Topic
Software metric
About: Software metric is a research topic. Over the lifetime, 10338 publications have been published within this topic receiving 253038 citations.
Papers published on a yearly basis
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Papers
Book•
2 Sep 2011TL;DR: This research addresses the needs for software measures in object-orientation design through the development and implementation of a new suite of metrics for OO design, and suggests ways in which managers may use these metrics for process improvement.
Abstract: Given the central role that software development plays in the delivery and application of information technology, managers are increasingly focusing on process improvement in the software development area. This demand has spurred the provision of a number of new and/or improved approaches to software development, with perhaps the most prominent being object-orientation (OO). In addition, the focus on process improvement has increased the demand for software measures, or metrics with which to manage the process. The need for such metrics is particularly acute when an organization is adopting a new technology for which established practices have yet to be developed. This research addresses these needs through the development and implementation of a new suite of metrics for OO design. Metrics developed in previous research, while contributing to the field's understanding of software development processes, have generally been subject to serious criticisms, including the lack of a theoretical base. Following Wand and Weber (1989), the theoretical base chosen for the metrics was the ontology of Bunge (1977). Six design metrics are developed, and then analytically evaluated against Weyuker's (1988) proposed set of measurement principles. An automated data collection tool was then developed and implemented to collect an empirical sample of these metrics at two field sites in order to demonstrate their feasibility and suggest ways in which managers may use these metrics for process improvement. >
6,169 citations
Book•
1 Jan 2013
TL;DR: The Second Edition of Software Metrics provides an up-to-date, coherent, and rigorous framework for controlling, managing, and predicting software development processes.
Abstract: From the Publisher:
The Second Edition of Software Metrics provides an up-to-date, coherent, and rigorous framework for controlling, managing, and predicting software development processes. With an emphasis on real-world applications, Fenton and Pfleeger apply basic ideas in measurement theory to quantify software development resources, processes, and products. The book offers an accessible and comprehensive introduction to software metrics, now an essential component of software engineering for both classroom and industry. Software Metrics features extensive case studies from Hewlett Packard, IBM, the U.S. Department of Defense, Motorola, and others, in addition to worked examples and exercises. The Second Edition includes up-to-date material on process maturity and measurement, goal-question-metric, planning a metrics program, measurement in practice, experimentation, empirical studies, ISO9216, and metric tools.
3,164 citations
1 Jan 1994
TL;DR: Measurement is a mechanism for creating a corporate memory and an aid in answering a variety of questions associated with the enactment of any software process.
Abstract: As with any engineering discipline, software development requires a measurement mechanism for feedback and evaluation. Measurement is a mechanism for creating a corporate memory and an aid in answering a variety of questions associated with the enactment of any software process. It helps support project planning (e.g., How much will a new project cost?); it allows us to determine the strengths and weaknesses of the current processes and products (e.g., What is the frequency of certain types of errors?); it provides a rationale for adopting/refining techniques (e.g., What is the impact of the technique XX on the productivity of the projects?); it allows us to evaluate the quality of specific processes and products (e.g., What is the defect density in a specific system after deployment?). Measurement also helps, during the course of a project, to assess its progress, to take corrective action based on this assessment, and to evaluate the impact of such action.
2,055 citations
TL;DR: Several of Chidamber and Kemerer's OO metrics appear to be useful to predict class fault-proneness during the early phases of the life-cycle and are better predictors than "traditional" code metrics, which can only be collected at a later phase of the software development processes.
Abstract: This paper presents the results of a study in which we empirically investigated the suite of object-oriented (OO) design metrics introduced in (Chidamber and Kemerer, 1994). More specifically, our goal is to assess these metrics as predictors of fault-prone classes and, therefore, determine whether they can be used as early quality indicators. This study is complementary to the work described in (Li and Henry, 1993) where the same suite of metrics had been used to assess frequencies of maintenance changes to classes. To perform our validation accurately, we collected data on the development of eight medium-sized information management systems based on identical requirements. All eight projects were developed using a sequential life cycle model, a well-known OO analysis/design method and the C++ programming language. Based on empirical and quantitative analysis, the advantages and drawbacks of these OO metrics are discussed. Several of Chidamber and Kemerer's OO metrics appear to be useful to predict class fault-proneness during the early phases of the life-cycle. Also, on our data set, they are better predictors than "traditional" code metrics, which can only be collected at a later phase of the software development processes.
1,903 citations
TL;DR: The ability to create and deploy reproducible environments across these centers, a previously unmet need, makes Singularity a game changing development for computational science.
Abstract: Here we present Singularity, software developed to bring containers and reproducibility to scientific computing. Using Singularity containers, developers can work in reproducible environments of their choosing and design, and these complete environments can easily be copied and executed on other platforms. Singularity is an open source initiative that harnesses the expertise of system and software engineers and researchers alike, and integrates seamlessly into common workflows for both of these groups. As its primary use case, Singularity brings mobility of computing to both users and HPC centers, providing a secure means to capture and distribute software and compute environments. This ability to create and deploy reproducible environments across these centers, a previously unmet need, makes Singularity a game changing development for computational science.
1,788 citations
Related Topics (5)
Performance Metrics
| Year | Papers |
|---|---|
| 2025 | 9 |
| 2024 | 33 |
| 2023 | 59 |
| 2022 | 128 |
| 2021 | 114 |
| 2020 | 171 |