Software Trouble Index

Size, complexity, and human dependency on software--based products have grown dramatically during past decades. Software developers are struggling to deliver reliable software with acceptable level of quality, within given budget and schedule. One measure of software quality and reliability is the number of residual faults. Therefore, researchers are focusing on the identification of the number of fault presents in the software or identification of program modules that are most likely to contain faults. A lot of models have been developed using various techniques. A common approach is followed for software reliability prediction utilizing failure data. Software reliability and quality prediction is highly desired by the stakeholders, developers, managers, and end users. Detecting software faults early during development will definitely improve the reliability and quality in cost-effective way.KeywordsSoftware ReliabilityFault PredictionSoftware MetricsCapability Maturity ModelTest Case PrioritizationThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

: The Rome Air Development Center has developed the Software Quality Framework as a means to specify software quality goals and measure software quality. Much of the work to date has focused on metrics applicable to software code. This report describes an effort undertaken to measure the quality of software products earlier in the software development life cycle, during the design phase, and to automate the capture of metric data from design media. Metrics of software quality, primarily those related to the criterion simplicity (or conversely, complexity), were reviewed. This review includes those metrics previously developed in the Software Quality Framework. Two metrics, Halstead's Software Science and McCabe's Cyclomatic Complexity were chosen for their amenability to measurement during design and their potential for automation. Two design media were used: Design Aids for Real-Time Systems, an experimental automated design tool developed at the Charles Stark Draper Laboratory; and Ada as a program design language.

Software reliability has been considered as a crucial parameter in the measurement of software quality. In the present scenario, software companies try to develop high reliable software to sustain in the competitive market environment. Reliability may be defined in terms of software ability up to which it can perform its desired functions without any failure. Many software reliability growth models (SRGMs) have been provided by the researchers with a sole motive of reliability measurement. The high availability of these models raises a question that “Is each model is fit to each type of dataset?” To answer this question, a comprehensive analysis of SRGMs is highly required. The present study highlights the various concepts about the SRGMs so that they can be used more efficiently to measure the software reliability.

The number of people who need special care and are living alone has increased significantly in recent years. To help and assist them, different kinds of systems have been developed, for example, to detect and alert falls. However, the acceptance of such systems requires on the user part the belief that the system uses the collected data properly and not cause any harm. Specifically, trust for ubiquitous systems, which represent computing everywhere, anytime, and transparent for the final user, is a relevant issue. Thus, this paper evaluates, using measures of software quality, trust in a ubiquitous system, called fAlert, for detecting and warning falls. fAlert is an Android system that makes use of sensors to detect anomalies in everyday user activities.

As a measure of software quality, current static code analyses reveal thousands of quality defects on systems in brown-field development in practice. Currently, there exists no way to prioritize among a large number of quality defects and developers lack a structured approach to address the load of refactoring. Consequently, although static analyses are often used, they do not lead to actual quality improvement. Our approach recommends to remove quality defects, exemplary code clones and long methods, which are easy to refactor and, thus, provides developers a first starting point for quality improvement. With an empirical industrial Java case study, we evaluate the usefulness of the recommendation based on developers’ feedback. We further quantify which external factors influence the process of quality defect removal in industry software development.

We empirically examine the relationship between software design modularity and software quality in open source software (OSS) development projects. Conventional wisdom suggests that degree of software modularity affects software quality. An analysis of 203 software releases in 46 OSS projects hosted on SourceForge.net lends support for a more complex relationship between software modularity and software quality than conventional wisdom suggests. We find that software modularity is associated with reduced software complexity, an increased number of static software bugs, and a mixed relationship with the percentage of bugs closed. We do not find empirical evidence supporting any relationship between modularity and other measures of customer satisfaction. In addition to empirically testing the relationship between modularity and quality, we introduce new measures of software modularity and software quality. Implications are developed for the theory of modularity and the practice of software development.

Software Quality is very important aspect for any software development company. Software quality measurement is also a major concern for improving the software applications in software development processes in these companies. The quantification of various quality factors and integrate them into various software quality models is very important to analyze the quality of software system. Software usability is one of the important quality factors now days due to the increasing demand of interactive and user friendly software systems. In this paper, an attempt has been made to quantifying the usability of Ms-Excel 2007 and Ms-Excel 2010 application software using ISO/IEC 9126 model and compare the numeric value of usability for both version of Ms-Excel 2007 and Ms-Excel 2010. Due to the random nature of the usability attributes, the fuzzy multi criteria decision technique has been used to evolve the usability of the software office application. The present method will be helpful to analyze and enhance the quality of interactive software system.

Cost, schedule and quality are highly correlated factors in software development. They basically form three sides of the same triangle. Beyond a certain point (the "Quality is Free" point), it is difficult to increase the quality without increasing either cost or schedule or both for the software under development. As products and applications mature, users expect higher quality products. They want IT organizations to be responsible and accountable for the quality claims made by the product marketing teams. In the last couple decades, much software engineering research has focussed on standards, methodologies and techniques for improving software quality, measuring software quality and software quality assurance. Most of this research is focused on the internal/development view of quality. More recent studies done in conjunction with the marketing groups have made attempts to understand the customer view of quality. All of these different ongoing activities to understand quality from the various perspectives have made the field even more enriching and exciting. The Fifth Workshop on Software Quality aims to bring together academic, industrial and commercial communities interested in software quality topics to discuss the different technologies being defined and used in the software quality area.

Within the software engineering community we are beginning to see the emergence of models and assessment procedures that focus on software quality measurement and the capability of an organization to produce a quality product (Jones, 1990; Humphrey, 1990). While certainly a step in the right direction, these procedures describe where we would like to be, but provide little assistance in how to get there. The material presented in this book describes not only the destination, i.e. a process supporting software quality assessment and prediction, but a road map outlining how to get there.

For a software-intensive system, software quality measures how well the software is designed and how well the software conforms to that design, whereas architecture of a software system is typically defined as the fundamental organization of the system embodied in its components, their relationships to each other and the environment, and the principles governing the system's design and evolution. Obviously, as long as there were no software systems, governing their architecture was no problem at all; when there were only small systems, governing their architecture became a mild problem; and now we have gigantic software systems, and governing their architecture has become an equally gigantic problem (to paraphrase Edsger Dijkstra). In this paper we propose a unified approach to the problem of governing (or managing) the knowledge about architecture of software systems and demonstrate by example its impact on a certain software project. First we postulate that only the holistic approach that supports continuous integration and verification for all system architectural artifacts is one worth taking. Next we demonstrate by example how a concrete large software project being developed in an agile approach is being perceived using the model in question

Empirical Analysis of Quality Models in Practice in Small IT Companies in SEE Region

Maturity models assess the organization's processes to determine their level of maturity and capability. There is an implicit assumption that a higher level of maturity (or more capability) leads to higher level of productivity and quality. Based on this assumption, maintenance organizations that implement a number of exemplary practices should show an improvement in both. In this article, we use data from a maintenance organization to verify this assumption. The introduction presents the challenges associated with the measurement of software maintenance productivity and quality. We then introduce our methodology, followed by an analysis of the data, and, finally, lessons learned and future work.

Software change history plays an important role in measuring software quality and predicting defects. Co-change metrics such as number of files changed together has been used as a predictor of bugs. In this study, we further investigate the impact of specific characteristics of co-change dispersion on software quality. Using statistical regression models we show that co-changes that include files from different subsystems result in more bugs than co-changes that include files only from the same subsystem. This can be used to improve bug prediction models based on co-changes.

The role of product quality in industries influenced by network effects has been the subject of significant debate among management theorists. Some have suggested that network effects can result in inferior products, as consumers value a large cohort of fellow adopters over the technical quality of a given product. Others argue that cases of market domination by inferior products are quite rare and that product quality is an important aspect of network-based competition. Thus, a fundamental question has arisen from this debate: in industries influenced by network effects, does product quality matter? This research uses a sample of product releases in the application software industry from 1986 to 1998 to test the impact of product quality on installed base growth for a given product line. Using software quality measures from archival trade publication reviews, quality is found to have a positive and significant impact on growth, even after controlling for installed base size and other product, firm, and segment characteristics. This finding suggests that the first-mover advantages often ascribed to network industries may be more complex than previously thought. Rather, effective strategy in network competition appears to center on the trade-off between early product releases, with the intent of establishing an early installed base, and later product releases, with the intent of improving the quality of the focal product. Several potential extensions of this work are offered, with a specific focus on (1) the impact of variation in the strength of network effects across industries, and (2) the dueling incentives faced by incumbents in network industries, who may possess greater capabilities to produce high-quality products but limited incentive to do so. Other potential contributions for theory and practice are offered and discussed.

The measurement of software quality is an essential component in contemporary software development since it guarantees the dependability and effectiveness of software products. This article offers a comprehensive examination of the importance, aspects, and methodologies employed in the assessment of software quality. The paper commences by providing a comprehensive introduction to software quality and its different dimensions. It subsequently explores a range of measurement methods, which span both process and product metrics, as well as objective and subjective metrics. The literature review part presents a comprehensive categorization of various techniques for measuring software quality, offering a perceptive critique of the existing models. This study provides a comprehensive analysis of the difficulties and advantages associated with the implementation of software quality measurement. It offers unique perspectives on the typical obstacles faced during contemporary software quality evaluation. Moreover, the article showcases real-life applications and case studies that exemplify the practical utilisation of various measuring approaches. Through the examination of these applications, readers can gain a pragmatic comprehension of the implementation of software quality measurement in various contexts. The report finishes by elucidating emerging trends and proposing potential avenues for future research in the domain of software quality monitoring. The primary goal of this study is to examine innovations and identify prospective areas for further inquiry within the field of software quality assessment. The study places particular emphasis on future trends and innovations that have the potential to dramatically impact the domain of software quality assessment.