Software as a service

About: Software as a service is a research topic. Over the lifetime, 8514 publications have been published within this topic receiving 136177 citations. The topic is also known as: Service as a Software Substitute & SaaSS.

Metrics for managing customer view of software quality

Abstract: Traditional software metrics, such as code coverage, McCabe complexity, etc. address the needs of a software engineer. In contrast, managers of software development organizations face a broader set of issues. For example, an executive responsible for multiple products and releases has to understand the customer views of those products and put in place, appropriate actions across the products that will be of high business value. We present examples of data and metrics associated with service (i.e. product support) for field reported problems and customer critical situations, and customer satisfaction ratings across a comprehensive range of software product attributes. Issues arising in the data integration, analysis, and correlation of these metrics are highlighted. A systematic methodology for statistical analysis of the data that enables management to derive key, actionable drivers of change through the metrics is presented. We also present an outline of a decision support system developed at IBM for tracking and using software metrics to enable executives to make better informed decisions in supporting their products.

A Study of Project Management System Acceptance

Abstract: This study surveyed 497 project management software users in a wide variety of project-driven organizations to examine the relationships among: computer self-efficacy, information quality, system functionality, ease of use, project complexity, performance impact, organization size, project size, and user education, training and experience level. The findings indicated that information quality and project complexity are the dominant factors in explaining the levels of perceived system utilization; system functionality and ease of use have a significant effect on software usage; and that a strong relationship exists between perceptions of usage of software and project managers' performance. Inconsistent with prior research, training level was found to have no influence on project management software usage. However, software experience and education level had a moderate effect on the use of the software. Both organization size and project size had significant effects on the use of the software.

Sharing with a Difference: Realizing Service-Based SaaS Applications with Runtime Sharing and Variation in Dynamic Software Product Lines

Abstract: A single-instance multi-tenant (SIMT) SaaS application enables a SaaS provider to achieve economies of scale through runtime sharing. However, runtime sharing can make tenant-specific variations difficult to achieve in such an application. In this paper, we propose an approach to realizing SIMT SaaS applications, which is based on Dynamic Software Product Lines (DSPL) and supports runtime sharing and variation. With the collaboration among a subset of services as the unit of composition, the commonality among the tenants' requirements is realized in the DSPL architecture by sharing collaboration units, and their variability is realized by composing different collaboration units, all at runtime. In addition, we adopt a feature-based high-level representation of the commonality and variability between the tenants' requirements to facilitate the runtime creation and reconfiguration of their application variants. We compare our approach with two alternative approaches in terms of development effort and degree of sharing. We further quantify the runtime overhead incurred by our multi-tenancy support.

An Extensible Architecture for Detecting Violations of a Cloud Environment's Constraints during Legacy Software System Migration

Abstract: By utilizing cloud infrastructures or platforms as services, SaaS providers can counter fluctuating loads through smoothly scaling up and down and therefore improve resource- and cost-efficiency, or transfer responsibility for the maintenance of complete underlying software stacks to a cloud provider, for instance. Our model-based approach CloudMIG aims at supporting SaaS providers to semi-automatically migrate legacy software systems to the cloud. Thereby, the analysis of conformance with the specific constraints imposed by a cloud environment candidate along with the detection of constraint violations constitutes an important early phase activity. We present an extensible architecture for describing cloud environments, their corresponding constraints, and appropriate violation detection mechanisms. There exist predefined constraint types with specified domain semantics as well as generic variants for modeling arbitrary constraints. A software system's compliance can be examined with the assistance of so called constraint validators. They operate on discovered KDM-based models of a legacy system. Additional constraint validators can be plugged into the validation process as needed. In this context, we implemented a prototype and modeled the PaaS environment Google App Engine for Java. We report on a quantitative evaluation regarding the detected constraint violations of five open source systems.