Analyzing software data bindings in large-scale systems

One central feature of the structure of a software system is the coupling among its components (e.g., subsystems. modules) and the cohesion within them. The purpose of this study is to quantify ratios of coupling and cohesion and use them in the generation of hierarchical system descriptions. The ability of the hierarchical descriptions to localize errors by identifying error-prone system structure is evaluated using actual error data. Measures of data interaction, called data bindings, are used as the basis for calculating software coupling and cohesion. A 135,000 source line system from a production environment has been selected for empirical analysis. Software error data was collected from high-level system design through system test and from some field operation of the system. A set of five tools is applied to calculate the data bindings automatically, and cluster analysis is used to determine a hierarchical description of each of the system's 77 subsystems. An analysis of variance model is used to characterize subsystems and individual routines that had either many/few errors or high/low error correction effort

Calculation and use of an environment's characteristic software metric set

Since both cost/quality and production environments differ, this study presents an approach for customizing a characteristic set of software metrics to an environment. The approach is applied in the Software Engineering Laboratory (SEL), a NASA Goddard production environment, to 49 candidate process and product metrics of 652 modules from six (51,000 to 112,000 lines) projects. For this particular environment, the method yielded the characteristic metric set (source lines, fault correction effort per executable statement, design effort, code effort, number of I/O parameters, number of versions). The uses examined for a characteristic metric set include forecasting the effort for development, modification, and fault correction of modules based on historical data

Sugar beet investigations in Ohio in 1900

Caption title.Mode of access: Internet

Will It be a Tough Year?

While there may be some glimmers of hope about a turnaround to the U.S. economy, such as decreasing unemployment, Virginia CPAs aren\u27t betting on a huge recovery in the next year. The second annual VSCPA Economic Outlook Survey reveals Virginia CPAs are more pessimistic about the United States and Virginia economies than they were last year, but they are actually more optimistic about Virginia\u27s economy compared to the United States as a whole. Likewise, VSCPA members continue to feel good about the economic outlook in Virginia relative to neighboring states

Databook for human factors engineers. Volume 2 - Common formulas, metrics, definitions

Human factors engineering manual including mathematical formulas, nomographs, conversion tables, units of measurement, and nomenclature

Experience in hepatic resection for metastatic colorectal cancer: Analysis of clinical and pathologic risk factors

Background. The selection of patients for resective therapy of hepatic colorectal metastases remains controversial. A number of clinical and pathologic prognostic risk factors have been variably reported to influence survival. Methods. Between January 1981 and December 1991, 204 patients underwent curative hepatic resection for metastatic colorectal cancer. Fourteen clinical and pathologic determinants previously reported to influence outcome were examined retrospectively. This led to a proposed TNM staging system for metastatic colorectal cancer (mTNM). Results. No operative deaths occurred (death within 1 month). Overall 1-, 3-, and 5-year survivals were 91%, 43%, and 32%, respectively. Gender, Dukes' classification, site of primary colorectal cancer, histologic differentiation, size of metastatic tumor, and intraoperative blood transfusion requirement were not statistically significant prognostic factors (p > 0.05). Age of 60 years or more, interval of 24 months or less between colorectal and hepatic resection, four or more gross tumors, bilobar involvement, positive resection margin, lymph node involvement, and direct invasion to adjacent organs were significant poor prognostic factors (p < 0.05). In the absence of nodal disease or direct invasion, patients with unilobar solitary tumor of any size, or unilobar multiple tumors of 2 cm or smaller (stages I and II) had the highest survival rates of 93% at 1 year, 68% at 3 years, and 61% at 5 years. Unilobar disease with multiple lesions greater than 2 cm (stage III) resulted in 1-, 3-, and 5-year survivals of 98%, 45%, and 28%, respectively. Patients with bilobar involvement (multiple tumors, any size, or a single large metastasis) (stage IVA) had survival rates of 88% at 1 year, 28% at 3 years, and 20% at 5 years (p < 0.00001). Patients with nodal involvement or extrahepatic disease (stage IVB) experienced the poorest outcome with 1-, 3- , and 5-year survivals of 80%, 12%, and 0%, respectively (p < 0.00001). Conclusions. The proposed mTNM staging system appears to be useful in predicting the outcomes after hepatic resection of metastatic colorectal tumors