Software Project Control Research Articles

Automated Software Project Planning and Control

This paper describes an automated software project planning and control system developed in Budapest, Hungary and now in operation in three large West German corporations. The system consists of five major components, one for each basic project management task-System requirements analysis and documentation-project cost and time estimation-project activity and result planning,-project monitoring and control-system configuration management and quality controlIt operates on IBM and Siemens mainframe computers under the operating systems MVS. VM and BS2000. The methodological basis of the system is the entity/relationship model of ChenIn the first phase, the functional applications, information areas, participatingorganizations and requirements on these entities are defined using entitylattribute formats. The functional applications and information areas are defined both in terms of their estimated quantities - number of instructions and data elements, number of components, and number of function points - and in terms of their desired quality characteristics - reliability ergonomy, efficiency, maintainability, etc. Projects are then defined to fulfill the requirements placed on the applications and data areas as prescribed by IBM in its Business Systems Planning ApproachIn the second phase, the project effort and calendar time as well as the predicted maintenance effort are automatically calculated using three different estimation techniques - COCOMO, Function Point, and Component AnalysisIn the third phase, a product breakdown tree is designed to obtain the elementary results. Corresponding to this result tree, an activity tree is generated which includes an activity for each desired result - module. data capsule, document, test procedure, etc. It is then transformed into a network for computing the activity dependencies and the critical path using the MPM methodIn the fourth phase. the project progress is monitored in terms of quantity of results produced, quality of results obtained, time spent and cost accrued. Deviations from the plan are automatically reported and the differences documentedproduct status database together with their quality assessment on a scale of 0:1 ratio of achieved quality to desired quality. Components are also given a version number, a completion date and a configuration status. Incoming error reports and change requests are accumulated and their relationships to the software components established. These are then aggregated and transformed into requirements so as to close the cycle and initiate a new project.

Automated software project planning and control

This paper describes an automated software project planning and control system developed in Budapest, Hungary and now in operation in three large West German corporations. The system consists of five major components, one for each basic project management task: 1. - system requirements analysis and documentation, 2. - project cost and time estimation, 3. - project activity and result planning, 4. - project monitoring and control, 5. - system configuration management and quality control. It operates on IBM and Siemens mainframe computers under the operating systems MVS, VM and BS2000. The methodological basis of the system is the entity/relationship model of Chen. In the first phase, the functional applications, information areas, participating organizations and requirements on these entities are defined using entity/attribute formats. The functional applications and information areas are defined both in terms of their estimated quantities — number of instructions and data elements, number of components, and number of function points — and in terms of their desired quality characteristics —reliability ergonomy, efficiency, maintainability, etc. Projects are then defined to fulfill the requirements placed on the applications and data areas as prescribed by IBM in its Business Systems Planning Approach. In the second phase, the project effort and calendar time as well as the predicted maintenance effort are automatically calculated using three different estimation techniques — COCOMO, Function Point, and Component Analysis. In the third phase, a product breakdown tree is designed to obtain the elementary results. Corresponding to this result tree, an activity tree is generated which includes an activity for each desired result — module, data capsule, document, test procedure, etc. It is then transformed into a network for computing the activity dependencies and the critical path using the MPM method. In the fourth phase, the project progress is monitored in terms of quantity of results produced, quality of results obtained, time spent and cost accrued. Deviations from the plan are automatically reported and the differences documented. In the fifth and final phase, all of the software components produced are registed in a product status database together with their quality assessment on a scale of 0:1 ratio of achieved quality to desired quality. Components are also given a version number, a completion date and a configuration status. Incoming error reports and change requests are accumulated and their relationships to the software components established. These are then aggregated and transformed into requirements so as to close the cycle and initiate a new project.

Software metrics: fault content estimation and software process control

The paper shows how software metrics can be used to plan and control software projects. Software metrics will be essential if the software industry is to continue growing and developing complex systems. The only way to increase knowledge of the software development and maintenance processes and the final product is to measure them and use the measurements in models for estimating their future behaviour. The emphasis of this paper is on complexity metrics and reliability models, and especially on their use for fault content estimation and control of the development and maintenance processes. Empirical results and guidelines of how to use complexity metrics and reliability models are presented.

Controlling software projects

Attempts to control software development often cause difficulties. Conventional engineering management techniques must be adapted to cope with the problems of software

Software Development: The Staircase Approach

Abstract Modelling of the software development process for large software systems provides a means for controlling software projects. This paper presents a new model, the Staircase Approach, which takes into account the merits, applicability, and limits of the well-known Waterfall, Evolutionary Development, and Fast Prototyping models. In a nutshell, this approach utilises the ideas of Evolutionary Development for system level activities, the principles of the Waterfall Model for the lower level activities, and is suited extremely well for practising Fast Prototyping. Experiences gained in applying it indicate that the Staircase Approach is more suited than conventional models in achieving the objective of better software project control.

Controlling software projects

In recent years the software industry has seen the increasing imposition of structure and discipline on technical development activities in an attempt to improve the efficiency of software development and the reliability of the software produced. The clear emphasis in the modern approach to software engineering is to focus attention on the overall development process and the co-ordination all aspects of software development. This paper examines the principles of managing and successfully controlling software development from a software engineering basis.

Structured design benefits to a process control software project

A 12-man-year process control software project has been successfully completed in 12 months without interruption of the production process of CERN PS accelerators. After 6 months of careful preparation by a small team, 9 man-years of software, i.e. around 100 control programs amounting to more than 40'000 instructions, have been produced in 6 months by 6 experienced full-time software engineers and 24 part-time engineers and technicians, part of whom had never programmed before. The delivered product met the users specifications, was completed within schedule, conformed to the standards and was fully documented.

Structured design benefits to a process control software project

A 12-man-year process control software project has been successfully completed in 12 months without interruption of the production process of CERN PS accelerators. After 6 months of careful preparation by a small team, 9 man-years of software, i.e., around 100 control programs amounting to more than 40,000 instructions, have been produced in 6 months by 6 experienced full-time software engineers and 24 part-time engineers and technicians, part of whom had never programmed before. The delivered product met the users specifications, was completed within schedule, conformed to the standards and was fully documented.

Software Project Management - Reaping The Benefits Of An Installed Software Quality Management System (SQMS)

According to Burrill and Ellsworth [1], Increased size, complexity, involvement of many areas, and the demand for quality will all generate an increased need for effective project This paper outlines a framework which project managers can employ to develop their own effective game plan for managing software projects. The framework has several ingredients. The first ingredient is about laying the foundation for tackling software projects. The second ingredient is a three-phased software project management lifecycle model assessment, planning, and control. The paper will discuss what the purpose, the tasks, and the outputs of each phase are, as well as the need for repeating the cycle. The third ingredient is the three project management work aspects process, product, and people management. Those aspects help managers to identify tasks which must be done in their own specific project. The paper will also illustrate how the work aspects can combine with the lifecycle model to a good effect. An example will be given to demonstrate the usefulness of the proposed framework.