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The article describes 7 types of metrics and more than 50 their representatives, provides a detailed description and calculation algorithms used. It also touches upon the role of metrics in software development.

For some time the software industry has espoused the need for improved specification-based software size metrics. This paper reports on a study of nineteen recently developed systems in a variety of application domains. The systems were developed by a single software services corporation using a variety of languages. The study investigated several metric characteristics. It shows that: earlier research into inter-item correlation within the overall function count is partially supported; a priori function counts, in themself, do not explain the majority of the effort variation in software development in the organization studied; documentation quality is critical to accurate function identification; and rater error is substantial in manual function counting. The implication of these findings for organizations using function based metrics are explored.

Includes bibliographical references (p. 21-23)

This report covers the period from 1 June 1978, to 31 May 1979, during which the second of three phases was completed. This phase concentrated on the augmentation of the Program Testing Translator described in the Final Report on AFOSR F44620-74-C-008 of December 1976. The augmentation permits formation of links of greater length than those previously used. It also alleviates the process of composing the tracks of execution sequences, a requirement for establishing an automatic record of the status of testing. Applications have been made to an Air Force logistics model (Optimum Repair Level Analysis-ORLA). In these applications tests were made with the purpose of successively increasing the count of exercised tracks. Because there are numerous user-selected options the count so obtained was not truly indicative of the data base's effect on testing. Nonetheless progress has been made in determining the way to process programs automatically in the way indicated in the Annual Report for the preceding period. (Author)

In its role as an agent for improving software technology use within the U.S. Air Force, the Software Technology Support Center (STSC) is supporting metrics technology improvement activities for its customers. These activities include: disseminating information regarding the U.S. Air Force Policy on software metrics, providing metrics information to the public through CrossTalk, conducting customer workshops in software metrics, guiding metrics technology adoption programs at customer locations, researching new and evolving metrics methodologies, etc. This guide covers the following: (a) It defines a metrics capability evaluation method that deals specifically with defining a customer's metrics capability. (b) It presents metrics capability questionnaires that help gather metrics capability data. (c) It outlines a metrics capability evaluation report that provides the basis for developing a metrics customer project plan. (d) It provides a metrics customer profile form used to determine the initial information required to prepare for a metrics capability evaluation. (e) It provides a customer organization information form that helps guide the STSC in gathering cultural information about the organization that will help with developing and implementing the metrics customer project plan.

The purpose of this handbook is threefold. Specifically, it: (1) Serves as a reference guide for implementing standard software reliability practices at Marine Corps Tactical Systems Support Activity and aids in applying the software reliability model. (2) Serves as a tool for managing the software reliability program. (3) Serves as a training aid.

The Clinger-Cohen Act of 1996 requires performance measurement of information technology systems. Measuring the performance of program management for the Chemical Accountability Management Information Network (CAMIN) system requires a thoughtful selection of useful metrics. The CAMIN is a complex Management Information System in the post deployment software system (PDSS) phase of the system life cycle. This research uses three primary sources for candidate metrics for a PDSS like CAMIN: 1) typical software metrics from DoD and commercial applications, 2) typical fielded software system metrics from DoD and commercial applications, and 3) case analysis of metrics currently used by CAMIN and other DoD systems in the PDSS phase. Analysis of these candidate metrics creates a concise list of combined metrics that are applicable to fielded software systems. The current primary issues of CAMIN program management establish the basis for selection of appropriate program management metrics from the candidate list. These issues are examined in a process to answer the primary research question, What are appropriate metrics and measures for management of the Chemical Accountability Management Information Network?

Thesis advisor(s): David F. Matthews, Mark E. Nissen

This paper attempts to characterize and present a state of the art view of several quantitative models and metrics of the software life cycle. These models and metrics can be used to aid in managing and engineering software projects. They deal with various aspects of the software process and product, including resources allocation and estimation, changes and errors, size, complexity and reliability. Some indication is given of the extent to which the various models have been used and the success they have achieved.

Effective management of any process requires quantification, measurement, and modeling. Software metrics provide a quantitative basis for the development and validation of models of the software development process. Metrics can be used to improve software productivity and quality. This module introduces the most commonly used software metrics and reviews their use in constructing models of the software development process. Although current metrics and models are certainly inadequate, a number of organizations are achieving promising results through their use. Results should improve further as we gain additional experience with various metrics and models.

There are many metrics for gauging software during the several phases of development, but each leaves questions about the quality and maintainability of the software. A new metric is proposed which may overcome some of these problems while giving a strong intuitive model for gauging development progress through design, coding, and testing. A proposal is made for the collection of data for testing and evaluation of this model. (Author).

Different metrics are useful for different purposes and at different times in the life cycle of a software development project. For example, project managers need measures to predict resources and schedules, to track costs and to locate potential problem areas. These needs differ from those of a customer or end user who would like some measure of the reliability of the system and proof of the thoroughness of the testing that has been done. Still different are the needs of a programmer who would benefit from feedback about the complexity of a just-compiled module. The problem of defining a unified set of metrics is not simple and straightforward. This paper will describe the software project selected, the data collection effort and the candidate metrics that are being considered.

Software metrics (or measurements) which predict software quality have been refined and enhanced. Metrics were classified as anomaly-detecting metrics which identify deficiencies in documentation or source code, predictive metrics which measure the logic of the design and implementation, and acceptance metrics which are applied to the end product to assess compliance with requirements. A Software Quality Measurement Manual was produced which contained procedures and guidelines for assisting software system developers in setting quality goals, applying metrics and making quality assessments.

Software metrics (or measurements) which predict software quality have been refined and enhanced. Metrics were classified as anomaly-detecting metrics which identify deficiencies in documentation or source code, predictive metrics which measure the logic of the design and implementation, and acceptance metrics which are applied to the end product to assess compliance with requirements. A Software Quality Measurement Manual was produced which contained procedures and guidelines for assisting software system developers in setting quality goals, applying metrics and making quality assessments.

The Software Supportability Qualitative Assessment Methodology is a five volume reference set that provides measures to aid in the support of information systems. The volumes are aimed at improving the support process by more accurately assessing the capabilities of support organizations, qualitatively measuring the supportability of fielded systems and evaluating the operational readiness of fielded systems. The five volumes are: (1) Developing Quality Measures for Information Systems Support; (2) The Review of Metrics for Developing an Information Systems Support Measurement Framework; (3) Implementing the Software Supportability Measure; (4) Implementing the Support Organization Assessment Measure; and (5) Implementing the Operational Readiness Measure. This volume provides a survey and evaluation of current metrics in terms of information systems support. Specifically, three classes of metrics are reviewed: software product metrics, life cycle process metrics, and process management metrics.

The Rome Air Development Center has developed the Software Quality Framework as a means to specify software quality goals and measure software quality. Much of the work to date has focused on metrics applicable to software code. This report describes an effort undertaken to measure the quality of software products earlier in the software development life cycle, during the design phase, and to automate the capture of metric data from design media. Metrics of software quality, primarily those related to the criterion simplicity (or conversely, complexity), were reviewed. This review includes those metrics previously developed in the Software Quality Framework. Two metrics, Halstead's Software Science and McCabe's Cyclomatic Complexity were chosen for their amenability to measurement during design and their potential for automation. Two design media were used: Design Aids for Real-Time Systems, an experimental automated design tool developed at the Charles Stark Draper Laboratory; and Ada as a program design language.

The main purpose of this thesis is to theoretically investigate the effect of reusing software on metrics that are based on the entropy function of communication information theory. R. Chanon's Entropy Loading and E. Chen's Control Structure Entropy were applied to C and Ada programs obtained from the open literature. Four units of program decomposition (statement, component, module, and program) along Chanon's definition of an object were introduced to classify software reuse units. A total of three versions for each of the programs included in the study were considered (i.e., optimum reuse, intermediate reuse, and no reuse). The lines of code metric was utilized to quantify the amount of nonreusable code in each of the versions of the programs. The lines of code metric was not applied to the 'reused' segments of code since they are not considered part of the effort of writing the new program. Pearson product-moment correlations were computed between the metrics studied and the lines of code metric. (kr)

The paper captures the project management experience of using process metrics to measure the development of a large software system for the U.S. government. The Command Center Processing and Display System-Replacement (CCPDS- R) program is a development effort consisting of three subsystems and over 6000, 000 lines of Ada source code executing in a distributed Digital Equipment Corporation VAX VMS environment. The initial subsystem called the Command Subsystem, consists of over 3000,000 lines of Ada source code and is 2 years into development with a successful Critical Design Review (CDR) held at month 25 of the contract. Utilizing the new Ada process model, over 280,000 lines of Ada source code have been developed and integrated into a working demonstration on the operational hardware. This approach has permitted the validation of the software design, allowed early analysis and resolution of the software performance issues, and provided extensive insight into the usability and flexibility of the system for the user community. This first program use of the incremental, demonstration based process model with related software metrics has been totally successful. The technology now is being transferred to other projects within the company. The U.S. Government acquisition agency has designated CCPDS-R as its flagship program and is basing new acquisitions on the approach utilized by the CCPDS-R program.

Moving software development into the engineering arena requires controllability, and to control a process, it must be measurable. Measuring the process does no good if the product is not also measured, i.e., being the best at producing an inferior product does not define a quality process. Also, not every number extracted from software development is a valid measurement. A valid measurement only results when we are able to verify that the number is representative of the attribute that we wish to measure. Many proposed software metrics are used by practitioners without these metrics ever having been validated, leading to costly but often useless calculations. Several researchers have bemoaned the lack of scientific precision in much of the published software measurement work and have called for validation of software metrics by measurement theory. This dissertation applies measurement theory to validate fifty proposed object-oriented software metrics.

Presentation of research abstract for CS632 on the importance of implementing a standard software development process and a metrics program in tandem to drive continuous improvement.

Presentation of research abstract for CS632 on the importance of implementing a standard software development process and a metrics program in tandem to drive continuous improvement.

DAISY text only version of Software Metrics This new edition of this invaluable reference brings the coverage of software metrics fully up to date. The book has been rewritten and redesigned to take into account the fast changing developments in software metrics, most notably their widespread penetration into industrial practice. New sections deal with prcess maturity and measurement, goal-question-metric, metrics plans, experimentation, empirical studies, object-oriented metrics, and metrics tools. 88 line illustrations.

Cover title

Today's software is extremely complex, often constituting millions of lines of instructions. Programs are expected to operate smoothly on a wide variety of platforms. There are continuous attempts to try to assess what the reliability of a software package is and to predict what the reliability of software under development will be. The quantitative aspects of these assessments deal with evaluating, characterizing and predicting how well software will operate. Experience has shown that it is extremely difficult to make something as large and complex as modern software and predict with any accuracy how it is going to behave in the field. This thesis proposes to create an integrated system to predict software reliability for mission critical systems. This will be accomplished by developing a flexible DBMS to track failures and to integrate the DBMS with statistical analysis programs and software reliability prediction tools that are used to make calculations and display trend analysis. It further proposes a software metrics model for fault prediction by determining and manipulating metrics extracted from the code.

Due to the large number of product, project and people parameters which impact large custom software development efforts, measurement of software product quality is a complex undertaking. Furthermore, the absolute perspective from which quality is measured (customer satisfaction) is intangible. While we probably can't say what the absolute quality of a software product is, we can determine the relative quality, the adequacy of this quality with respect to pragmatic considerations, and identify good and bad trends during development. While no two software engineers will ever agree on an optimum definition of software quality, they will agree that the most important perspective of software quality is its ease of change. We can call this flexibility, adaptability or some other vague term, but the critical characteristic of software is that it is soft. The easier the product is to modify, the easier it is to achieve any other software quality perspective. This paper presents objective quality metrics derived from consistent lifecycle perspectives of rework which, when used in concert with an evolutionary development approach, can provide useful insight to produce better quality per unit cost/schedule or to achieve adequate quality more efficiently.

The levels of quality, maintainability, testability, and stability of software can be improved and measured through the use of automated testing tools throughout the software development process. Automated testing tools assist software engineers to gauge the quality of software by automating the mechanical aspects of the software-testing task. Automated testing tools vary in their underlying approach, quality, and ease-of-use, among other characteristics. Evaluating available tools and selecting the most appropriate suite of tools can be a difficult and time-consuming process. In this thesis, we propose a suite of objective metrics for measuring tool characteristics, as an aide in systematically evaluating and selecting automated testing tools. Future work includes further research into the validity and utility of this suite of metrics, conducting similar research using a larger software project, and incorporating a larger set of tools into similar research.

This report presents a proposed plan for DoD implementation of software metrics in support of acquisition reform and improved software risk management. The report documents the concluding phase of a one-year task to assess software metrics and to determine how to improve their use in software acquisition, particularly of weapon system software. An earlier effort surveyed the state of development and use of software metrics in industry and defense organizations. This survey found 1) that industry is strongly committed to using software metrics in a corporate-wide approach to gain marketplace advantages, and 2) that defense contractors exhibit a state of evolution in metrics use that is comparable to that of strictly commercial companies, if not more mature. The overall vision of the proposed plan is to establish a department-wide, bottom-to-top corporate approach for collecting and using software metrics to improve analysis and decision-making in software acquisition and risk management. Acquisition reform and the need for improved risk management should provide more specific goals to address under this vision, comparable to industry's goals of marketplace benefits from using software metrics. The plan is framed as eight specific recommendations, including a list of future research and development work that would support their implementation.

This report documents the efforts and portrays the findings and recommendations of the Army Software Test and Evaluation Panel (STEP) Subgroup on measures. The final recommendations include the mandatory use of a minimum, common set of software metrics in order to better measure and manage software development from the test and evaluation perspective. This set of measures should be used to help determine whether the system under consideration has demonstrated the necessary functionality, maturity, and readiness to proceed to the next stage of development or testing. This set of metrics is a minimum set; other metrics of specific interest to a certain agency or point of view can and should be collected if desired. Of course, there are many characteristics of the software that need to be evaluated for quality and conformance but do not lend themselves to measurement. These quality factors remain important to any evaluation of software. Metrics are simply one element of a set of tools that should be used in a software evaluation

This paper presents a set of software management metrics that have been developed by the ESD/MITRE Software Center. The metrics are designed to assist in monitoring the progress of software development by gaining better visibility into the software acquisition process. This revision reflects government and industry comments on the previous version, and includes new charts, information on application of the metrics, and appendices containing generic and sample data items. This document is intended to help Project Managers prepare software development status reports. System Program Officers (SPOs) are expected to use these metrics to augment conventional acquisition system development reports such as cost and schedule reports. Section II presents each metric. Section III discusses application of the metrics. Section IV describes continuing work efforts in the area of software status monitoring and metrics.

Software development efforts have become the highest-risk element of modern program management. One way that we can mitigate this risk is through the use of metrics. Software metrics can give us insight about the progress, quality, and expected completion of a software development effort. In earlier software development efforts, programming was viewed as a "black art" and, consequently, software metrics were not commonly used. Today, it is generally accepted that a software development effort should be properly planned and that software metrics should be used to control the project. Program managers are no longer concerned about whether or not to use metrics, but are more concerned with which metrics to use and whether or not the ones chosen will be effective. The Bradley Fighting Vehicle A3 Program provides valuable insight into the use of metrics. A principal finding of this research is that implementing an effective metrics program is extremely difficult, especially when the contractor is not experienced in developing software-intensive systems. Because this situation often exists, future and current program managers must assess their own knowledge of software development and plan to mitigate the effects of other factors they cannot influence. They must educate themselves on software issues and metrics and solicit assistance from independent agencies that specialize in software development.

One way to increase the quality of software products and the productivity of software development is to reuse existing software components when building new software systems. In order to monitor improvements in reuse, the level of reuse must be measured. In this NASA supported project we (1) derived a suite of metrics which quantify reuse attributes for object oriented, object based, and procedural software, (2) designed prototype tools to take these measurements in Ada, C++, Java, and C software, (3) evaluated the reuse in available software, (4) analyzed the relationship between coupling, cohesion, inheritance, and reuse, (5) collected object oriented software systems for our empirical analyses, and (6) developed quantitative criteria and methods for restructuring software to improve reusability.

The objective of this study was to determine the relative utility of selected software requirement metrics in assessing the productivity of the software requirements analysis process and the quality of the products of this process. This objective was met by collecting information about the perceptions that practicing software professionals have of the usefulness of various requirement metrics. The study employed a two part methodology. The first part utilized Basili's goal/question/metric paradigm to identify specific goals of the measurement effort and to identify requirement metrics worthy of further investigation. The second part employed a typical research design to gather perceptions that software professionals have of the utility of several metrics selected from those identified earlier. The study produced inconclusive results and further research is recommended. Results were based on a small sample and the data only reiterated the mixed opinions that software professionals have of the usefulness of software metrics. One significant finding is the consensus that a metric must be precisely defined for it to be accepted by the software community.

In this paper, we describe our experience implementing some of classic software engineering metrics using Boa - a large-scale software repository mining platform - and its dedicated language. We also aim to take an advantage of the Boa infrastructure to propose new software metrics and to characterize open source projects by software metrics to provide reference values of software metrics based on large number of open source projects. Presented software metrics, well known and proposed in this paper, can be used to build large-scale software defect prediction models. Additionally, we present the obstacles we met while developing metrics, and our analysis can be used to improve Boa in its future releases. The implemented metrics can also be used as a foundation for more complex explorations of open source projects and serve as a guide how to implement software metrics using Boa as the source code of the metrics is freely available to support reproducible research.

Thesis advisors, Donald P. Gaver and Norman F. Schneidewind

Thesis advisors, Donald P. Gaver and Norman F. Schneidewind

In the context of critical applications, such as shielding and radiation protection, ensuring the quality of simulation software they depend on is of utmost importance. The assessment of simulation software quality is important not only to determine its adoption in experimental applications, but also to guarantee reproducibility of outcome over time. In this study, we present initial results from an ongoing analysis of Geant4 code based on established software metrics. The analysis evaluates the current status of the code to quantify its characteristics with respect to documented quality standards; further assessments concern evolutions over a series of release distributions. We describe the selected metrics that quantify software attributes ranging from code complexity to maintainability, and highlight what metrics are most effective at evaluating radiation transport software quality. The quantitative assessment of the software is initially focused on a set of Geant4 packages, which play a key role in a wide range of experimental applications and are representative of different software development processes. We provide an interpretation of the data resulting from measurements on the selected Geant4 packages, and discuss methods to improve them. This work can be used as a baseline for evaluating correlations between software quality embedded in the Geant4 development process and simulation observables produced by Geant4-based applications. The result provide constructive guidance both to improve key software tools, such as Geant4, and to estimate their contribution in risk analyses concerning sensitive applications.

There is growing concern over the frequent cases of cost overruns, and underestimation in software cost, especially, indigenous software products. This has a lot to do with the choice of Cost-estimation tools, techniques and models deployed. Constructive Cost Model (COCOMO) II model has been adjudged as the most reliable and accurate. However, the existing cost drivers/variables of this model (COCOMO II) do not capture fully the uniqueness of Nigeria’s computing environment. This paper has highlighted the strengths and weaknesses of COCOMO II considering the hierarchy of COCOMO. A new algorithm was proposed to effectively enhance the cost estimation effort of indigenous software in Nigeria

The expense of maintaining software is greater than any other phase in the life cycle. To help reduce the costs, software which may not be maintainable should be identified before being released for use. Measures of software quality, or metrics, may be able to help do this. The goal of this thesis was to identify measures which could indicate the maintainability of JOVIAL (J73) software, and to implement selected ones. Maintainability cannot be measured directly, so a strong indicator, complexity, was measured instead. Five categories of complexity metrics were reviewed: size, control, data, information, and hybrid. Through an analysis of metrics from each category, the information metric was selected for implementation. Using Ada as the implementation language, an analyzer to compute the information metric was constructed. The design was primarily object-oriented but was influenced by compiler theory. The resulting analyzer can easily incorporate new metrics or new input/output requirements. Testing was performed using both simple code examples and actual F-16 flight software. The analyzer properly computes the information metric with few exceptions. A plan to compare the results of the analyzer with the results of the sponsor's present manual review was described.

The software required to test FORTRAN programs, first with random numbers and then by preselected constructed cases, was developed during this interval. Software modifications were made to permit performance measurements of the degree of coverage to include the results due to the use of constructed cases. The automation of the mix of random numbers and constructed cases was studied and limitations were found. Two new models for use during the development phase of programming were developed. These models apply to programs which grow in size during the debugging period.

This document presents the findings of the TTCP Workshop on Software Metrics held on 21-24 May 90 at Rochester Institute of Technology in Rochester, NY. The workshop was hosted by the Air Force Systems Command's Rome Laboratory and sponsored by The Technical Cooperation Program (TTCP). The workshop brought together experts from gov't, industry and academia to examine the state-of-the- art and state-of-the-practice of software measurement technology and to share ideas and develop recommendations for further development and application of software metrics. Four panels were convened to look at four different but overlapping aspects of software metrics, namely software product metrics, software process metrics, system metrics and software metrics in acquisition. The findings of the panels is presented in this proceedings.

Due to the large number of product, project, and people parameters which impact large custom software development efforts, measurement of software product quality is a complex undertaking. Furthermore, the absolute perspective from which quality is measured (customer satisfaction) is intangible. While we probably can't say what the absolute quality of a software product is, we can determine the relative quality, the adequacy of this quality with respect to pragmatic considerations, and identify good and bad trends during development. While no two software engineers will ever agree on an optimum definition of software quality, they will agree that the most important perspective of software quality is its ease of change. We can call this flexibility, adaptability, or some other vague term, but the critical characteristic of software is that it is soft. The easier the product is to modify, the easier it is to achieve any other software quality perspective. This paper presents objective quality metrics derived from consistent lifecycle perspectives of rework which, when used in concert with an evolutionary development approach, can provide useful insight to produce better quality per unit cost/schedule or to achieve adequate quality more efficiently. The usefulness of these metrics is evaluated by applying them to a large, real world, Ada project.

More often than not, company executives ask the wrong questions about software security.  This session will discuss techniques for changing the conversation about software security in order to encourage executives to ask the right questions – and provide answers that show progress towards meaningful objectives.  Caroline will discuss a progression of software security capabilities and the metrics that correspond to different levels of maturity.  She’ll discuss an approach for developing key metrics for your unique software security program and walk through a detailed example. Caroline Wong Cigital, Inc. Director of Strategic Security Initiatives Caroline Wong, CISSP, is the Director of Strategic Security Initiatives at Cigital, the world's largest consulting firm specializing in software security.  Prior to this role, Caroline led a product management team at Symantec and security teams at Zynga and eBay.  Caroline is the author of “Security Metrics: A Beginner’s Guide” and is well known as a thought leader on the topics of security strategy, operations, and metrics.  She has been a featured speaker at industry conferences including RSA (USA and Europe), ITWeb Summit (South Africa), Metricon, the Executive Women's Forum, ISC2 and the Information Security Forum.  Caroline contributed as a technical reviewer to the Center for Information Security Consensus Metrics Definitions.  She graduated from U.C. Berkeley with a B.S. in Electrical Engineering and Computer Sciences, has a Certificate in Finance and Accounting from Stanford's Executive Education Program, and is CISSP certified.  Caroline was awarded the 2010 Women of Influence "One to Watch" Award by the Executive Women's Forum. - Managed by the official OWASP Media Project https://www.owasp.org/index.php/OWASP_Media_Project Source: https://www.youtube.com/watch?v=50vOxExpAOU Uploader: OWASP

Software development efforts have become the highest-risk element of modern program management. One way that we can mitigate this risk is through the use of metrics. Software metrics can give us insight about the progress, quality, and expected completion of a software development effort. In earlier software development efforts, programming was viewed as a \"black art\" and, consequently, software metrics were not commonly used. Today, it is generally accepted that a software development effort should be properly planned and that software metrics should be used to control the project. Program managers are no longer concerned about whether or not to use metrics, but are more concerned with which metrics to use and whether or not the ones chosen will be effective. The Bradley Fighting Vehicle A3 Program provides valuable insight into the use of metrics. A principal finding of this research is that implementing an effective metrics program is extremely difficult, especially when the contractor is not experienced in developing software-intensive systems. Because this situation often exists, future and current program managers must assess their own knowledge of software development and plan to mitigate the effects of other factors they cannot influence. They must educate themselves on software issues and metrics and solicit assistance from independent agencies that specialize in software development

The Contel Technology Center's Software Engineering Laboratory (SEL) has as one of its goals the improvement of productivity and quality throughout Contel Corporation. The SEL's Process and Metrics Project addresses that goal in part by recommending metrics to be collected on each software development project throughout the corporation. This report suggests an initial set of metrics for which data are to be collected and analyzed, based on a process maturity framework developed at the Software Engineering Institute. Metrics are to be implemented step by step in four phases, corresponding to the maturity of the development process. Phase I metrics focus on project management. Phase II metrics measure the products produced during development, while Phase III metrics capture characteristics of the development process itself. Phase IV adds feedback loops to the process metrics, so that metrics play an active and ongoing role in assessing and controlling the development process from the very beginning of a project.

The Contel Technology Center's Software Engineering Laboratory (SEL) has as one of its goals the improvement of productivity and quality throughout Contel Corporation. The SEL's Process and Metrics Project addresses that goal in part by recommending metrics to be collected on each software development project throughout the corporation. This report suggests an initial set of metrics for which data are to be collected and analyzed, based on a process maturity framework developed at the Software Engineering Institute. Metrics are to be implemented step by step in four phases, corresponding to the maturity of the development process. Phase I metrics focus on project management. Phase II metrics measure the products produced during development, while Phase III metrics capture characteristics of the development process itself. Phase IV adds feedback loops to the process metrics, so that metrics play an active and ongoing role in assessing and controlling the development process from the very beginning of a project.

The Contel Technology Center's Software Engineering Laboratory (SEL) has as one of its goals the improvement of productivity and quality throughout Contel Corporation. The SEL's Process and Metrics Project addresses that goal in part by recommending metrics to be collected on each software development project throughout the corporation. This report suggests an initial set of metrics for which data are to be collected and analyzed, based on a process maturity framework developed at the Software Engineering Institute. Metrics are to be implemented step by step in four phases, corresponding to the maturity of the development process. Phase I metrics focus on project management. Phase II metrics measure the products produced during development, while Phase III metrics capture characteristics of the development process itself. Phase IV adds feedback loops to the process metrics, so that metrics play an active and ongoing role in assessing and controlling the development process from the very beginning of a project.

Due to the large number of product, project, and people parameters which impact large custom software development efforts, measurement of software product quality is a complex undertaking. Furthermore, the absolute perspective from which quality is measured (customer satisfaction) is intangible. While we probably can't say what the absolute quality of a software product is, we can determine the relative quality, the adequacy of this quality with respect to pragmatic considerations, and identify good and bad trends during development. While no two software engineers will ever agree on an optimum definition of software quality, they will agree that the most important perspective of software quality is its ease of change. We can call this flexibility, adaptability, or some other vague term, but the critical characteristic of software is that it is soft. The easier the product is to modify, the easier it is to achieve any other software quality perspective. This paper presents objective quality metrics derived from consistent lifecycle perspectives of rework which, when used in concert with an evolutionary development approach, can provide useful insight to produce better quality per unit cost/schedule or to achieve adequate quality more efficiently. The usefulness of these metrics is evaluated by applying them to a large, real world, Ada project.

A large number of Air Force programs require significant software development during implementation. Unfortunately, the software almost always takes longer than anticipated and requires extensive manpower to remove latent defects from the delivered products. Industry and academia are doing a great deal of work in the developing field of software production and quality metrics- -tools designed to help estimate project size and assess software quality, thus alleviating this industry-wide problem. This study examines the current state of these tools to see if they provide useful measures which can improve the software component of Air Force programs or if the effort used to implement these metrics represents wasted manpower. The study concludes with an assessment that the tools provide valuable data which, when properly applied, can help software managers set achievable schedules for quality software products which can be completed on time and require significantly less software maintenance manpower. (Author)

Optical fiber bas been the preferred cabling technology for certain building and campus network LAN backbones. Until recently however the use of fiber as a cabling medium to the desktop has been confined to special environments that require the unique properties of optical fiber such as noise immunity security distance high bandwidth demands (CAD/CAM video conferencing) and immunity to electrical interference. However choosing to use optical fiber in a network over other cabling options may present significant advantages in its inherent ability to handle data at higher speeds Decrease costs of optical fiber components compared to the increase electronic costs of carrying Gigabit Ethernet over Cat 5 or Cat SE UTP copper cabling has also accelerated the migration to optical fiber LAN. The thesis conducts a feasibility study of implementing a Fiber Optic Local Area Network in Software Metrics Laboratory in Ingersoll 158.

Relying on one validation and verification (V&V) alone cannot detect all of the security problems of a software system. Each class of V&V effort detects different class(s) of faults in software. Even composing a series of V&V efforts, one can never be completely sure that all faults have been detected. Additionally, security-related V&V efforts must continuously be updated to handle the newest forms of exploits of underlying vulnerabilities in software. The alerts produced by automated static analysis (ASA) tools and other static metrics have been shown to be an effective estimator of the actual reliability in a software system. Predictions of defect density and high-risk components can be identified using static analyzers early in the development phase. Our research hypothesis is the actual number of security vulnerabilities in a software system can be predicted based upon the number of security-related alerts reported by one or more static analyzers and by other static metrics. We built and evaluated statistical prediction model are used to predict the actual overall security of a system.