Software Engineering Laboratory (SEL) data and information policy

The policies and overall procedures that are used in distributing and in making available products of the Software Engineering Laboratory (SEL) are discussed. The products include project data and measures, project source code, reports, and software tools

The cleanroom case study in the Software Engineering Laboratory: Project description and early analysis

This case study analyzes the application of the cleanroom software development methodology to the development of production software at the NASA/Goddard Space Flight Center. The cleanroom methodology emphasizes human discipline in program verification to produce reliable software products that are right the first time. Preliminary analysis of the cleanroom case study shows that the method can be applied successfully in the FDD environment and may increase staff productivity and product quality. Compared to typical Software Engineering Laboratory (SEL) activities, there is evidence of lower failure rates, a more complete and consistent set of inline code documentation, a different distribution of phase effort activity, and a different growth profile in terms of lines of code developed. The major goals of the study were to: (1) assess the process used in the SEL cleanroom model with respect to team structure, team activities, and effort distribution; (2) analyze the products of the SEL cleanroom model and determine the impact on measures of interest, including reliability, productivity, overall life-cycle cost, and software quality; and (3) analyze the residual products in the application of the SEL cleanroom model, such as fault distribution, error characteristics, system growth, and computer usage

The Software Management Environment (SME)

The Software Management Environment (SME) is a research effort designed to utilize the past experiences and results of the Software Engineering Laboratory (SEL) and to incorporate this knowledge into a tool for managing projects. SME provides the software development manager with the ability to observe, compare, predict, analyze, and control key software development parameters such as effort, reliability, and resource utilization. The major components of the SME, the architecture of the system, and examples of the functionality of the tool are discussed

Comparative study of Object oriented and Functional testing using ML-Unit Tool

Abstract—: Object-oriented languages tend to be good and anyone make application for a fixed set of operations with things in addition to in the same way ones program code evolves, people primarily fill out new things. That is accomplished from adding new classes of which implement existing methods, plus the existing classes usually are left alone. Function languages are generally good as soon as people make application for a fixed set of things, and equally your current program code evolves, a person primarily add new operations in existing things. This is done by adding new function in which compute with existing information types, along with the existing function are generally left are done. Here in our paper we will compare object oriented with functional testing. DOI: 10.17762/ijritcc2321-8169.15072

Software Engineering Laboratory (SEL) relationships, models, and management rules

Over 50 individual Software Engineering Laboratory (SEL) research results, extracted from a review of published SEL documentation, that can be applied directly to managing software development projects are captured. Four basic categories of results are defined and discussed - environment profiles, relationships, models, and management rules. In each category, research results are presented as a single page that summarizes the individual result, lists potential uses of the result by managers, and references the original SEL documentation where the result was found. The document serves as a concise reference summary of applicable research for SEL managers

A study of the portability of an Ada system in the software engineering laboratory (SEL)

A particular porting effort is discussed, and various statistics on analyzing the portability of Ada and the total staff months (overall and by phase) required to accomplish the rehost, are given. This effort is compared to past experiments on the rehosting of FORTRAN systems. The discussion includes an analysis of the types of errors encountered during the rehosting, the changes required to rehost the system, experiences with the Alsys IBM Ada compiler, the impediments encountered, and the lessons learned during this study

Measuring the software process and product: Lessons learned in the SEL

The software development process and product can and should be measured. The software measurement process at the Software Engineering Laboratory (SEL) has taught a major lesson: develop a goal-driven paradigm (also characterized as a goal/question/metric paradigm) for data collection. Project analysis under this paradigm leads to a design for evaluating and improving the methodology of software development and maintenance

Automatically generated acceptance test: A software reliability experiment

This study presents results of a software reliability experiment investigating the feasibility of a new error detection method. The method can be used as an acceptance test and is solely based on empirical data about the behavior of internal states of a program. The experimental design uses the existing environment of a multi-version experiment previously conducted at the NASA Langley Research Center, in which the launch interceptor problem is used as a model. This allows the controlled experimental investigation of versions with well-known single and multiple faults, and the availability of an oracle permits the determination of the error detection performance of the test. Fault interaction phenomena are observed that have an amplifying effect on the number of error occurrences. Preliminary results indicate that all faults examined so far are detected by the acceptance test. This shows promise for further investigations, and for the employment of this test method on other applications

Foundations of Empirical Software Engineering: The Legacy of Victor R. Basili

This book captures the main scientific contributions of Victor R. Basili, who has significantly shaped the field of empirical software engineering from its very start. He was the first to claim that software engineering needed to follow the model of other physical sciences and develop an experimental paradigm. By working on this postulate, he developed concepts that today are well known and widely used, including the Goal-Question-Metric method, the Quality-Improvement paradigm, and the Experience Factory. He is one of the few software pioneers who can aver that their research results are not just scientifically acclaimed but are also used as industry standards. On the occasion of his 65th birthday, celebrated with a symposium in his honor at the International Conference on Software Engineering in St. Louis, MO, USA in May 2005, Barry Boehm, Hans Dieter Rombach, and Marvin V. Zelkowitz, each a long-time collaborator of Victor R. Basili, selected the 20 most important research papers of their friend, and arranged these according to subject field. They then invited renowned researchers to write topical introductions. The result is this commented collection of timeless cornerstones of software engineering, hitherto available only in scattered publications