, like Function Points Analysis (FPA) or COSMIC, are well-established approaches to estimate software size. Several approximations of these methods have been recently proposed as they require less time/information to be applied, however their effectiveness for effort prediction is not known. Objective: The effectiveness of approximated functional size measures for estimating the development effort is a key open question, since an approximate sizing approach may miss to capture factors affecting the effort. Therefore, we empirically investigated the use of approximate FPA and COSMIC sizing approaches, also compared with their standard versions, for effort estimation. Method: We measured 25 industrial software projects realised by a single company by using FPA, COSMIC, two approximate sizing approaches proposed by IFPUG for FPA (i.e. High Level and Indicative FPA), and three approximate sizing approaches proposed by the COSMIC organisation for COSMIC (i.e. Average Functional Process, Fixed Size Classification, and Equal Size Band). Then we investigated the quality of the regression models built using the obtained measures to estimate the development effort. Results: Models based on High Level FPA are effective, providing a prediction accuracy comparable to the one of the original FPA, while those based on the Indicative FPA method show poor estimation accuracy. Models based on COSMIC approximate sizing methods are also quite effective, in particular those based on the Equal Size Band approximation provided an accuracy similar to the one of standard COSMIC. Conclusion: Project managers should be aware that predictions based on High Level FPA and standard FPA can be similar, making this approximation very interesting and effective, while Indicative FPA should be avoided. COSMIC approximations can also provide accurate effort estimates, nevertheless, the Fixed Size Classification and Equal Size Band approaches introduce subjectivity in the measurement.

Literature review on Functional Requirements for Function Point Analysis in Mobile Game

Functional size measurement has been widely used as the effort prediction method for software project over the past decades. Despite the success in predicting the cost, time requirement, and staff resources utilizing the amount of functionality delivered by a system, the method still needs to be improved further especially in dealing with mobile application characteristics. In the domain of mobile game application, the functional features can be challenging to identify wholly due to various application platforms, diversity of game genre, and complex game scenario. This paper presents a literature review concerning the functional requirements of the mobile game. The review includes the process of defining the research question, search strategy, and selection of study. Fifty-three articles were found in the academic libraries, and only 30 relevant studies were selected for the review. This literature review aims to provide researchers and practitioners in software measurement and gaming technology with an overview of common functional characteristics in the mobile game, which can be integrated into the functional size measurement method.

Design and automation of a COSMIC measurement procedure based on UML models

Context. Many organizations are adopting the COSMIC method to size software products for estimating and controlling their development costs and performances. Using a functional size measurement method requires specialized expertise and can be time-consuming. Objectives. Since UML is the de facto industrial modeling language standard for object-oriented systems, it is very useful to understand how to exploit UML models for measuring software systems and for developing tools that can automatically derive the COSMIC size from them. This paper provides an answer to these needs. Method. We present a measurement procedure to derive the COSMIC functional size from UML software artifacts and a tool, named J-UML COSMIC, for the automation of the procedure. Based on the observation that different development processes are characterized by the use of different UML models, the tool has been designed to work with different UML artifacts (such as use case models, package diagrams, component diagrams, class diagrams, activity diagrams, and sequence diagrams) and to adapt to the specific employed process. To assess the measurement procedure and J-UML COSMIC, we have carried out two case studies and compared the measurement results provided by the tool with the ones obtained by experts applying the standard COSMIC method. Results. Using the proposed measurement procedure the tool is able to identify from UML software models all the COSMIC concepts and data movements identified by the experts. Moreover, the tool allows us to obtain incremental accurate measurements when new models are considered or existing ones are detailed. Conclusions. The designed approach is able to automatically measure the functional size starting from UML artifacts and providing higher accurate results when more data is available.

Application of the Functional Size Measurement Method on the Example of the National Register of Ukraine

An example of using the COSMIC functional size estimation method for calculating the size of the Unified State Information and Telecommunication System “Electronic Register of Apostilles” at COSMIC functional points is considered. The approaches to estimating the complexity and cost of creating this system based on its functional size are discussed.

Empirical evaluation and proposals for bands-based COSMIC early estimation methods

Abstract Background. In the early phases of software development projects, thorough application of the COSMIC functional size measurement method may require more time and effort than available. Thus, early approximate methods have been proposed for estimating the COSMIC functional size of an application, instead of measuring it. Objective. The goal of this paper is to empirically evaluate the accuracy of the COSMIC early size estimation methods that are based on evaluations at the functional process level, for which historical data are available. The goal is to provide practitioners with empirical evidence on the accuracy of these methods. Method. We evaluated the Average Functional Process and the Equal Size Bands methods. We also proposed and evaluated two new approaches for defining bands in the Fixed Size Classification method. The estimation was performed by applying these methods to a set of software applications for which the data necessary to perform estimations were available, having been previously measured according to the standard COSMIC method. Results. Our analyses show that the Average Functional Process method generally provides estimates that are reasonable for early and quick sizing, but in some cases its estimation errors are too large to be acceptable. On the contrary, the methods using bands can provide quite accurate estimates. We determine the level of accuracy that can be obtained based on the type of method used, the number of bands used, and the quantitative characterization of the ability to classify each functional process in the correct band. Conclusions. The Average Functional Process method may be unreliable, as it occasionally yields quite large errors. Organizations using bands-based methods cannot just follow the prescribed estimation process: they need to properly train people in charge of classifying functional processes in the correct size band.

IFPUG Function Points to COSMIC Function Points convertibility: A fine-grained statistical approach

BackgroundFunctional size measurement is widely used in software organizations because it supports the estimation of software development effort. Function Point Analysis was the first functional size measurement method and became quite popular. The COSMIC method is considered a second-generation method, due to its novel design, and has also gained wide acceptance. Since the proposal of the COSMIC method, the measure convertibility issue arose. Many studies have investigated this issue: several conversion techniques have been proposed and their accuracy has been evaluated through empirical studies. ObjectiveThe goal of the paper is to explore statistic conversion criteria that leverage the similarity between the Base Functional Components of the considered functional measurement methods, especially concerning elementary processes and functional processes. MethodStatistical models of the relationship between the considered measures were built, using Least Median of Squares linear regression. The models use measures of Function Point Analysis Base Functional Components and COSMIC Base Functional Components as independent and dependent variables, respectively. Accuracy of conversion was assessed via leave-one-out cross validation. ResultsThe proposed method was tested on three datasets, and was compared with other conversion methods. The proposed method achieved results that are never less accurate – and sometimes much more accurate – than alternative methods’. ConclusionsThe proposed method requires that when traditional Function Points are measured, information concerning Base Functional Components are recorded. If such information is available, the proposed approach is – according to the collected evidence – preferable to other conversion methods, with respect to both the effort required to obtain the results and their accuracy.

Comparative Analysis Of Functional Size Measurement Methods On Software Development Projects

¬This paper presents the role and significance of the estimation of programming sizes when estimating the execution of programming exercises and in assessing exertion for new programming undertakings. ¬is paper shows the comparative analysis of four standard programming estimating techniques (the Albrecht/IFPUG, MkII FPA, NESMA, and COSMIC method) that have professed to be practical size estimation techniques and look at the genuine idea of their size scales. ¬is paper identifies find that sizes delivered by the Albrecht/IFPUG and MkII FPA and NESMA techniques are entirely a size of standard (improvement) exertion. Only the COSMIC method gives a genuine proportion of practical size and therefore the most appropriate method for execution examinations crosswise over undertakings utilizing diverse advancements.

A study on the statistical convertibility of IFPUG Function Point, COSMIC Function Point and Simple Function Point

Background Several functional size measurement methods have been proposed. A few ones –like IFPUG and COSMIC methods– are widely used, while others –like Simple Function Points method– are interesting new proposals, which promise to deliver functional size measures via a faster and cheaper measurement process.Objectives Since all functional size measurement methods address the measurement of the same property of software (namely, the size of functional specifications), it is expected that measures provided in a given measurement unit can be converted into a different measurement unit. In this paper, convertibility of IFPUG Function Points, COSMIC Function Points, and Simple Function Points is studied.MethodConvertibility is analyzed statistically via regression techniques. Seven datasets, each one containing measures of a set of software applications expressed in IFPUG Function Points, COSMIC Function Points and Simple Function Points, were analyzed. The components of functional size measures (usually known as Base Functional Components) were also involved in the analysis.ResultsAll the analyzed measures appear well correlated to each other. Statistically significant quantitative models were found for all the combinations of measures, for all the analyzed datasets. Several models involving Base Functional Components were found as well.ConclusionsFrom a practical point of view, the paper shows that converting measures from a given functional size unit into another one is viable. The magnitude of the conversion errors is reported, so that practitioners can evaluate if the expected conversion error is acceptable for their specific purposes. From a conceptual point of view, the paper shows that Base Functional Components of a given method can be used to estimate measures expressed in a different measurement unit: this seems to imply that different functional size measurement methods are ‘structurally’ strongly correlated.

Functional change impact analysis in use cases: An approach based on COSMIC functional size measurement

Context: Because functional changes are inevitable throughout the software life-cycle, it is essential to assess and evaluate whether a Functional Change (FC) can be handled within the estimated project budget and time. Thus, a well-defined change measure and control process is vital for the success of the development project. In fact, the size measurement is widely used for effort and cost estimation. This paper explores the COSMIC Functional Size Measurement (FSM) method to evaluate a FC. Objective: The objective of this paper is to assess a FC in terms of COSMIC Function Point units in order to identify changes incurring potential impact on the software development progress. Thus, we suppose that the functional size of a FC is one of the factors that must be taken into consideration to analyze the impact of changes on the development progress. This helps managers in making decisions to answer a FC request. Method: The method proposed in this paper analyzes the FC impact in use case diagrams, the de-facto standard for modeling the Functional User Requirements (FUR). It distinguishes between internal and external FC to a use case. It proposes to quantify the FC impact on the functional size of a use case diagram in terms of COSMIC Function Point (CFP) units. In addition, it evaluates the status of a FC according to its functional size. Furthermore, we propose an algorithm for prioritizing changes in the case where more than one functional change is proposed. The algorithm is based on a set of heuristics where the objective is to minimize the effort required to answer the changes. It accounts for the most important factors when prioritizing changes (the functional size of the FC, and the preference of the change requester). These two factors are identified based on an investigation with the international COSMIC community. Originality: Several techniques have been used to identify and analyze the impact of a FC during various phases of the software life-cycle. For example, some researches used the colored commit graphs (at the implementation phase), other studies used the consistency rules between UML diagrams (at the design phase), etc. Compared to other approaches focused on impact change analysis, our proposed approach uses the COSMIC-FSM method. Quantifying the functional size of a FC in terms of CFP units allows us to evaluate more realistically the impact of a FC on the software development progress. Results: We propose six categories of FC status according to their sizes. Based on the FC status, it is possible to identify the FC impact on the software development progress. The FC status will help not only designers/developers in analyzing the impact of FC on the size of their work products but also managers to decide to accept or forgo a FC and maintain the development schedule. Moreover, the experiment conducted with 30 computer engineering students showed that students' ratings can be approximately evaluated when measuring FUR in terms of CFP units based on the FC status. Conclusion: Based on the finding of this study, it is now feasible to identify FC leading to potential impact on the software development progress. More specifically, evaluating FC in the use case diagrams will help in making quick decisions about accepting or rejecting a FC. Regardless of the used software life-cycle process, use cases are popular for specifying the software functionality. In practice, our proposed approach is applicable not only in the software development industry but also in academia. • Evaluate a functional change using COSMIC-FSM method to identify if it can be handled within the estimated budget and time. • A functional change impact analysis on the UML use case diagram approach is proposed. • The approach quantify a change in terms of CFP units and its impact on the functional size of the use case diagram. • Functional change status is identified based on its size. Six categories have been proposed to identify potential changes.

Automated COSMIC Function Point measurement using a requirements engineering ontology

ContextThere are two interrelated difficulties in requirements engineering processes. First, free-format modelling practices in requirements engineering activities may lead to low quality artefacts and productivity problems. Second, the COSMIC Function Point Method is not yet widespread in the software industry because applying measurement rules to imprecise and ambiguous textual requirements is difficult and requires additional human measurement effort. This challenge is common to all functional size measurement methods. ObjectiveIn this study, alternative solutions have been investigated to address these two difficulties. Information created during the requirements engineering process is formalized as an ontology that also becomes a convenient model for transforming requirements into COSMIC Function Point Method concepts. MethodA method is proposed to automatically measure the functional size of software by using the designed ontology. The proposed method has been implemented as a software application and verified with real projects conducted within the ICT department of a leading telecommunications provider in Turkey. ResultsWe demonstrated a novel method to measure the functional size of software in COSMIC FP automatically. It is based on a newly developed requirements engineering ontology. Our proposed method has several advantages over other methods explored in previous research. ConclusionManual and automated measurement results are in agreement, and the tool is promising for the company under study and for the industry at large.

基于IFPUG功能点方法的实时系统度量

IFPUG作为目前使用最为广泛的功能规模度量方法，不同度量员在对同一个实时系统进行度量时，结果存在较大的偏差。本文通过IFPUG和COSMIC方法对多个实际项目度量结果的比对，分析存在偏差的原因，提出IFPUG→COSMIC→待度量软件的映射关系，并对方法进行验证。结果表明，建立IFPUG→COSMIC→待度量软件的映射关系，可以提高数据功能的识别准确度，缩小不同度量员度量结果间的偏差。 As the most widely used functional size measurement method, IFPUG still has the limitation that there is a large deviation in experimental results when different measurement members measure the same real-time system. Based on the comparison of several measurement results of multiple projects by IFPUG and COSMIC method, this paper analyzes the reasons of these deviations. And a mapping relationship of IFPUG→COSMIC→measurement software is proposed. The experiment results show that establishing the mapping relationship of IFPUG→COSMIC→measurement software can improve the recognition accuracy of the data function and narrow the deviations between different measurement results of different practitioners.

COSMIC度量中持久存储器的识别方法

COSMIC方法是当前用于软件规模度量的一种全功能点估算方法。目前，该方法适用的项目很广泛，计数规则也比较简单，易于学习和掌握，已经被更多的软件组织所接受。运用COSMIC度量方法，其中有一项重要工作，就是识别持久存储器，为识别数据移动和计算功能点提供判定依据。但是，由于COSMIC度量手册中仅对识别持久存储器的一些原则和规则进行了规定和说明，有较大的模糊和不确定性，并且没有给出行之有效的操作方法，使得度量人员在实践度量中，存在较大的主观性，由此导致度量结果存在较大偏差。本文在遵循COSMIC度量手册原则和规则的基础上，结合实践度量实验，提出了一种可实施的识别持久存储器的方法步骤。 COSMIC method is a full function point counting method which is currently used for software size measurement. At present, this method’s applicable project is very wide and its counting rules are simple and easy to learn and master. It has been accepted by more and more software organizations. An important job of using the COSMIC measurement is to identify the persistent storage and to provide decision basis to identify the data movement and the calculation function point. However, the COSMIC Functional Size Measurement Method Version only regulates and explains some principles and rules to identify the persistent storage. So, it has lager fuzzy and uncertainty. It also doesn’t give an effective operation method, which makes the measurement personnel have a big subjectivity in the practical measurement. They lead to a great deviation in the measurement results. On the basis of the principles and rules of the COSMIC Functional Size Measurement Method Version, combined with the practical measurement experiment, this paper proposes procedures that can be carried out to identify the persistent storage.

Web Effort Estimation: Function Point Analysis vs. COSMIC

Context: software development effort estimation is a crucial management task that critically depends on the adopted size measure. Several Functional Size Measurement (FSM) methods have been proposed. COSMIC is considered a 2nd generation FSM method, to differentiate it from Function Point Analysis (FPA) and its variants, considered as 1st generation ones. In the context of Web applications, few investigations have been performed to compare the effectiveness of the two generations. Software companies could benefit from this analysis to evaluate if it is worth to migrate from a 1st generation method to a 2nd one.Objective: the main goal of the paper is to empirically investigate if COSMIC is more effective than FPA for Web effort estimation. Since software companies using FPA cannot build an estimation model based on COSMIC as long as they do not have enough COSMIC data, the second goal of the paper is to investigate if conversion equations can be exploited to support the migration from FPA to COSMIC.Method: two empirical studies have been carried out by employing an industrial data set. The first one compared the effort prediction accuracy obtained with Function Points (FPs) and COSMIC, using two estimation techniques (Simple Linear Regression and Case-Based Reasoning). The second study assessed the effectiveness of a two-step strategy that first exploits a conversion equation to transform historical FPs data into COSMIC, and then builds a new prediction model based on those estimated COSMIC sizes.Results: the first study revealed that, on our data set, COSMIC was significantly more accurate than FPs in estimating the development effort. The second study revealed that the effectiveness of the analyzed two-step process critically depends on the employed conversion equation.Conclusion: for Web effort estimation COSMIC can be significantly more effective than FPA. Nevertheless, additional research must be conducted to identify suitable conversion equations so that the two-step strategy can be effectively employed for a smooth migration from FPA to COSMIC.

A Detailed Analysis of Software Cost Estimation Using Cosmic-FFP

Software cost estimation is one of the most challenging tasks in software engineering. For the estimation, Function points are useful in the business application software domain and problematic in the real-time software domain. Full Function Points (FFP) are useful for functionality-based estimation, specifically for real-time and embedded software. Functional size measurement method that has user view of functional requirements developed by Common Software Measurement International Consortium (COSMIC) called COSMIC-FFP. By using COSMIC-FFP model, an early prediction of the functional complexity of the software throughout the software development life cycle within given budget constraints, reliability can be done. In this paper, a detailed analysis with process flow of COSMIC-FFP model has been discussed.

A measurement method for sizing the structure of UML sequence diagrams

ContextThe COSMIC functional size measurement method on UML diagrams has been investigated as a means to estimate the software effort early in the software development life cycle. Like other functional size measurement methods, the COSMIC method takes into account the data movements in the UML sequence diagrams for example, but does not consider the data manipulations in the control structure. This paper explores software sizing at a finer level of granularity by taking into account the structural aspect of a sequence diagram in order to quantify its structural size. These functional and structural sizes can then be used as distinct independent variables to improve effort estimation models. ObjectiveThe objective is to design an improved measurement of the size of the UML sequence diagrams by taking into account the data manipulations represented by the structure of the sequence diagram, which will be referred to as their structural size. MethodWhile the design of COSMIC defines the functional size of a functional process at a high level of granularity (i.e. the data movements), the structural size of a sequence diagram is defined at a finer level of granularity: the size of the flow graph of their control structure described through the alt, opt and loop constructs. This new measurement method was designed by following the process recommended in Software Metrics and Software Metrology (Abran, 2010). ResultsThe size of sequence diagrams can now be measured from two perspectives, both functional and structural, and at different levels of granularity with distinct measurement units. ConclusionIt is now feasible to measure the size of functional requirements at two levels of granularity: at an abstract level, the software functional size can be measured in terms of COSMIC Function Point (CFP) units; and at a detailed level, the software structural size can be measured in terms of Control Structure Manipulation (CSM) units. These measures represent complementary aspects of software size and can be used as distinct independent variables to improve effort estimation models.

An experimental study on the conversion between IFPUG and UCP functional size measurement units

The use of functional size measurement (FSM) methods in software development organizations is growing during the years. Also, object oriented (OO) techniques have become quite a standard to design the software and, in particular, Use Cases is one of the most used techniques to specify functional requirements. Main FSM methods do not include specific rules to measure the software functionality from its Use Cases analysis. To deal with this issue some other methods like Kramer’s functional measurement method have been developed. Therefore, one of the main issues for those organizations willing to use OO functional measurement method in order to facilitate the use cases count procedure is how to convert their portfolio functional size from the previously adopted FSM method towards the new method. The objective of this research is to find a statistical relationship for converting the software functional size units measured by the International Function Point Users Group (IFPUG) function point analysis (FPA) method into Kramer-Smith’s use cases points (UCP) method and vice versa. Methodologies for a correct data gathering are proposed and results obtained are analyzed to draw the linear and non-linear equations for this correlation. Finally, a conversion factor and corresponding conversion intervals are given to establish the statistical relationship.

RATIONALIZATION OF BUSINESS SOFTWARE SYSTEMS DEVELOPMENT AND ENHANCEMENT PROJECTS INVESTMENT DECISIONS ON THE BASIS OF FUNCTIONAL SIZE MEASUREMENT

Each rational investment decision, including those made by clients with regard to Business Software Systems (BSS) Development and Enhancement Projects (D&EP), should meet two measurable criteria: effectiveness and economic efficiency. However, in the case of BSS D&EP, the assumption concerning the measurability of these criteria is often treated as controversial. Meanwhile, the so-called concept of BSS D&EP Functional Assessment (FA), proposed by the author and verified in practice, allows for using the potential offered by the Functional Size Measurement (FSM) concept and methods in the area of the quantitative evaluation of these two criteria. Thus, the paper aims at presenting and proving the capabilities of using the functional assessment concept in the quantitative evaluation of BSS D&EP effectiveness and economic efficiency. Linking FSM issues with managerial aspects through the FA concept may contribute to a better understanding of the FSM importance, which is still underestimated by business managers, as in the subject literature this issue is usually considered from a technical perspective. Meanwhile, BSS D&EP FA can constitute the basis for rational decisions not only for BSS providers, but also for BSS clients. These issues classify into economics problems of software engineering research and practice.

A Practical Approach to Size Estimation of Embedded Software Components

To estimate software code size early in the development process is important for developing cost-efficient embedded systems. We have applied the COSMIC Functional Size Measurement (FSM) method for size estimation of embedded software components in the automotive industry. Correlational studies were conducted using data from two automotive companies. The studies show strong correlation between functional size and software code size, which is important for obtaining accurate estimation results. This paper presents the characteristics and results of our work, and aims to provide a practical framework for how to use COSMIC FSM for size estimation purposes. We investigate the results from our earlier correlational studies, and conduct further studies to identify such a framework. Based on these activities, we conclude that a clear purpose of the estimation process, a well-defined domain allowing categorization of software, consistent content and quality of requirements, and historical data from implemented software are key factors for size estimation of embedded software components.

The Economic Importance of Business Software Systems Functional Size Measurement

Execution of Business Software Systems (BSS) Development and Enhancement Projects (D&EP) encounters many problems, leading to the high scale of their failure, which then is reflected in considerable financial losses. One of the fundamental causes of such projects’ low effectiveness are improperly derived estimates for their costs and time. In their case, the budget and time frame are determined by the effort being spent on activities needed to deliver product that would be meeting client’s requirements. Meanwhile, objective and reliable effort estimation still appears to be a great challenge, what in the author’s opinion is caused by effort estimation based on resources, while such planning activity should base on the required software product size, which determines work effort. Estimation of BSS size requires using of the suitable software size measure, which has been sought for several decades now. What’s more, it is worth using the capabilities offered by such measure for the BSS D&EP assessment from the perspective being critical to a client, that is from functional perspective. Thus this paper analyses capabilities, being significant from the economic point of view, of taking advantage of suitable approach to the BSS size measurement, with particular consideration given to the two most popular functional size measurement methods normalized by ISO/IEC, namely International Function Point Users Group (IFPUG) method and Common Software Measurement International Consortium (COSMIC) method. This should contribute to the better understanding of the importance of this issue, still being underestimated by business managers – as in the subject literature this issue is usually considered from the technical point of view. Meanwhile, suitable BSS size measurement should constitute the basis for rational activities and business decisions not only for providers, but also for clients needs.