Sue E. Black

Formal Versus Agile: Survival of the Fittest

Many research have focused on new formal methods, integrating formal methods into agile ones, and assessing the agility of formal methods. This paper proves that formal methods can survive in an agile world; they are not obsolete and can be integrated into it. The potential for combining agile and formal methods holds promise. It might not always be an easy partnership, and succeeding will depend on a fruitful interchange of expertise between the two communities. Conducting a realistic trial project using a combined approach with an appropriate formal methods tool in a controlled environment will help assess the effectiveness of such an approach.

A survey of social media use in software systems development

In this paper, we describe the preliminary results of a pilot survey conducted to collect information on social media use in global software systems development. We created an on-line survey for developers who are using social media to communicate at work and whose work falls within the domain of software systems development, including web applications. Our results show that social media can enable better communication through the software system development process. 91% of respondents said that using social media has improved their working life.

Design metrics for web application maintainability measurement

Many web applications have evolved from simple HTML pages to complex applications that have a high maintenance cost. This high maintenance cost is due to the heterogeneity of web applications, to fast Internet evolution and the fast- moving market which imposes short development cycles and frequent modifications. In order to control the maintenance cost, quantitative metrics for predicting web applications maintainability must be used. This paper provides an exploratory study for new design metrics used for measuring the maintainability of web applications from class diagrams. The metrics are based on Web Application Extension (WAE)for UML and will measure the following design attributes: size, complexity, coupling and reusability. In this study the metrics are applied to two web applications from the telecommunications domain.

Fault Analysis in OSS Based on Program Slicing Metrics

In this paper, we investigate the Barcode OSS using two of Weiser’s original slice-based metrics (Tightness and Overlap) as a basis, complemented with fault data extracted from multiple versions of the same system. We compared the values of the metrics in functions with at least one reported fault with fault-free modules to determine a) whether significant differences in the two metrics would be observed and b) whether those metrics might allow prediction of faulty functions. Results revealed some interesting traits of the Tightness metric and, in particular, how low values of that metric seemed to indicate fault-prone functions. A significant difference was found between the Tightness metric values for faulty functions when compared to fault-free functions suggesting that Tightness is the ‘better’ of the two metrics in this sense. The Overlap metric seemed less sensitive to differences between the two types of function.

Is ripple effect intuitive? A pilot study

The computation of ripple effect is based on the effect that a change to a single variable will have on the rest of a program; it determines the scope of the change and provides a measure of the program’s complexity. The original algorithm used to compute ripple effect has been reformulated mainly to provide clarity in the operations involved. The reformulation involved some approximation which was shown not to affect the measures produced. The reformulated, approximated algorithm has been implemented as the software tool: Ripple Effect and Stability Tool (REST). This paper uses a software development project as a case study to look at the relationship between the approximated ripple effect and a programmer’s intuitive idea of ripple effect. Four versions of a mutation testing software tool were written in C over a period of several months. After the completion of each version the programmer was asked to detail his predicted/intuitive ripple effect for each module of code. The predictions are compared with the approximated ripple effect measures for each module and some surprising conclusions drawn.

Exploring the Eradication of Code Smells: An Empirical and Theoretical Perspective

This article has been made available through the Brunel Open Access Publishing Fund - Copyright @ 2010 Hindawi Publishing Corporation

A General Evaluation Criteria for Web Applications Maintainability Models

Many World Wide Web applications incorporate important business assets and offer a convenient way for businesses to promote their services through the Internet. Many of these Web applications evolved from simple HTML pages to complex applications which are difficult to maintain. Several maintainability models have been proposed for measuring the maintainability of Web applications. It is difficult to choose between the different maintainability models since no common criteria exists for evaluating them. In this paper, we introduce a general evaluation criteria for maintainability models (ECMM) which is applied on a sample Web application.

An Industrial Study Using UML Design Metrics for Web Applications

Many web applications have evolved from simple HTML pages to complex applications that are difficult to maintain. In order to control the maintenance of web applications quantitative metrics and models for predicting web applications maintainability must be used. This paper introduces new design metrics for measuring the maintainability of web applications from class diagrams. The metrics are based on Web Application Extension (WAE) for UML and measure the design attributes of size, complexity, and coupling. The paper describes an experiment carried out using a CVS repository from a US telecoms web application. A relationship is established between the metrics and maintenance effort measured by the number of lines of code changed.

Reducing Regression Test Size by Exclusion

Operational software is constantly evolving. Regression testing is used to identify the unintended consequences of evolutionary changes. As most changes affect only a small proportion of the system, the challenge is to ensure that the regression test set is both safe (all relevant tests are used) and inclusive (only relevant tests are used). Previous approaches to reducing test sets struggle to find safe and inclusive tests by looking only at the changed code. We use decomposition program slicing to safely reduce the size of regression test sets by identifying those parts of a system that could not have been affected by a change; this information will then direct the selection of regression tests by eliminating tests that are not relevant to the change. The technique properly accounts for additions and deletions of code. We extend and use Rothermel and Harrolds framework for measuring the safety of regression test sets and introduce new safety and precision measures that do not require a priori knowledge of the exact number of modification-revealing tests. We then analytically evaluate and compare our techniques for producing reduced regression test sets.

Visualizing the underlying trends of component latencies affecting Service Operation Performance

This paper presents a technology agnostic method for extracting the underlying distinct patterns of variations in the overall Performance of a Service Operation for changes to different application components supporting the Service Operation in a computer based Service Provider-Consumer contract. This short paper advocates that visualizing these patterns would help in early projection of the operations performance due to modification of the application components/processing catering to the operation, without the need of repetitive performance and load testing of the whole service. Lookup datasets against different component configurations are created to associate the variability of component processing impedances to the service operations Performance and best fit regression types are applied to enable trend extrapolation and interpolation.