Nazim H. Madhavji

Software cost estimation with incomplete data

The construction of software cost estimation models remains an active topic of research. The basic premise of cost modeling is that a historical database of software project cost data can be used to develop a quantitative model to predict the cost of future projects. One of the difficulties faced by workers in this area is that many of these historical databases contain substantial amounts of missing data. Thus far, the common practice has been to ignore observations with missing data. In principle, such a practice can lead to gross biases and may be detrimental to the accuracy of cost estimation models. We describe an extensive simulation where we evaluate different techniques for dealing with missing data in the context of software cost modeling. Three techniques are evaluated: listwise deletion, mean imputation, and eight different types of hot-deck imputation. Our results indicate that all the missing data techniques perform well with small biases and high precision. This suggests that the simplest technique, listwise deletion, is a reasonable choice. However, this will not necessarily provide the best performance. Consistent best performance (minimal bias and highest precision) can be obtained by using hot-deck imputation with Euclidean distance and a z-score standardization.

A field study of requirements engineering practices in information systems development

To make recommendations for improving requirements engineering processes, it is critical to understand the problems faced in contemporary practice. We describe a field study whose general objectives were to formulate recommendations to practitioners for improving requirements engineering processes, and to provide directions for future research on methods and tools. The results indicate that there are seven key issues of greatest concern in requirements engineering practice. These issues are discussed in terms of the problems they represent, how these problems are addressed successfully in practice, and impediments to the implementation of such good practices.

Software Evolution and Feedback: Theory and Practice

List of Contributors. PART ONE SOFTWARE EVOLUTION. 1 Software Evolution (Meir Lehman and Juan Fernandez Ramil). 2 A Nontraditional View of the Dimensions of Software Evolution (Dewayne E. Perry). 3 IT Legacy Systems: Enabling Environments That Reduce the Legacy Problem: A Complexity Perspective (Eve Mitleton-Kelly). 4 Facets of Software Evolution (Roland T. Mittermeir). 5 Evolution in Software Systems: Foundations of the SPE Classification Scheme )Stephen Cook, Rachel Harrison, Meir M. Lehman and Paul Wernick). 6 A Simple Model of Software System Evolutionary Growth (W adys aw M. Turski). 7 Statistical Modelling of Software Evolution Processes (Tetsuo Tamai and Takako Nakatani). 8 A Case Study of Software Requirements Changes Due to External Factors (Vic Nanda and Nazim H. Madhavji). 9 Understanding Open-Source Software Evolution (Walt Scacchi). 10 Structural Analysis of Open Source Systems (Andrea Capiluppi, Maurizio Morisio and Juan Fernandez-Ramil). 11 A Study of Software Evolution at Different Levels of Granularity (Elizabeth Burd). 12 The Role of Ripple Effect in Software Evolution (Sue Black). 13 The Impact of Software-Architecture Compliance on System Evolution (R. Mark Greenwood, Ken Mayes, Wykeen Seet, Brian C. Warboys, Dharini Balasubramaniam, Graham Kirby, Ron Morrison and Aled Sage). 14 Comparison of Three Evaluation Methods for Object-Oriented Framework Evolution (Michael Mattsson). 15 Formal Perspectives on Software Evolution: from Refinement to Retrenchment (Michael Poppleton and Lindsay Groves). 16 Background and Approach to Development of a Theory of Software Evolution (Meir M Lehman and Juan Fern-andez Ramil). 17 Difficulties with Feedback Control in Software Processes (Meir M. Lehman, Dewayne E. Perry and Wlad Turski). 18 Policy-Guided Software Evolution (Nazim H. Madhavji and Josee Tasse). 19 Feedback in Requirements Discovery and Specification: a Quality Gateway for Testing Requirements (Suzanne Robertson). 20 Requirements Risk and Software Reliability (Norman F. Schneidewind). 21 Combining Process Feedback with Discrete Event Simulation Models to Support Software Project Management (David Raffo and Joseph Vandeville). 22 A Feedforward Capability to Improve Software Reestimation (William W. Agresti). 23 Modelling the Feedback Part of the Software Process in Software Resource Estimation (Juan Fernandez-Ramil and Sarah Beecham). 24 Value-Based Feedback in Software and Information Systems Development (Barry Boehm and LiGuo Huang). 25 Expert Estimation of Software Development Cost: Learning through Feedback (Magne Jorgensen and Dag Sjoberg). 26 Self-Adaptive Software: Internalized Feedback (Robert Laddaga, Paul Robertson and Howard Shrobe). 27 Rules and Tools for Software Evolution Planning and Management (Meir M (Manny) Lehman and Juan Fernandez Ramil). Index.

The process cycle

Historically, the process of software development has played an important role in the field of software engineering. A number of software life-cycle models have been developed in the last three decades. These models, although helpful is giving general guidance to software developers, do not expose myriad details that are critical in any large software development project. Recent development however, have unfolded many hidden aspects of the software process, giving rise to a new discipline that we call software process engineering. This paper depicts software process in the context of software environments, examines recent developments in the process field and proposes the concept of process cycle, which embodies the scope of engineering and evolution of software processes. The paper describes the details of the process cycle, including such issues as the role of corporate goals and policies in the engineering, management, performance and improvement of software processes; the transformation of the process artifacts through the process cycle; role of human beings in this (meta-) process; and communications in the cycle.

A reverse engineering environment based on spatial and visual software interconnection models

Reverse engineering is the process of extracting system abstractions and design information out of existing software systems. This information can then be used for subsequent development, maintenance, re-engineering, or reuse purposes. This process involves the identification of software artifacts in a particular subject system, and the aggregation of these artifacts to form more abstract system representations. This paper describes a reverse engineering environment which uses the spatial and visual information inherent in graphical representations of software systems to form the basis of a software interconnection model. This information is displayed and manipulated by the reverse engineer using an interactive graph editor to build subsystem structures out of software building blocks. The spatial component constitutes information about how a software structure looks. The coexistence of these two representations is critical to the comprehensive appreciation of the generated data, and greatly benefits subsequent analysis, processing, and decision-making.

User participation in the requirements engineering process: An empirical study

In the development of information systems, user participation in the requirements engineering (RE) process is hypothesised to be necessary for RE success. In this paper we develop a theoretical model which predicts that the interaction between user participation in the RE process and uncertainty has an impact on RE success. This theory is empirically tested using survey data. We develop instruments to measure user participation and uncertainty. An existing instrument for measuring RE success was used. This instrument covers two dimensions of RE success: (a) the quality of RE service, and (b) the quality of RE products. The results, indicate that as uncertainty increases, greater user participation alleviates the negative influence of uncertainty on the quality of RE service, and that as uncertainty decreases, the beneficial effects on the quality of RE service of increasing user participation diminish. Furthermore, we did not find that the interaction between user participation and uncertainty had an impact on the quality of RE products. Based on these results, we make recommendations for managing user participation in the RE process, and provide directions for future research.

Prism-methodology and process-oriented environment

The Prism model of engineering processes and an architecture which captures this model in its various components are described. The architecture has been designed to hold a product software process description the life-cycle of which is supported by an explicit representation of a higher-level (or meta) process description. The central part of this paper describes the nine-step Prism methodology for building and tailoring process models and gives several scenarios to support this description. In Prism, process models are built using a hybrid process modeling language that is based on a high-level Petri net formalism and rules. An important observation is that this environment should be seen as an infrastructure for carrying out the more difficult task of creating sound process models. >

Prism = methodology + process-oriented environment

A description is given of Prism, an experimental process-oriented environment supporting methodical development, instantiation, and execution of software process models. Also described is an architecture that captures this model in its various components. The architecture has been designed to hold a product software process description, the life cycle of which is supported by an explicit representation of a higher level (or meta) process description. Also described is the nine-step Prism methodology for building and tailoring process models, and several scenarios to support this description are given. In Prism, process models are built using a hybrid process modeling language, which is based on a high-level Petri net formalism and rules. The Prism prototype has been implemented on UNIX, GRAS database for attributed graph structures, and the Sunview user interface.<<ETX>>

Emerging technologies that support a software process life cycle

The goal of developing quality software can be achieved by focusing on the improvement of both product quality and process quality. While the traditional focus has been on product quality, there is an increased awareness of the benefits of improving the quality of the processes used to develop and support those products. These processes are key elements in understanding and improving the practice of software engineering. In this paper, existing objectives for the development and application of models of software processes are restated, and current research sponsored by the IBM Centre for Advanced Studies (CAS) is discussed as it applies to furthering each of the objectives. A framework is also presented that relates the research work to the various sectors of a software process life cycle. The on-going research involves four universities, CAS, and collaboration with IBM Toronto Laboratory developers.

Implementing concepts from the Personal Software Process in an industrial setting

The Personal Software Process (PSP) has been taught at a number of universities with impressive results. If is also of interest to industry as a means for training their software engineers. While there are published reports on the teaching of PSP in classroom settings (at universities and industry), little systematic study has been conducted on the implementation of PSP in industry. Also, largely anecdotal evidence exists as to its effectiveness with real programming tasks. Effectiveness is measured in terms of the number of trained engineers who actually use PSP in their daily work, and improvements in productivity and defect removal. We report on a study of the implementation of some PSP concepts in a commercial organization. The empirical enquiry method that we employed was action research. Our results identify the problems that were encountered during the four major activities of an implementation of PSP: planning, training, evaluation, and leveraging. We describe how these problems were addressed, and the general lessons learned from the implementation. An overall transfer of PSP training rate of 46.5% was achieved. For the engineers in our study, those who applied all of the taught PSP concepts on-the-job improved their defect detection capabilities.