A Vehicle Management End-to-End Testing and Analysis Platform for Validation of Mission and Fault Management Algorithms to Reduce Risk for NASA's Space Launch System

The engineering development of the new Space Launch System (SLS) launch vehicle requires cross discipline teams with extensive knowledge of launch vehicle subsystems, information theory, and autonomous algorithms dealing with all operations from pre-launch through on orbit operations. The characteristics of these spacecraft systems must be matched with the autonomous algorithm monitoring and mitigation capabilities for accurate control and response to abnormal conditions throughout all vehicle mission flight phases, including precipitating safing actions and crew aborts. This presents a large and complex system engineering challenge, which is being addressed in part by focusing on the specific subsystems involved in the handling of off-nominal mission and fault tolerance with response management. Using traditional model based system and software engineering design principles from the Unified Modeling Language (UML) and Systems Modeling Language (SysML), the Mission and Fault Management (M&FM) algorithms for the vehicle are crafted and vetted in specialized Integrated Development Teams (IDTs) composed of multiple development disciplines such as Systems Engineering (SE), Flight Software (FSW), Safety and Mission Assurance (S&MA) and the major subsystems and vehicle elements such as Main Propulsion Systems (MPS), boosters, avionics, Guidance, Navigation, and Control (GNC), Thrust Vector Control (TVC), and liquid engines. These model based algorithms and their development lifecycle from inception through Flight Software certification are an important focus of this development effort to further insure reliable detection and response to off-nominal vehicle states during all phases of vehicle operation from pre-launch through end of flight. NASA formed a dedicated M&FM team for addressing fault management early in the development lifecycle for the SLS initiative. As part of the development of the M&FM capabilities, this team has developed a dedicated testbed that integrates specific M&FM algorithms, specialized nominal and off-nominal test cases, and vendor-supplied physics-based launch vehicle subsystem models. Additionally, the team has developed processes for implementing and validating these algorithms for concept validation and risk reduction for the SLS program. The flexibility of the Vehicle Management End-to-end Testbed (VMET) enables thorough testing of the M&FM algorithms by providing configurable suites of both nominal and off-nominal test cases to validate the developed algorithms utilizing actual subsystem models such as MPS. The intent of VMET is to validate the M&FM algorithms and substantiate them with performance baselines for each of the target vehicle subsystems in an independent platform exterior to the flight software development infrastructure and its related testing entities. In any software development process there is inherent risk in the interpretation and implementation of concepts into software through requirements and test cases into flight software compounded with potential human errors throughout the development lifecycle. Risk reduction is addressed by the M&FM analysis group working with other organizations such as S&MA, Structures and Environments, GNC, Orion, the Crew Office, Flight Operations, and Ground Operations by assessing performance of the M&FM algorithms in terms of their ability to reduce Loss of Mission and Loss of Crew probabilities. In addition, through state machine and diagnostic modeling, analysis efforts investigate a broader suite of failure effects and associated detection and responses that can be tested in VMET to ensure that failures can be detected, and confirm that responses do not create additional risks or cause undesired states through interactive dynamic effects with other algorithms and systems. VMET further contributes to risk reduction by prototyping and exercising the M&FM algorithms early in their implementation and without any inherent hindrances such as meeting FSW processor scheduling constraints due to their target platform - ARINC 653 partitioned OS, resource limitations, and other factors related to integration with other subsystems not directly involved with M&FM such as telemetry packing and processing. The baseline plan for use of VMET encompasses testing the original M&FM algorithms coded in the same C++ language and state machine architectural concepts as that used by Flight Software. This enables the development of performance standards and test cases to characterize the M&FM algorithms and sets a benchmark from which to measure the effectiveness of M&FM algorithms performance in the FSW development and test processes

A MANAGED APPROACH OF INTERACTION BETWEEN AGILE SCRUM AND SOFTWARE CONFIGURATION MANAGEMENT SYSTEM

In current age the agile software development is one of the most popular software development methodology but due the mismanagement and lack of efficient handling of agile scrum and software configuration management system our software industry is facing a high rate of failed product, keeping this as my motivation, I have designed a efficient checklist which will help the industry to organized the interaction between agile scrum process and software configuration management system in a efficient and managed way and definitely that will increase the successful project in the software industry. Index-term : Agile Scrums, Software development, Software configuration management system, Checklist, Successful project

Integrating automated support for a software management cycle into the TAME system

Software managers are interested in the quantitative management of software quality, cost and progress. An integrated software management methodology, which can be applied throughout the software life cycle for any number purposes, is required. The TAME (Tailoring A Measurement Environment) methodology is based on the improvement paradigm and the goal/question/metric (GQM) paradigm. This methodology helps generate a software engineering process and measurement environment based on the project characteristics. The SQMAR (software quality measurement and assurance technology) is a software quality metric system and methodology applied to the development processes. It is based on the feed forward control principle. Quality target setting is carried out before the plan-do-check-action activities are performed. These methodologies are integrated to realize goal oriented measurement, process control and visual management. A metric setting procedure based on the GQM paradigm, a management system called the software management cycle (SMC), and its application to a case study based on NASA/SEL data are discussed. The expected effects of SMC are quality improvement, managerial cost reduction, accumulation and reuse of experience, and a highly visual management reporting system

Management of Software Development Projects

Any major software development starts with the Initiating process group. Once the charter document is approved, the Planning and then to the Executing stages will follow. Monitoring and Controlling is measuring the potential performance deviation of the project in terms of schedule and costs and performs the related Integrated Change Control activities. At the end, during the Closing, the program/project manager will check the entire work is completed and the objectives are met.

Project Management - Software Development Methodology

This article talks about project management in a software development area. The emphasis is given to the process of software development and the main responsibilities of the project manager. Furthermore, some aspects of different management topics that can be found in almost all projects nowadays are also described. To have a successful project one needs to have a team of persons who will participate in the project according to their professional expertise. The teams and sub-teams are defined and their roles are described.project management, software development area, process of software development

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

Active artefact management for distributed software engineering

We describe a software artefact repository that provides its contents with some awareness of their own creation. "Active" artefacts are distinguished from their passive counterparts by their enriched meta-data model which reflects the work-flow process that created them, the actors responsible, the actions taken to change the artefact, and various other pieces of organisational knowledge. This enriched view of an artefact is intended to support re-use of both software and the expertise gained when creating the software. Unlike other organisational knowledge systems, the meta-data is intrinsically part of the artefact and may be populated automatically from sources including existing data-format specific information, user supplied data and records of communication. Such a system is of increased importance in the world of "virtual teams" where transmission of vital organisational knowledge, at best difficult, is further constrained by the lack of direct contact between engineers and differing development cultures

TexRad-Feedback plc - cancer management imaging software

At the University of Sussex Professor Chris Chatwin, Dr Rupert Young & Dr Balaji Ganeshan were awarded an Achieving Impact Award by Vice Chancellor Professor Michael Farthing and Deputy Vice Chancellor Professor Michael Davies for their cancer management Imaging Software.The TexRAD Cancer management technology is being used as a research tool in seven of the G8 Countries; FDA and CE approvals for clinical use are imminent