Gabriela Robiolo

Employing use cases to early estimate effort with simpler metrics

In order to calculate size and to estimate effort in applications, the standard method most usually used is function points, which has been used with good results in the development of industrial software for some time. However, some aspects should be improved, namely: the time at which the estimation of effort is performed and the margin of error in the effort estimation. Consequently, another size metric which could be used to obtain more accurate estimations should be found. This article presents two other size metrics for projects based on use cases: transactions and entity objects. Effort is estimated by using the technique mean productivity value. There is also a description of two case studies, one which involved four academic projects and the other one which involved four industrial projects. They were developed in order to compare the estimations obtained with each method. The result shows that the current way of estimating effort can be improved by using the number of transactions as a size metric and the technique mean productivity value.

Transactions and paths: Two use case based metrics which improve the early effort estimation

The fact that Albrechts function point method must be frequently improved or adjusted to suit new development contexts shows that there is a need for a new approach to early estimate effort. Such approach should reduce the estimation error and it is convenient for it to be based on use cases. The authors defined two simple metrics which capture two key aspects of software applications, size and complexity, which are called Transactions (T) and Paths (P). Also, in order to demonstrate that it is possible to reduce the error of effort estimation using these two new metrics, a case study was developed.

Towards a simplified definition of Function Points

Background: The measurement of Function Points is based on Base Functional Components. The process of identifying and weighting Base Functional Components is hardly automatable, due to the informality of both the Function Point method and the requirements documents being measured. So, Function Point measurement generally requires a lengthy and costly process. Objectives: We investigate whether it is possible to take into account only subsets of Base Functional Components so as to obtain functional size measures that simplify Function Points with the same effort estimation accuracy as the original Function Points measure. Simplifying the definition of Function Points would imply a reduction of measurement costs and may help spread the adoption of this type of measurement practices. Specifically, we empirically investigate the following issues: whether available data provide evidence that simplified software functionality measures can be defined in a way that is consistent with Function Point Analysis; whether simplified functional size measures by themselves can be used without any appreciable loss in software development effort prediction accuracy; whether simplified functional size measures can be used as software development effort predictors in models that also use other software requirements measures. Method: We analyze the relationships between Function Points and their Base Functional Components. We also analyze the relationships between Base Functional Components and development effort. Finally, we built effort prediction models that contain both the simplified functional measures and additional requirements measures. Results: Significant statistical models correlate Function Points with Base Functional Components. Basic Functional Components can be used to build models of effort that are equivalent, in terms of accuracy, to those based on Function Points. Finally, simplified Function Points measures can be used as software development effort predictors in models that also use other requirements measures. Conclusion: The definition and measurement processes of Function Points can be dramatically simplified by taking into account a subset of the Base Functional Components used in the original definition of the measure, thus allowing for substantial savings in measurement effort, without sacrificing the accuracy of software development effort estimates.

An Alternative Method Employing Uses Cases for Early Effort Estimation

Function points are a standard method frequently used to calculate size and to estimate effort in applications. Although it has been used with good results in the development of industrial software, it is still necessary to improve some aspects such as: the time at which the estimation of effort is performed and the margin of error in the effort estimation. In this article an alternative method for early effort estimation based on use cases is presented. Two new alternative notions of size are used for effort estimation: transactions and entity objects. A case study developed in order to compare the estimations obtained with the two methods for actual projects is described. The result shows that by using number of transactions as a notion of size and the technique mean productivity value to perform the estimation, the current way of estimating effort can be improved.

The role of the measure of functional complexity in effort estimation

Background. Currently there are several definitions of measures that should represent the size of software functional requirements. These measures have gained a quite relevant role, since they are one of the few basis upon which effort estimation can be based. However, traditional Functional Size Measures do not take into account the amount and complexity of the elaboration required, concentrating instead on the amount of data accessed or moved. This is a problem, when it comes to effort estimation, since the amount and complexity of the required data elaborations affect the implementation effort, but are not adequately represented by the current measures (including the standardized ones). Objective. The paper evaluates different types of functional size measures as effort estimators. Moreover, the consequences of taking into consideration also the amount and complexity of required elaboration in the effort estimation models are evaluated. Methods. In this paper we take into consideration a representative set of functional size measures (namely, function points, COSMIC function points and use case points) and a recently proposed elaboration complexity measure (Paths) and evaluate how well these measures are correlated with the development effort. To this end, we measured a set of 17 projects and analyzed the resulting data. Results. We found that it is possible to build statistically valid models of the development effort that use the functional size and complexity measures as independent variables. In fact, we discovered that using the measure of elaboration complexity in addition to the functional size substantially improves the precision of the fitting. Conclusions. The analysis reported here suggests that a measure of the amount and complexity of elaboration required from a software system should be used, in conjunction with traditional functional size measures, in the estimation of software development effort. Further investigations, involving a greater number of projects, are however needed to confirm these findings.

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

Abstract 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. Method Convertibility 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. Results All 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. Conclusions From 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.

Traceable complexity metric from requirements to code

This paper presents a methodology to detect and measure the complexity of traceable transactions from requirements (use cases) to code (source code) of a system.

The Hero program: Development and initial validation of an intervention program to promote prosocial behavior in adolescents

This article has a dual purpose. First, it proposes to investigate adolescents’ opinion and acceptance of the new online program called “Hero.” Second, this article studies the program’s effectiveness in promoting prosocial behavior. The sample included 51 men and women participants between the ages of 12 and 16 (average age 15.02; SD = 1.07; 49% men). All of the adolescents attended high school and belonged to a middle socioeconomic status. The results indicated that the majority of the users enjoyed participating in the Hero program and thought that it was easy to use and useful, that what they learned could be transferred to daily life, and that they would recommend the program to other adolescents. Moreover, the Hero intervention was effective in promoting prosocial behavior toward strangers and family members but not in promoting prosocial behavior toward friends.

Matching in Entrepreneurial Finance Networks

We empirically explore the importance of networks in the match formation of startups and investors. Using a massive network of connections from the entrepreneurial finance setting in California, we estimate a matching model were network distance can both determine the value of a prospective match as well as moderate observable complementarities. We find that distance drives matching value and moderates preferences for experience and education. While we corroborate that there is significant sorting along this preferences in realized matches, our results indicate that connections can potentially outweigh them, emphasizing the role of networks in alleviating matching frictions in these markets.

The Added-Value of Network Connections in Entrepreneurial Finance

Entrepreneurs are usually exhorted to attract the best networked investors. We provide further insights into this advice by estimating network effects in the performance of entrepreneurial ventures. We show dimensions that are critical in this estimation, such as the consideration for startups’ connections, common connections among investors, and the decreasing returns to network centrality, and estimate their relative importance. We estimate networks effects using an an original database of connections among startups, investors and individuals with relevant roles in California, collected from web-based sources, resulting in a network of nearly 1 million connections.