Software source code sizing using fuzzy logic modeling

Knowing the likely size of a software product before it has been constructed is potentially beneficial in project management: for instance, size can be an important factor in determining an appropriate development/integration schedule, and it can be a significant input in terms of the allocation of personnel and other resources. In this study we consider the applicability of fuzzy logic modeling methods to the task of software source code sizing, using a previously published data set. Our results suggest that, particularly with refinement using data and knowledge, fuzzy predictive models can outperform their traditional regression-based counterparts

A New Calibration for Function Point Complexity Weights

Function Point (FP) is a useful software metric that was first proposed twenty-five years ago, since then, it has steadily evolved into a functional size metric consolidated in the well-accepted Standardized International Function Point Users Group (IFPUG) Counting Practices Manual - version 4.2. While software development industry has grown rapidly, the weight values assigned to count standard FP still remain same, which raise critical questions about the validity of the weight values. In this paper, we discuss the concepts of calibrating Function Point, whose aims are to estimate a more accurate software size that fits for specific software application, to reflect software industry trend, and to improve the cost estimation of software projects. A FP calibration model called Neuro-Fuzzy Function Point Calibration Model (NFFPCM) that integrates the learning ability from neural network and the ability to capture human knowledge from fuzzy logic is proposed. The empirical validation using International Software Benchmarking Standards Group (ISBSG) data repository release 8 shows a 22% accuracy improvement of mean MRE in software effort estimation after calibration

A systematic review of software development cost estimation studies

This paper aims to provide a basis for the improvement of software estimation research through a systematic review of previous work. The review identifies 304 software cost estimation papers in 76 journals and classifies the papers according to research topic, estimation approach, research approach, study context and data set. A web-based library of these cost estimation papers is provided to ease the identification of relevant estimation research results. The review results combined with other knowledge provide support for recommendations for future software cost estimation research, including: 1) Increase the breadth of the search for relevant studies, 2) Search manually for relevant papers within a carefully selected set of journals when completeness is essential, 3) Conduct more studies on estimation methods commonly used by the software industry, and, 4) Increase the awareness of how properties of the data sets impact the results when evaluating estimation methods

A knowledge management performance measurement system for small and medium enterprises

An important step after the implementation of knowledge management (KM) is to evaluate its effectiveness and performance. Knowledge management performance measurement (KMPM) is necessary in order to achieve effective and successful KM. Comprehensive set of constructs and metrics for KMPM have yet to be developed. In addition, a KMPM system that applies these constructs and metrics is found lacking. It is more apparent in the case of small and medium enterprises (SMEs) as most of the studies have focused on large organizations. Furthermore, as KM is characterized by an environment subject to uncertainties and fuzziness, there is a need to adopt a specific approach to address this issue. In this research, the focus is on the development of a KMPM system for the SMEs. A novel conceptual framework that categorized KM into three main aspects; knowledge resources, KM processes, and KM factors was used as a foundation for developing the system. New set of KMPM constructs and metrics were developed and tailored for the SMEs. Investigation of the developed constructs and metrics in terms of their applicability was carried out through a questionnaire survey. The constructs and metrics were validated through statistical analysis using the Statistical Package for the Social Sciences, where reliability analysis was conducted followed by validity analysis in terms of content, construct, convergent, discriminant, and criterion validities. The analysis results indicated that the developed constructs and metrics were applicable, reliable, and valid. Following this, a fuzzy logic methodology was utilized as the evaluation mechanism for the KMPM system. MATLAB software was used to develop the fuzzy inference system and Simulink was used to design and develop the system’s layout and interface. Case studies were conducted in three small and medium sized consultancy companies to evaluate the developed system. From the evaluation, the evaluators commented that the system was comprehensive, userfriendly, and suitable for SMEs application. In essence, this research has developed new set of constructs and metrics as well as a KMPM system specifically designed for SMEs