Jean-Marc Desharnais

A comparison of software effort estimation techniques: using function points with neural networks, case-based reasoning and regression models

Estimating software development effort remains a complex problem attracting considerable research attention. Improving the estimation techniques available to project managers would facilitate more effective control of time and budgets in software development. This paper reviews a research study comparing three estimation techniques using function points as an estimate of system size. The models considered are based on regression analysis, artificial neural networks and case-based reasoning. Although regression models performed poorly on the data set of 299 projects, both artificial neural networks and case-based reasoning appeared to have value for software development effort estimation models. Case-based reasoning in particular is appealing because of its similarity to expert judgment approaches and for its potential as an expert assistant in support of human judgment.

The state of the art of mobile application usability evaluation

Mobile devices and applications provide significant advantages to their users, in terms of portability, location awareness, and accessibility. A number of studies have examined usability challenges in the mobile context, and proposed definitions of mobile application usability and methods to evaluate it. This paper presents the state of the art of the evaluation and measurement of mobile application usability.

Initiating software process improvement in very small enterprises

The paper concerns software process improvement in Very Small Enterprises (VSEs). It presents briefly a gradual methodology to initiate software process improvement in VSE through three steps approach and develops the first and most original step. This first step is based on a light evaluation achieved by means of a dedicated Micro-Evaluation approach. It has been experimented during 7 years in 86 organizations from three countries. The experience with that utilization tends to show that such a light approach is practicable and promising, at least for the targeted enterprises.

Estimating Software Development Effort with Case-Based Reasoning

Software project effort estimation is a difficult problem complicated by a variety of interrelated factors. Current regression-based models have not had much success in accurately estimating system size. This paper describes a case based reasoning approach to software estimation which performs somewhat better than regression models based on the same data and which has some similarity to human expert judgement approaches. An analysis is performed to determine whether different forms of averaging and adaptation improve the overall quality of the estimate.

An Expert-Based Framework for Evaluating iOS Application Usability

Mobile applications are gaining in popularity because of the significant advantages of mobile devices, such as portability, location awareness, electronic identity, and an integrated camera. However, these devices have a number of disadvantages in terms of usability, like limited resources and small screen size. Evaluating the usability of applications developed for mobile operating systems is a very important step in addressing these disadvantages and achieving success in mobile application markets, such as Apples App Store. Usability evaluation must be tailored to all the various mobile operating systems in use, as they each have their own particular characteristics. This paper presents a mobile application usability evaluation framework for one of the most popular mobile operating systems, iOS. A set of questions is defined and applied to evaluate the usability of eleven applications available at the App Store.

Measurement of functional reuse in maintenance

This paper is concerned with the identification and measurement of reuse within projects in which functional enhancements have been added to existing software applications. The proposed approach is based on the measurement of reuse from a functional perspective rather than from a technical perspective. Two key concepts are introduced: a reuse indicator and a predictor ratio. The reuse indicator is derived from an analysis of the function types as currently defined in Function Points Analysis. The predictor ratio is derived from an understanding of the avoided-cost concept and of how it can be captured using historical databases of function points from previous development projects. This paper indicates how, in functional enhancement projects, the predictor ratio can be combined into the reuse indicator to derive an alternative size measure which takes into account functions reused and not redeveloped. The paper also demonstrates how these ratios can then be integrated in a maintenance productivity model to analyse the benefits of reuse by taking into account the avoided cost of functions reused. A case study based on an industrial data set is provided to illustrate the measurement of functional reuse in an enhancement project and its impact in maintenance productivity analysis.

An investigation into the best practices for the successful design and implementation of lightweight software process assessment methods

Software process assessment (SPA) is an effective tool to understand an organizations process quality and to explore improvement opportunities. However, the knowledge that underlies the best practices required to develop assessment methods, either lightweight or heavyweight methods, is unfortunately scattered throughout the literature. This paper presents the results of a systematic literature review to organize those recognized as the best practices in a way that helps SPA researchers and practitioners in designing and implementing their assessment methods. Such practices are presented in the literature as assessment requirements, success factors, observations, and lessons learned. Consequently, a set of 38 best practices has been collected and classified into five main categories, namely practices related to SPA methods, support tools, procedures, documentation, and users. While this collected set of best practices is important for designing lightweight as well as heavyweight assessment methods, it is of utmost importance in designing lightweight assessment methods, as the design of which depends on individual experience. The paper is revised based on previous reviewers comments.Literature is reviewed to identify best practices related to SPA methods.A set of 38 best practices has been collected and classified.Classes include SPA methods, support tools, procedures, documentation, and users.The collected set is of utmost importance in designing lightweight SPA methods.

Using the COSMIC method to estimate Agile user stories

Agile Project Management (APM) is widely used in different software projects from different application domains. APM includes a series of commonly used project management approaches with the intent to handle better uncertainty and unpredictability, which is not always successful. For instance, in a large portion of software projects, accurate planning (and estimating) of whole project lifetime with Agile is difficult. Since a continuously change in (product) requirements occurs as well their incompleteness at the project initialization phase, project plan must be under control and continuously be revised according to its needs and resources. In Agile projects, planning is mainly based on guess estimate of the effort trying to balance the product and the resources not showing the part of each one. In order to improve the guess estimate, this paper proposes an approach moving from the COCOMO (Constructive Cost Model) worked, using the COSMIC measurement method at the micro-level (User Stories) jointly with the quality of the documentation for deploying the functional analysis. The proposed procedure shows that this approach can help the planner to know better why the global effort changes by the time.

An exploratory study on the accuracy of FPA to COSMIC measurement method conversion types

Background: Functional size measurement methods are increasingly being adopted by software organizations due to the benefits they provide to software project managers. The Function Point Analysis (FPA) measurement method has been used extensively and globally in software organizations. The COSMIC measurement method is considered a second generation FSM method, because of the novel aspects it brings to the FSM field. After the COSMIC method was proposed, the issue of convertibility from FPA to COSMIC method arose, the main problem being the ability to convert FPA historical data to the corresponding COSMIC Function Point (CFP) data with a high level of accuracy, which would give organizations the ability to use the data in their future planning. Almost all the convertibility studies found in the literature involve converting FPA measures to COSMIC measures statistically, based on the final size generated by both methods. Objectives: This paper has three main objectives. The first is to explore the accuracy of the conversion type that converts FPA measures to COSMIC measures statistically, and that of the type that converts FPA transaction function measures to COSMIC measures. The second is to propose a new conversion type that predicts the number of COSMIC data movements based on the number of file type references referenced by all the elementary processes in a single application. The third is to compare the accuracy of our proposed conversion type with the other two conversion types found in the literature. Method: One dataset from the management information systems domain was used to compare the accuracy of all three conversion types using a systematic conversion approach that applies three regression models: Ordinary Least Squares, Robust Least Trimmed Squares, and logarithmic transformation were used. Four datasets from previous studies were used to evaluate the accuracy of the three conversion types, to which the Leave One Out Cross Validation technique was applied to obtain the measures of fitting accuracy. Results: The conversion type most often used as well as the conversion type based on transaction function size were found to generate nonlinear, inaccurate and invalid results according to measurement theory. In addition, they produce a loss of measurement information in the conversion process, because of the FPA weighting system and FPA structural problems, such as illegal scale transformation. Our proposed conversion type avoids the problems inherent in the other two types but not the nonlinearity problem. Furthermore, the proposed conversion type has been found to be more accurate than the other types when the COSMIC functional processes comprise dataset applications that are systematically larger than their corresponding FPA elementary processes, or when the processes vary from small to large. Finally, our proposed conversion type delivered better results over the tested datasets, whereas, in general, there is no statistical significant difference between the accuracy of the conversion types examined for every dataset, particularly the conversion type most often used is not the most accurate. Conclusions: Our proposed conversion type achieves accurate results over the tested datasets. However, the lack of knowledge needed to use it over all the datasets in the literature limits the value of this conclusion. Consequently, practitioners converting from FPA to COSMIC should not stay with only one conversion type, assuming that it is the best. In order to achieve a high level of accuracy in the conversion process, all three conversion types must be tested via a systematic conversion approach.

Identification and analysis of attributes and base measures within ISO 9126

The ISO 9126 quality model is a 4-part suite of documents presenting 10 characteristics of the quality of software products, 27 subcharacteristics, and an inventory of more than 250 derived measures proposed to quantify these quality characteristics and subcharacteristics. However, these measures are presented only at a fairly abstract level as formulae composed from a set of 80 base measures. As the base measures themselves lack detailed descriptions, including the attributes they are attempting to measure, they are highly susceptible to individual interpretation. Improving the design of the 80 base measures is a daunting task. The ISO 9126 standard is currently under revision by an ISO working group (ISO/IEC JTC1/SC7 WG6), and this paper proposes a process to determine which of these base measures should be improved in the timeliest fashion.