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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.

The evaluations of and recommendations for the use of software development measures based on the practical and analytical experience of the Software Engineering Laboratory are discussed. The basic concepts of measurement and system of classification for measures are described. The principal classes of measures defined are explicit, analytic, and subjective. Some of the major software measurement schemes appearing in the literature are derived. The applications of specific measures in a production environment are explained. These applications include prediction and planning, review and assessment, and evaluation and selection.

Software engineering activities in the Industry has come a long way with various improve- ments brought in various stages of the software development life cycle. The complexity of modern software, the commercial constraints and the expectation for high quality products demand the accurate fault prediction based on OO design metrics in the class level in the early stages of software development. The object oriented class metrics are used as quality predictors in the entire OO software development life cycle even when a highly iterative, incremental model or agile software process is employed. Recent research has shown some of the OO design metrics are useful for predicting fault-proneness of classes. In this paper the empirical validation of a set of metrics proposed by Chidamber and Kemerer is performed to assess their ability in predicting the software quality in terms of fault proneness and degradation. We have also proposed the design complexity of object-oriented software with Weighted Methods per Class metric (WMC-CK metric) expressed in terms of Shannon entropy, and error proneness.

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.

This report presents the results of a study of software metrics applied to various classes of COBOL programs. Particular attention is given to the software science metrics of Halstead, which were applied to hundreds of COBOL programs written by students at Ohio State University, as well as several production COBOL programs. The results include support of the inclusion of Data Division in the software science counting strategy, nonsupport for the use of the software science language level metric, and the identification of a weakness in the ability of the Halstead E measure to capture integration effort. Several proposed complexity metrics were compared for their ability to predict actual development effort, with none of the metrics studied behaving in an impressive manner. Some approaches for refining existing complexity metrics to overcome their apparent weaknesses are suggested.

This report presents the results of a study of software metrics applied to various classes of COBOL programs. Particular attention is given to the software science metrics of Halstead, which were applied to hundreds of COBOL programs written by students at Ohio State University, as well as several production COBOL programs. The results include support of the inclusion of Data Division in the software science counting strategy, nonsupport for the use of the software science language level metric, and the identification of a weakness in the ability of the Halstead E measure to capture integration effort. Several proposed complexity metrics were compared for their ability to predict actual development effort, with none of the metrics studied behaving in an impressive manner. Some approaches for refining existing complexity metrics to overcome their apparent weaknesses are suggested.

Within DOD, there exists many different network platforms and configurations. Managing multiple platforms with different protocols, configurations, and applications is a challenging task for a network manager. A possible solution to efficiently manage these multiple platforms is to allow platforms to share resources, databases, and applications. In the Software Metrics Lab at the Naval Postgraduate School two disparate networks exist: a LocalTalk network and an IBM Token Ring network. Interconnection and interoperability between these networks is possible. This thesis uses a combination of three interconnection approaches: protocol function, network access, and network services approach to design an interconnected network. This thesis provides a proposed solution and an implementation plan, along with estimated hardware and software costs. The methodology used to reach a solution is a combination of a literature review on network connectivity, and interviews with consultants, technical editors of network magazines, and the school's cognizant lab managers.

The role of metrics in software quality is well recognized. However, software metrics are yet to be standardized and integrated into development practices across software industry. While process, project, and product metrics share a common goal of contributing to software quality and reliability, utilization of metrics has been at minimum. This work is an effort to bring more attention to software metrics. It examines the practices of metrics in software industry and the experiences of some organizations that have developed, promoted, and utilized variety of software metrics. As various types of metrics are being developed and used, these experiences show evidence of benefits and improvements in quality and reliability. Dinesh Kumar Y | Nuka Raju Kolli"Novel Metrics in Software Industry" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-2 | Issue-1 , December 2017, URL: http://www.ijtsrd.com/papers/ijtsrd8215.pdf Article URL: http://www.ijtsrd.com/computer-science/other/8215/novel-metrics-in-software-industry/dinesh-kumar-y

The role of metrics in software quality is well recognized. However, software metrics are yet to be standardized and integrated into development practices across software industry. While process, project, and product metrics share a common goal of contributing to software quality and reliability, utilization of metrics has been at minimum. This work is an effort to bring more attention to software metrics. It examines the practices of metrics in software industry and the experiences of some organizations that have developed, promoted, and utilized variety of software metrics. As various types of metrics are being developed and used, these experiences show evidence of benefits and improvements in quality and reliability. Dinesh Kumar Y | Nuka Raju Kolli"Novel Metrics in Software Industry" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-2 | Issue-1 , December 2017, URL: http://www.ijtsrd.com/papers/ijtsrd8215.pdf Article URL: http://www.ijtsrd.com/computer-science/other/8215/novel-metrics-in-software-industry/dinesh-kumar-y

Mark Popovich of the Good Companies/Good Jobs Initiative and Larry Schlang of Working Metrics discuss what the Working Metrics software is and how it works. Clip is from the Working in America event "The Aspen Institute Launches New Tool to Create Business Incentives by Measuring Good Jobs" on October 29, 2018.

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.

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.

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.

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.

Software metrics provide an effective method for characterizing software. Metrics have traditionally been composed through the definition of an equation. This approach is limited by the fact that all the interrelationships among all the parameters be fully understood. This paper explores an alternative, neural network approach to modeling metrics. Experiments performed on two widely accepted metrics, McCabe and Halstead, indicate that the approach is sound, thus serving as the groundwork for further exploration into the analysis and design of software metrics.

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 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.

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

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

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

As systems become increasingly software dependent, their reliability will accordingly depend more so on the reliability of their resident software. Just as techniques and processes were developed and improved to ensure hardware reliability, so most techniques evolve to ensure software reliability. Two questions are addressed by this thesis. First, how do we measure software reliability throughout a project's lifecycle? Second, is there a tool which will provide effective insight into the test-now-or-later problem? The solution to our first question is a U.S. Army software procurement methodology which is briefly outlined as the overall framework for software procurement in this thesis. The solution to our second problem is the primary focus of this thesis. A software fault analysis tool is developed and programmed. Some results from this algorithm are provided and their potential resource saving impact explored. Program managers of software-intensive projects would be well advised to use the Army's methodology and this fault analysis tool to potentially save critically short procurement resources.

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.

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.

This paper is concerned with methods of measuring and developing quality software. Reliable flight and ground support software is a highly important factor in the successful operation of the space shuttle program. Reliability is probably the most important of the characteristics inherent in the concept of 'software quality'. It is the probability of failure free operation of a computer program for a specified time and environment.

When digital technology is employed to perform some function aboard aircraft, the designer documents the technology and the applicant presents a package to the Certification Engineer (CE). Typically, the package might include design and test specifications, test plans, and test results for the systems. This package assures the CE that the designer has properly developed and validated the system. Software Quality Metrics (SQM) may be used during the software (SW) development and testing. SQM technology attempts to quantify various quality-oriented factors, such as reliability and maintainability. The SW developer determines the quality factors that are important to the application. SW Metrics that correlate to these factors are used on the code to determine to what extent these factors have been reached. Based on the results, the developer determines whether the SW meets the requirements set for it and how well the SW will perform. This technical report documents the results of a study conducted to analyze SQM as they apply to the code contained in avionic equipment and systems. This report is intended to provide an indepth explanation of how SQM may be applied and interpreted.

The increasing cost and complexity of software in recent years is causing growing interest in the development of measurement technology to evaluate, predict and compare software complexity. Metrics can be used throughout all the development cycle providing valuable information to the software developers in order to enhance the final products. The goal of this thesis is to verify empirically the fault-predictive ability of some software complexity metrics and specifically their usefulness during the testing phase. A set of eight programs, varying in length from 1,186 to 2,489 lines of Pascal code with 157 faults identified with specific modules, provided the data for this study. The results of the analysis of the programs using four metrics, cyclomatic complexity, bandwidth, nested complexity and the number of statements, show that control-structure metrics can be effectively used to detect the more fault-prone modules. The nested complexity of the modules seems to be some relation with the number of faults caused by wrong use of variables and overrestrictive input checks. These observations can be particularly useful during the testing phase because testers can use control-structure metrics to predict not only the modules that may cause more problems but also the more frequent types of faults and use the metrics to guide the choice of testing techniques.

Network Control Center (NCC) Project metrics are captured during the implementation and testing phases of the NCCDS software development lifecycle. The metrics data collection and reporting function has interfaces with all elements of the NCC project. Close collaboration with all project elements has resulted in the development of a defined and repeatable set of metrics processes. The resulting data are used to plan and monitor release activities on a weekly basis. The use of graphical outputs facilitates the interpretation of progress and status. The successful application of metrics throughout the NCC project has been instrumental in the delivery of quality software. The use of metrics on the NCC Project supports the needs of the technical and managerial staff. This paper describes the project, the functions supported by metrics, the data that are collected and reported, how the data are used, and the improvements in the quality of deliverable software since the metrics processes and products have been in use.

Software Development is an infant engineering discipline compared with other engineering areas. The ability of programs, Program Managers, and Lead Software Engineers to effectively measure how a program is doing is increasingly difficult based on shifting requirements, resource constraints, familiarity of the development domain, etc. The Department of the Navy is dedicated to provide the highest quality software to its users. In doing, there is a need for a formalized set of Software Quality Metrics. The goal of this paper is to establish the validity of those necessary Quality metrics. In our approach we collected the data of over a dozen programs from previous tests, analyzed current states of the software, derived formulas via weighting to provide necessary results, investigated tool sets to provide the necessary variable data for our formulas and tested the formulas for validity.

In the dynamic software field there are major challenges in adapting metrics and cost estimation methods to continuing changes. There is a need to assess emerging trends and re-interpret software size measures and estimation models for new processes. Future trends of software systems are overviewed with implications for software sizing and cost estimation capabilities. Methods are shown to handle some of these effects, but many software variabilities remain uncovered.

This thesis investigated several hypotheses that specific product measures could be used to predict later software lifecycle process or product measures. It collected software product and process measures from four consecutive major releases of a large Cobol legacy system (400K LOC). The types of product measures used were size and specific complexity measures. A statistical software package was used to calculate sample correlation coefficients between the measures. A 95% confidence interval was computed for each sample correlation coefficient that showed a strong or moderate linear correlation. The maintenance process measures provided were manhours used for each program changed or added, and defects detected during each change request. Sample correlation coefficients were derived to see if product measures such as size and complexity could reveal trends that could be used to estimate other software lifecycle measures such as effort or defects. The hypotheses to this research could neither be accepted nor rejected because the process measures collected by the system's owners were recorded at a level too high for sound statistical analysis. Weaknesses are identified in the way these process measures are collected, and suggestions are provided on how process measures can be better identified and recorded.

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.

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 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.

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.

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.

Includes bibliographical references (p. [236]-247) and index

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.

Modernization of Department of Defense (DoD) weapon systems has resulted in an ever-increasing dependence on software. Despite technological advances in the software field, software development remains costly and one of the highest risk factors on most weapon system programs. The use of software metrics is a methodology for mitigating this uncertainty so that software development progresses under informed decision making. Software metrics are essential tracking tools used by program managers to monitor and control risk areas. However, the choice of metrics for a program is critical to their usefulness. This research provides a guide to acquisition managers on selecting the most effective metrics to use in management of weapon system software. The study identifies key issues in the use of software metrics experienced by program managers. The study recommends a revised set of metrics and improvements to the use of metrics based on innovations and improvements in the software field as well as software estimation tools that facilitate the use of these software metrics.

Modernization of Department of Defense (DoD) weapon systems has resulted in an ever-increasing dependence on software. Despite technological advances in the software field, software development remains costly and one of the highest risk factors on most weapon system programs. The use of software metrics is a methodology for mitigating this uncertainty so that software development progresses under informed decision making. Software metrics are essential tracking tools used by program managers to monitor and control risk areas. However, the choice of metrics for a program is critical to their usefulness. This research provides a guide to acquisition managers on selecting the most effective metrics to use in management of weapon system software. The study identifies key issues in the use of software metrics experienced by program managers. The study recommends a revised set of metrics and improvements to the use of metrics based on innovations and improvements in the software field as well as software estimation tools that facilitate the use of these software metrics.

Modernization of Department of Defense (DoD) weapon systems has resulted in an ever-increasing dependence on software. Despite technological advances in the software field, software development remains costly and one of the highest risk factors on most weapon system programs. The use of software metrics is a methodology for mitigating this uncertainty so that software development progresses under informed decision making. Software metrics are essential tracking tools used by program managers to monitor and control risk areas. However, the choice of metrics for a program is critical to their usefulness. This research provides a guide to acquisition managers on selecting the most effective metrics to use in management of weapon system software. The study identifies key issues in the use of software metrics experienced by program managers. The study recommends a revised set of metrics and improvements to the use of metrics based on innovations and improvements in the software field as well as software estimation tools that facilitate the use of these software metrics.

This paper is a summary of software change and defect data collected during extended development and post-deployment software support (PDSS) for the Training Laboratory (TRALAB), a computer-based training system developed starting in 1984 by the Naval Center for Space Technology (NCST) at the Naval Research Laboratory (NRL). Of note, the development contractor was required to apply software engineering technology developed previously at NRL as part of the Software Cost Reduction (SCR) project. Another important requirement was for the collection of project metric data that could be used to evaluate the effectiveness of the SCR approach. Data collection was accomplished by modifying customary project Software Problem Reports (SPRs). Analysis of the data collected on SPR resolution work during extended development integration and test (I&T) during August 1988 through April 1989 indicates that the application of SCR technology enhanced software ease of change. This paper is a continuation of the earlier analysis to include PDSS SPR data collected during August 1990 through May 1991. The more recent analysis continues to suggest that identifying expected system changes during system definition stages and modularizing the system to encapsulate these changes yield life-cycle benefits. Modifications required by changes tend to be confined to a small number of design components, and it is easier to implement expected changes in comparison to arbitrary changes. Computer programs, Ease of change, Information hiding, Software, PDSS, SCR, Metrics, TRALAB.

Over the decades, the increasing use of software has enabled construction and deployment of ever more capable space systems for SMC. However, managing, controlling, and participating in software development for such software-intensive systems is a difficult and error-prone task that is exacerbated by the lack of meaningful data on key products and processes. Such data should provide visibility into the health and status of the evolving software system, assist in early identification of current and potential problem areas, and aid in predicting such software system characteristics as reliability, maintainability, cost, and schedule. Until recently, comprehensive data collection analysis methods which treat software as an integral part of a larger system have not been available. This report introduces a software system metrics approach that has been developed for this purpose. The report discusses the utility of the approach, key concepts for applying metrics to software-intensive systems, and basic metrics planning guidelines. It also introduces a set of recommended metrics that cover both the system and the software throughout the life cycle. A complete description of the metrics approach, associated contractual guidelines, and detailed descriptions of several of the recommended metrics are the subject of a forthcoming TOR.

Over the decades, the increasing use of software has enabled construction and deployment of ever more capable space systems for SMC. However, managing, controlling, and participating in software development for such software-intensive systems is a difficult and error-prone task that is exacerbated by the lack of meaningful data on key products and processes. Such data should provide visibility into the health and status of the evolving software system, assist in early identification of current and potential problem areas, and aid in predicting such software system characteristics as reliability, maintainability, cost, and schedule. Until recently, comprehensive data collection analysis methods which treat software as an integral part of a larger system have not been available. This report introduces a software system metrics approach that has been developed for this purpose. The report discusses the utility of the approach, key concepts for applying metrics to software-intensive systems, and basic metrics planning guidelines. It also introduces a set of recommended metrics that cover both the system and the software throughout the life cycle. A complete description of the metrics approach, associated contractual guidelines, and detailed descriptions of several of the recommended metrics are the subject of a forthcoming TOR.

Modern software development methodologies include reuse of open source code. Reuse can be facilitated by architectural knowledge of the software, not necessarily provided in the documentation of open source software. The effort required to comprehend the system's source code and discover its architecture can be considered a major drawback in reuse. In a recent study we examined the correlations between design metrics and classes' architecture layer. In this paper, we apply our methodology in more open source projects to verify the applicability of our method. Keywords: system understanding; program comprehension; object-oriented; reuse; architecture layer; design metrics;

USA

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)

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)

This report covers the period from 1 June 1977, to 31 May 1978, during which the first of three phases was completed. This phase concentrated on identifying existing strategies for testing and composing new ones for use in the subsequent phases in which software metrics, related to testing, will be developed and tested against a variety of computer programs. The aim of the research is to produce an automatic testing tool which will exhaustively test all tracks through a program, where a track is a time integrated shadow of the execution sequence - where multiple passes through a program segment are recorded as a single pass and the order of usage of the segments is not relevant.