Improving Quality and Cost-Effectiveness in Enterprise Software Application Development: An Open, Holistic Approach for Project Monitoring and Control (original) (raw)

Case studies of software-process-improvement measurement

Computer, 1994

Siemens softwaredevelopment organizations are casestudy sites in a research project with the Software Engineering Institute. The effort has yielded suggestions for promoting softwareprocess improvement. oftware measurement is becoming integral to improving software development. The approach begins with a documented software-development process. A business enterpriseon the basis of its strategic objectivesestablishes goals to improve the process over a specified period of time. Then it defines measures to periodically gauge progress in achieving the improvement goals. When the data collected indicates development-process problems, the enterprise can formulate corrective actions and compare them to determine the best return on investment for software-process improvement. Figure 1 shows how measures play a key role in a closed-loop feedback mechanism for incremental improvements to the software-development process over time.' These process improvements result in higher quality products, thus increasing the business enterprise's competitiveness. In this article, we describe an ongoing research project conducted jointly by Siemens and the Software Engineering Institute. Siemens software-development organizations in Germany and the United States are case-study sites at which we measure the effect of methods to improve the software-development process. To observe and quantify the impact of software-process improvement, we must measure the performance of a software-development organization over time. Comparison of performance across organizations is very difficult, since organizations define measures and collect performance data in different ways. However, we can separately track performance improvement in each organization if it defines measures consistently and develops similar products. We have defined basic measures for performance of a software-development organization. We limited ourselves to a small number of simple measures to reduce the complexity of collecting, analyzing, and maintaining the performance data. Improving the software-development process improves the quality of software products and the overall performance of the software-development organization? However, as Figure 2 shows? process is only one of several controllable factors in improving software quality and organization performance. Others include the skills and experience of the people developing the software, the technology used (for example, CASE tools), product complexity, and environmental characteristics such as schedule pressure and communications.

QualitySpy: a framework for monitoring software development processes

The growing popularity of highly iterative, agile processes creates increasing need for automated monitoring of the quality of software artifacts, which would be focused on short terms (in the case of eXtreme Programming process iteration can be limited to one week). This paper presents a framework that calculates software metrics and cooperates with development tools (e.g. source version control system and issue tracking system) to describe current state of a software project with regard to its quality. The framework is designed to support high level of automation of data collection and to be useful for researchers as well as for industry. The framework is currently being developed hence the paper reports already implemented features as well as future plans. The first release is scheduled for July.

A Framework for Effective Software Monitoring in Project Management

2014

Developed software for project management rely heavily on collecting metrics to provide the progress feedback necessary to allow control of the project. However, interpretation of this data is very difficult and sometimes cumbersome. This paper addressed the need of a software implementation progress model that is needed to help interpret the accumulated data. Certain criteria are set for design of a proposed implementation progress model. Some findings from the studied projects from other researchers suggest the model is consistent with the observed behaviour. In addition to quantitative validity, the model is shown to provide meaningful interpretation of collected metric data by embedding certain quality function.

Event-Based Monitoring of Open Source Software Projects

2007

Project management traditionally has a strong focus on human reporting that fits well a tightly coupled form of organization to ensure the quality of project reporting. For loosely coupled forms of organization, such as open source systems (OSS) development projects, there are very few approaches to ensure the quality of project reporting; a promising approach can be to augment human reporting with data analysis based on the communication and state changes in an OSS project.

Measurement of Processes in Open Source Software Development

Trends in Information Management, 2012

Purpose: This paper attempts to present a set of basic metrics which can be used to measure basic development processes in an OSS environment. Design/Methodology/Approach: Reviewing the earlier literature helped in exploring the metrics for measuring the development processes in OSS environment. Results: The OSSD is different from traditional software development because of its open development environment. The development processes are different and the measures required to assess them have to be different.

MMT: A Tool for Observing Metrics in Software Projects

Int. J. Hum. Cap. Inf. Technol. Prof., 2017

This paper presents the Metrics Monitoring Tool MMT that was developed in university graduate and undergraduate courses on software project work in 2014-2016. The tool aims to support project members, project managers and upper management in reporting and monitoring software and project metrics for their easier and more effective utilization. The paper covers the development process of the tool, evaluation assessment, its current composition and features. The paradigm applied in this study is Design Science Research and the methods for evaluation include prototype, expert evaluation, case study and technical experiment. Data was collected from the tool users by two questionnaires. As a result, MMT was evaluated to ease the metrics handling, while several aspects related to the richness of functionalities and usability still require further development.

Monitoring Software Projects with SQuORE

2012

Quality has a price. But non-quality is even more expensive. Knowing the cost and consequences of software assets, being able to understand and control the development process of a service, or quickly evaluating the quality of external developments are of primary importance for every company relying on software. Standards and tools have tried with varying degrees of success to address these concerns, but there are many difficulties to be overcome: the diversity of software projects, the measurement processfrom goals and metrics selection to data presentation, or the user's understanding of the reports. These are situations where the SQuORE business intelligence tool introduces a novel decision-based approach to software projects quality assessment by providing a more reliable, more intuitive, and more context-aware view on quality. This in turn allows all actors of the project to share a common vision of the project progress and performance, which then allows efficient enhancing of the product and process. This position paper presents how SQuORE solves the quality dilemma, and showcases two real-life examples of industrial projects: a unit testing improvement program, and a fully-featured software project management model.

OSSMETER: a software measurement platform for automatically analysing open source software projects

Proceedings of the 2015 10th Joint Meeting on Foundations of Software Engineering, 2015

Deciding whether an open source software (OSS) project meets the required standards for adoption in terms of quality, maturity, activity of development and user support is not a straightforward process as it involves exploring various sources of information. Such sources include OSS source code repositories, communication channels such as newsgroups, forums, and mailing lists, as well as issue tracking systems. OSSMETER is an extensible and scalable platform that can monitor and incrementally analyse a large number of OSS projects. The results of this analysis can be used to assess various aspects of OSS projects, and to directly compare different OSS projects with each other.