Software reuse issues affecting AdaNET

The AdaNet program is reviewing its long-term goals and strategies. A significant concern is whether current AdaNet plans adequately address the major strategic issues of software reuse technology. The major reuse issues of providing AdaNet services that should be addressed as part of future AdaNet development are identified and reviewed. Before significant development proceeds, a plan should be developed to resolve the aforementioned issues. This plan should also specify a detailed approach to develop AdaNet. A three phased strategy is recommended. The first phase would consist of requirements analysis and produce an AdaNet system requirements specification. It would consider the requirements of AdaNet in terms of mission needs, commercial realities, and administrative policies affecting development, and the experience of AdaNet and other projects promoting the transfer software engineering technology. Specifically, requirements analysis would be performed to better understand the requirements for AdaNet functions. The second phase would provide a detailed design of the system. The AdaNet should be designed with emphasis on the use of existing technology readily available to the AdaNet program. A number of reuse products are available upon which AdaNet could be based. This would significantly reduce the risk and cost of providing an AdaNet system. Once a design was developed, implementation would proceed in the third phase

AdaNET services

MountainNet is a small firm which serves as a distribution center for AdaNET Services. These services include providing host systems and telecommunications for AdaNET, developing and supporting AdaNET Information Services, and developing a dynamic software inventory. AdaNET hosts are a Data General MV8000II and DEC VAX. Telecommunications are provided via the MountainNet private network and the Telenet public access dial network. Initially, the AdaNET Information Services will include software repositories, user communications and forums, software engineering information, bibliographic and library services, and an educational directory. The dynamic software inventory, which will become available in January 1990, will contain software engineering code and parts

AdaNET prototype library administration manual

The functions of the AdaNET Prototype Library of Reusable Software Parts is described. Adopted from the Navy Research Laboratory's Reusability Guidebook (V.5.0), this is a working document, customized for use the the AdaNET Project. Within this document, the term part is used to denote the smallest unit controlled by a library and retrievable from it. A part may have several constituents, which may not be individually tracked. Presented are the types of parts which may be stored in the library and the relationships among those parts; a concept of trust indicators which provide measures of confidence that a user of a previously developed part may reasonably apply to a part for a new application; search and retrieval, configuration management, and communications among those who interact with the AdaNET Prototype Library; and the AdaNET Prototype, described from the perspective of its three major users: the part reuser and retriever, the part submitter, and the librarian and/or administrator

Cooperative processing user interfaces for AdaNET

A cooperative processing user interface (CUI) system shares the task of graphical display generation and presentation between the user's computer and a remote host. The communications link between the two computers is typically a modem or Ethernet. The two main purposes of a CUI are reduction of the amount of data transmitted between user and host machines, and provision of a graphical user interface system to make the system easier to use

Repository-Based Software Engineering (RBSE) program

Support of a software engineering program was provided in the following areas: client/customer liaison; research representation/outreach; and program support management. Additionally, a list of deliverables is presented

TreeGrad: Transferring Tree Ensembles to Neural Networks

Gradient Boosting Decision Tree (GBDT) are popular machine learning algorithms with implementations such as LightGBM and in popular machine learning toolkits like Scikit-Learn. Many implementations can only produce trees in an offline manner and in a greedy manner. We explore ways to convert existing GBDT implementations to known neural network architectures with minimal performance loss in order to allow decision splits to be updated in an online manner and provide extensions to allow splits points to be altered as a neural architecture search problem. We provide learning bounds for our neural network.Comment: Technical Report on Implementation of Deep Neural Decision Forests Algorithm. To accompany implementation here: https://github.com/chappers/TreeGrad. Update: Please cite as: Siu, C. (2019). "Transferring Tree Ensembles to Neural Networks". International Conference on Neural Information Processing. Springer, 2019. arXiv admin note: text overlap with arXiv:1909.1179

A research review of quality assessment for software

Measures were recommended to assess the quality of software submitted to the AdaNet program. The quality factors that are important to software reuse are explored and methods of evaluating those factors are discussed. Quality factors important to software reuse are: correctness, reliability, verifiability, understandability, modifiability, and certifiability. Certifiability is included because the documentation of many factors about a software component such as its efficiency, portability, and development history, constitute a class for factors important to some users, not important at all to other, and impossible for AdaNet to distinguish between a priori. The quality factors may be assessed in different ways. There are a few quantitative measures which have been shown to indicate software quality. However, it is believed that there exists many factors that indicate quality and have not been empirically validated due to their subjective nature. These subjective factors are characterized by the way in which they support the software engineering principles of abstraction, information hiding, modularity, localization, confirmability, uniformity, and completeness