2,975 research outputs found
A research review of quality assessment for software
Measures were recommended to assess the quality of software submitted to the AdaNet program. The quality factors that are important to software reuse are explored and methods of evaluating those factors are discussed. Quality factors important to software reuse are: correctness, reliability, verifiability, understandability, modifiability, and certifiability. Certifiability is included because the documentation of many factors about a software component such as its efficiency, portability, and development history, constitute a class for factors important to some users, not important at all to other, and impossible for AdaNet to distinguish between a priori. The quality factors may be assessed in different ways. There are a few quantitative measures which have been shown to indicate software quality. However, it is believed that there exists many factors that indicate quality and have not been empirically validated due to their subjective nature. These subjective factors are characterized by the way in which they support the software engineering principles of abstraction, information hiding, modularity, localization, confirmability, uniformity, and completeness
Annotated bibliography of software engineering laboratory literature
An annotated bibliography of technical papers, documents, and memorandums produced by or related to the Software Engineering Laboratory is given. More than 100 publications are summarized. These publications cover many areas of software engineering and range from research reports to software documentation. This document has been updated and reorganized substantially since the original version (SEL-82-006, November 1982). All materials have been grouped into eight general subject areas for easy reference: the Software Engineering Laboratory; the Software Engineering Laboratory-software development documents; software tools; software models; software measurement; technology evaluations; Ada technology; and data collection. Subject and author indexes further classify these documents by specific topic and individual author
Annotated bibliography of Software Engineering Laboratory literature
An annotated bibliography of technical papers, documents, and memorandums produced by or related to the Software Engineering Laboratory is given. More than 100 publications are summarized. These publications cover many areas of software engineering and range from research reports to software documentation. All materials have been grouped into eight general subject areas for easy reference: The Software Engineering Laboratory; The Software Engineering Laboratory: Software Development Documents; Software Tools; Software Models; Software Measurement; Technology Evaluations; Ada Technology; and Data Collection. Subject and author indexes further classify these documents by specific topic and individual author
Using neural networks in software repositories
The first topic is an exploration of the use of neural network techniques to improve the effectiveness of retrieval in software repositories. The second topic relates to a series of experiments conducted to evaluate the feasibility of using adaptive neural networks as a means of deriving (or more specifically, learning) measures on software. Taken together, these two efforts illuminate a very promising mechanism supporting software infrastructures - one based upon a flexible and responsive technology
Modeling the object-oriented software process: OPEN and the unified process
A short introduction to software process modeling is presented, particularly object-oriented modeling. Two major industrial process models are discussed: the OPEN model and the Unified Process model. In more detail, the quality assurance in the Unified Process tool (formally called Objectory) is reviewed
MANAGING DEVELOPMENT PRODUCTIVITY OF THE COMPUTER AIDED SOFTWARE ENGINEERING (CASE) PROCESS WITH DYNAMIC LIFE CYCLE TRAJECTORY METRICS
This paper proposes a new vision for the measurement and
management of development productivity related to computer aided
software engineering (CASE) technology. We propose that they be
monitored and controlled via the application of dynamic software
development "life cycle trajectory metrics." This view develops
out of management accounting approaches for process control and
recent advances in CASE technology that make automated
measurement possible. We suggest that current approaches involve
the use of "static metricsâ for estimation and evaluation, with
the result that the depth of the insights they can provide to
management is necessarily limited. They only provide "point
estimatesâ of output or productivity at the beginning and end of
the project. Yet to manage software development proactively for
improved efficiency and effectiveness, management needs to track
the range of activities and effort across the entire software
development life cycle. This can only be accomplished when
timely and relevant information is obtained about the software
size output, as well as costs, via âdynamic metrics,â which
provide a richer phase-by-phase view.Information Systems Working Papers Serie
Assessing the Reuse Potential of Objects.
In this research, we investigate whether reusable classes can be characterized by object-oriented (OO) software metrics. Three class-level reuse measures for the OO paradigm are defined: inheritance-based reuse, inter-application reuse by extension, and inter-application reuse as a server. Using data from a software company, we collected metrics on Smalltalk classes. Among the 20 metrics collected are cyclomatic complexity, Lorenz complexity, lines of code, class coupling, reuse ratio, specialization ratio and number of direct subclasses. We used stepwise regression to derive prediction models incorporating the 20 metrics as the independent variables and the reuse measures, applied separately, as the dependent variable. Inheritance-based reuse and inter-application reuse by extension can be predicted using a subset of the 20 metrics. Two prediction models for inheritance-based reuse and inter-application reuse by extension were validated using a new set of 310 Smalltalk and VisualAge applications and subapplications. Validation results show that it is possible to predict whether a class from one application can be reused by extension in another application. We also conducted a t-test to test whether the mean metric values between reusable and non-reusable classes are the same. Results suggest that there exists significant differences in the mean metric values between the reusable and non-reusable classes
TRACKING THE 'LIFE CYCLE TRAJECTORY': METRICS AND MEASURES FOR CONTROLLING PRODUCTIVITY OF COMPUTER AIDED SOFTWARE ENGINEERING (CASE) DEVELOPMENT
This paper proposes a new vision for the measurement and
management of development productivity related to computer aided
software engineering (CASE) technology. We propose that
productivity be monitored and controlled in each phase of
software development life cycle, a measurement approach we have
termed life cycle trajectory measurement. Recent advances in
CASE technology that make low cost automated measurement possible
have made it feasible to collect life cycle trajectory measures.
We suggest that current approaches for productivity management
involve the use of static metrics that are available only at the
beginning and end of the project. Yet the depth of the insights
needed to make proactive adjustments in the software development
process requires monitoring the range of activities across the
entire software development life cycle. This can only be
accomplished with metrics that can measure performance parameters
in each phase of the life cycle. We develop metrics that have
the ability to measure and estimate software outputs from each
intermediate phase of the development life cycle. These metrics
are based on a count of the objects and modules that are used as
building blocks for application development in repository object-based
CASE environments. The viability of such object-based
metrics for life cycle trajectory measurement has been
empirically tested for the software construction phase using
project data generated in Integrated CASE development
environments.Information Systems Working Papers Serie
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