This study examines the potential of using stage‐wise process audit review and control (ARC) efforts in estimating overall effort and defects in a software project. Using archival data from 49 software projects that were based on the waterfall methodology, and obtained from a CMMI level 5 organisation, the authors found that higher ARC efforts at the requirement and build phases of a project were associated with an increase in overall project effort. Further, higher ARC efforts at the design and build phases were correlated with an increase in the number of defects delivered to the client at the end of the project. The predictive ability of the authors’ effort models was very high, with mean errors in the range of 3–4% of the overall project effort. They found that the mean ARC effort in their sample was 0.15 h/FP for the requirements stage, 0.31 h/FP for the design stage and 0.67 h/FP for the build stage. A project where the ARC effort for any of the three stages exceeded the respective benchmark, could be a candidate for deeper inspection to prevent excess effort or defects. Organisations can use their own data to develop similar benchmarks for their software project portfolios.

Software agents can perform effectively as negotiators in automated negotiation settings. We present a model for software agents that can automate negotiations by implementing a multi-issue learning heuristic that allows agents to learn from the bidding behavior of opponents. The performance of agents is evaluated using an experimental study involving human subjects. The results indicate that software agents can act as effective surrogates of human negotiators under some circumstances.

The Capability Maturity Model (CMM) has become a popular methodology for improving software development processes with the goal of developing high-quality software within budget and planned cycle time. Prior research literature, while not exclusively focusing on CMM level 5 projects, has identified a host of factors as determinants of software development effort, quality, and cycle time. In this study, we focus exclusively on CMM level 5 projects from multiple organizations to study the impacts of highly mature processes on effort, quality, and cycle time. Using a linear regression model based on data collected from 37 CMM level 5 projects of four organizations, we find that high levels of process maturity, as indicated by CMM level 5 rating, reduce the effects of most factors that were previously believed to impact software development effort, quality, and cycle time. The only factor found to be significant in determining effort, cycle time, and quality was software size. On the average, the developed models predicted effort and cycle time around 12 percent and defects to about 49 percent of the actuals, across organizations. Overall, the results in this paper indicate that some of the biggest rewards from high levels of process maturity come from the reduction in variance of software development outcomes that were caused by factors other than software size

This paper extends an exponential reliability growth model to determine the optimal number of test cases to be executed for various use case scenarios during the system testing of software. An example demonstrates a practical application of the optimization model for system test planning

This article presents a graph-based modeling system for structured modeling that supports model formulation, maintenance, and solution. The graph-based modeling system for structured modeling uses directed acyclic graphs called model graphs to represent models in various domains including mathematical programming, databases, and artificial intelligence. These graphs are modular and are synthesized using well-defined graphical constructs. The constructs have associated model expressions specified in a computer-executable language called Model Expression Language. The graphical constructs enable the system to automatically create model expressions and facilitate syntax-directed editing.