Marcelo Jenkins

Function Point Structure and Applicability: A Replicated Study

Background: The complexity of providing accurate functional software size and effort prediction models is well known in the software industry. Function point analysis (FPA) is currently one of the most accepted software functional size metrics in the industry, but it is hardly automatable and generally requires a lengthy and costly process. Objectives: This paper reports on a family of replications carried out on a subset of the International Software Benchmarking Standards Group dataset (ISBSG R12) to evaluate the structure and applicability of function points. The goal of this replication is to aggregate evidence about internal issues of FPA as a metric, and to confirm previous results using a different set of data. Methods: A subset of 202 business application projects from 2005 to 2011 was analyzed. FPA counting was analyzed in order to determine the extent to which the basic functional components (BFC) were independent of each other and thus appropriate for an additive model of size. The correlations among effort and BFCs and unadjusted function points (UFP) were assessed in order to determine whether a simplified sizing metric might be appropriate to simplify effort prediction models. Prediction models were constructed and evaluated in terms of accuracy. Results: The results confirmed that some BFCs of the FPA method are correlated. There is a relationship between BFCs and effort. That suggest that prediction models based on transactional functions (TF) or external inputs (EI) appears to be as good as a model based on UFP in this subset of projects. Conclusions: The results might suggest an improvement in the performance of the measurement process. Simplifying the FPA measurement process based on counting a subset of BFCs could allow savings in measurement effort, preserving the accuracy of effort estimates.

A Top-Down Design Approach for an Automated Testing Framework

Mobile applications have become popular work tools. Portability and ease of Internet connectivity are characteristics that favor this adoption. However, mobile applications sometimes incorrectly process events associated with the user-interaction features. These features include content presentation or navigation. Rotating the devices, and gestures such as scroll or zoom into screens are some examples. There is a need to assess the quality with which mobile applications are processing these user-interaction features in order to improve their performance. In this paper, we present a top-down design approach for an automated testing framework for mobile applications. Our framework integrates digital image processing, GUI information, and historical bug information to identify new bugs based on user-interaction features. Our framework captures images before and after applying the user-interaction features and uses the SURF algorithm to identify interest points in each image. We compared interest points to note differences on the screens before and after applying the user-interaction features. This differences helps to find bugs in mobile applications. The first results show that it is feasible to identify bugs with user-interaction features using the proposed technique.

Function point structure and applicability validation using the ISBSG dataset: a replicated study

Background: The complexity of providing accurate software size estimation and effort prediction models is well known in the software industry, turning it into one of the most important research issues in empirical software engineering. Function points (FPA) is currently one of the most accepted software functional size metrics in the industry, but it is hardly automatable and generally requires a lengthy and costly process. Although accurate size estimation and effort prediction are very important for the success of any project, many practitioners have experienced difficulties in applying them. Objectives: This paper reports on a replicated study carried out on a subset of the ISBSG dataset to evaluate the structure and applicability of function points. The goal of this replication was to aggregate evidence and confirm results reported about internal issues of FPA as a metric using a different set of data. First, we examined FPA counting in order to determine which base functional components (BFC) were independent of each other and thus appropriate for an additive model of size. Second, we investigated the relationship between size and effort. Methods: A subset of the ISBSG dataset was used with 14 business application projects developed in C# from 2008 to 2011. We studied BFC independence and correlation between size, effort and productivity. FPA base functional components independence was checked with the Pearson and Kendalls Tau correlation coefficient. Besides, we studied the correlation between size and effort. Results: The replication aggregated evidence and confirmed that some BFC of the FPA method are correlated. There is a relationship between BFC unadjusted function points and effort. Limitations: This is an initial experiment of a research in progress that was performed on a small subset of 14 recent projects taken from the ISBSG dataset. Conclusions: Simplifying and automating a FPA measurement process based on counting BFC could encourage the adoption of FSM methods. Further research is needed.

Application of Statistical Process Control to Software Defect Metrics: An Industry Experience Report

Statistical Process Control (SPC) has become of great significance for software engineering organizations as more of them decide to implement quality improvement initiatives. The Capability Maturity Model Integration (CMMI-DEV 1.3) for example, proposes the use of statistical techniques at maturity level 4 to ensure some degree of process predictability. However, the nature of software products and processes poses many challenges to the application of SPC, mainly regarding the design of control charts, a key tool. These challenges have led to opposing views on the applicability of SPC to software processes. This article presents an industry experience report on the application of SPC in a Software Verification and Validation Unit at an Information Technology Division from a financial institution. We present the steps followed to implement SPC in this organization, describe the theoretical assumptions involved in selecting the appropriate control charts, and show a process improvement analysis of using SPC in the organization.

PRO-SOFTWARE: a government-industry-academia partnership that worked

We describe the experience of implementing PRO-SOFTWARE, a software quality collaboration project involving government, industry, and academia designed to bolster the software industry in Costa Rica by improving their software processes. We describe how the project was conceived, who the stakeholders are, explain in detail the main components of the project, and report the results obtained thus far from implementing software process improvement initiatives at three software companies. Particularly, we describe how a group of seven software quality engineers were trained to create a local consultant force within the country able to provide competent software process improvement services to the rest of the industry. Our experience demonstrates that collaboration between government, industry and academia in the software field can be successful if clear goals are established and a proven methodology is used to implement the project. We should interest organizations that want to implement software process improvement projects with limited resources.

A combined object-oriented and logic programming tool for AI

Object-oriented programming and logic programming are two of the most used programming paradigms in artificial intelligence. The authors describe a proposal to combine these two paradigms into a common logical framework. The combined framework encompasses the main features of both paradigms, making it a suitable tool for developing AI applications. First, the combined paradigm is defined as the combination of the main properties of both paradigms. Then, the authors describe the main features of the Plog programming language, a logical language that supports such a paradigm.

A Software Defect-Proneness Prediction Framework: A new approach using genetic algorithms to generate learning schemes.

Recently, defect prediction software is an important research topic in the software engineering field. The demand for development of good quality software has seen a rapid growth in the last few years. The software measurement data collected during the software development process include valuable information about software projects status, progress, quality, performance, and evolution. The software fault prediction in the early phases of software development can help and guide software practitioners to focus the available testing resources on the weaker areas during the software development. OBJECTIVE: This paper presents an approach that combines three phases: data preprocessing, attribute selector and learning algorithms using a genetic approach and select the best combination. METHOD: The framework is comprised of 1) scheme learning generator. This component evaluates performance of the learning schemes and suggests the best option according to each data set analyzed, 2) defect predictor component builds models according to the evaluated learning schemes and predicts software defects with new data agreed to the constructed model. CONCLUSIONS: The framework has considered more combinations of learning schemes than other proposals which select the model configuration manually, which means that there are more possibilities to find better learning schemes for each data set. The computational processing of the genetic approach was less costly than Song approach. Finally, The Genetic approach presented an improvement of 0.032 equivalent to 3.2% more than Song approach.

Teaching computer aided software engineering at the graduate level

Although computer-aided software engineering (CASE) is one of the most current and interesting subjects within software engineering, relatively little has been published on the issue of teaching CASE at the graduate level. This paper reports a case study in teaching a graduate-level course on CASE tools in a span of six years. We explain the structure and contents of the course, describe the work the students perform as their term project, and summarize the outcome and lessons learned in five course offerings. The issues discussed in this paper might help educational institutions and college professors in designing and implementing software engineering courses at the graduate level.

COSMIC base functional components in Functional Size based effort estimation models

Software effort estimation models has been an area of considerable research for many years and it is still a challenge for software engineering. Although Functional Size Measurement (FSM) methods have become widely used, effort estimation based on the functional size still needs further research. Unbiased and comprehensive comparison between prediction models is needed. Some studies suggest that the relationship between effort and the base functional components of a FSM method would improve estimation models. This paper evaluates the structure of COSMIC FFP base functional components and its applicability in functional size based effort estimation models. Our study reports a benchmarking experiment evaluating 600 learning schemes for 12 ISBSG R12 sub datasets in business application projects which were sized by the COSMIC FSM method. In total, 7,200 runs were conducted (Learning schemes X Datasets) and the best learning schemes were reported by dataset. Lessons learned after conducting the experiment are discussed.

Applying a Verification Protocol to Evaluate the Accuracy of Functional Size Measurement Procedures: An Empirical Approach

This paper presents a verification protocol for analyzing the source of inaccuracy in measurement activities of Function Points Analysis FPA and Automated Function Point AFP. An empirical study was conducted with the protocol to determine the accuracy of FPA and AFP, and common differences during their application. The empirical study was conducted and differences between the measurement process regarding accuracy, reproducibility, and protocol adoption properties were reported. Effectiveness of the verification protocol to evaluate functional size measurement procedures was provided. The application of the protocol enabled participants to identify differences and their causes between counting results in a systematic way. Many participants had a favorable opinion regarding the usefulness of the protocol, and most of them agreed that the application of this protocol improved their understanding of measurement methods.