Engineering topics

Briand, Lionel

Publications and source records attributed to Briand, Lionel.

6 records

NASA NTRS1996

Understanding and Predicting the Process of Software Maintenance Releases

One of the major concerns of any maintenance organization is to understand and estimate the cost of maintenance releases of software systems. Planning the next release so as to maximize the increase in functionality and the improvement in quality are vital to successful maintenance management. The objective of this paper is to present the results of a case study in which an incremental approach was used to better understand the effort distribution of releases and build a predictive effort model for software maintenance releases. This study was conducted in the Flight Dynamics Division (FDD) of NASA Goddard Space Flight Center(GSFC). This paper presents three main results: 1) a predictive effort model developed for the FDD's software maintenance release process; 2) measurement-based lessons learned about the maintenance process in the FDD; and 3) a set of lessons learned about the establishment of a measurement-based software maintenance improvement program. In addition, this study provides insights and guidelines for obtaining similar results in other maintenance organizations.

Basili, Victor↗

NASA NTRS1995

Characterizing and Assessing a Large-Scale Software Maintenance Organization

One important component of a software process is the organizational context in which the process is enacted. This component is often missing or incomplete in current process modeling approaches. One technique for modeling this perspective is the Actor-Dependency (AD) Model. This paper reports on a case study which used this approach to analyze and assess a large software maintenance organization. Our goal was to identify the approach's strengths and weaknesses while providing practical recommendations for improvement and research directions. The AD model was found to be very useful in capturing the important properties of the organizational context of the maintenance process, and aided in the understanding of the flaws found in this process. However, a number of opportunities for extending and improving the AD model were identified. Among others, there is a need to incorporate quantitative information to complement the qualitative model.

Briand, Lionel↗

NASA NTRS1995

Goal-Driven Definition of Product Metrics Based on Properties

Defining product metrics requires a rigorous and disciplined approach, because useful metrics depend, to a very large extent, on one's goals and assumptions about the studied software process. Unlike in more mature scientific fields, it appears difficult to devise a "universal" set of metrics in software engineering, that can be used across application environments. We propose an approach for the definition of product metrics which is driven by the experimental goals of measurement, expressed via the Goal/Question/Metric (GQM) paradigm, and is based on the mathematical properties of the metrics. This approach integrates several research contributions from the literature into a consistent, practical and rigorous approach. The approach we outline should not be considered as a complete and definitive solution, but as a starting point for discussion about a product metric definition approach widely accepted in the software engineering community. At this point, we intend to provide an intellectual process that we think is necessary to define sound software product metrics. A precise and complete documentation of such an approach will provide the information needed to make the assessment and reuse of a new metric possible. Thus, product metrics are supported by a solid theory which facilitates their review and refinement. Moreover, their definition is made less exploratory and, as a consequence, one is less likely to identify spurious correlations between process and product metrics.

Briand, Lionel↗

NASA NTRS1995

Property-Based Software Engineering Measurement

Little theory exists in the field of software system measurement. Concepts such as complexity, coupling, cohesion or even size are very often subject to interpretation and appear to have inconsistent definitions in the literature. As a consequence, there is little guidance provided to the analyst attempting to define proper measures for specific problems. Many controversies in the literature are simply misunderstandings and stem from the fact that some people talk about different measurement concepts under the same label (complexity is the most common case). There is a need to define unambiguously the most important measurement concepts used in the measurement of software products. One way of doing so is to define precisely what mathematical properties characterize these concepts regardless of the specific software artifacts to which these concepts are applied. Such a mathematical framework could generate a consensus in the software engineering community and provide a means for better communication among researchers, better guidelines for analysis, and better evaluation methods for commercial static analyzers for practitioners. In this paper, we propose a mathematical framework which is generic, because it is not specific to any particular software artifact, and rigorous, because it is based on precise mathematical concepts. This framework defines several important measurement concepts (size, length, complexity, cohesion, coupling). It is not intended to be complete or fully objective; other frameworks could have been proposed and different choices could have been made. However, we believe that the formalism and properties we introduce are convenient and intuitive. In addition, we have reviewed the literature on this subject and compared it with our work. This framework contributes constructively to a firmer theoretical ground of software measurement.

Briand, Lionel↗

NASA NTRS1995

A Validation of Object-Oriented Design Metrics

This paper presents the results of a study conducted at the University of Maryland in which we experimentally investigated the suite of Object-Oriented (00) design metrics introduced by [Chidamber and Kemerer, 1994]. In order to do this, we assessed these metrics as predictors of fault-prone classes. This study is complementary to [Lieand 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 00 analysis/design method and the C++ programming language. Based on experimental results, the advantages and drawbacks of these 00 metrics are discussed and suggestions for improvement are provided. Several of Chidamber and Kemerer's 00 metrics appear to be adequate to predict class fault-proneness during the early phases of the life-cycle. We also showed that they are, on our data set, better predictors than "traditional" code metrics, which can only be collected at a later phase of the software development processes.

Basili, Victor R.↗

NASA NTRS1994

Building an experience factory for maintenance

This paper reports the preliminary results of a study of the software maintenance process in the Flight Dynamics Division (FDD) of the National Aeronautics and Space Administration/Goddard Space Flight Center (NASA/GSFC). This study is being conducted by the Software Engineering Laboratory (SEL), a research organization sponsored by the Software Engineering Branch of the FDD, which investigates the effectiveness of software engineering technologies when applied to the development of applications software. This software maintenance study began in October 1993 and is being conducted using the Quality Improvement Paradigm (QIP), a process improvement strategy based on three iterative steps: understanding, assessing, and packaging. The preliminary results represent the outcome of the understanding phase, during which SEL researchers characterized the maintenance environment, product, and process. Findings indicate that a combination of quantitative and qualitative analysis is effective for studying the software maintenance process, that additional measures should be collected for maintenance (as opposed to new development), and that characteristics such as effort, error rate, and productivity are best considered on a 'release' basis rather than on a project basis. The research thus far has documented some basic differences between new development and software maintenance. It lays the foundation for further application of the QIP to investigate means of improving the maintenance process and product in the FDD.

Valett, Jon D.↗