An Investigation of Human Factors in Software Development

The effects of human factors on "high-level" software properties–too intangible to quantify directly–can be inferred from the collective behavior of related "low-level" aspects.     

Programming measurement and estimation in the software engineering laboratory

This paper presents an attempt to examine a set of basic relationships among various software development variables, such as size, effort, project duration, staff size, and productivity. These variables are plotted against each other for 15 Software Engineering Laboratory projects that were developed for NASA/Goddard Space Flight Center by Computer Sciences Corporation. Certain relationships are derived in the form of equations, and these equations are compared with a set derived by Walston and Felix for IBM Federal Systems Division project data. Although the equations do not have the same coefficients, they are seen to have similar exponents. In fact, the Software Engineering Laboratory equations tend to be within one standard error of estimate of the IBM equations.     

Perspective-based Usability Inspection: An Empirical Validation of Efficacy

Inspection is a fundamental means of achieving software usability. Past research showed that the current usability inspection techniques were rather ineffective. We developed perspective-based usability inspection, which divides the large variety of usability issues along different perspectives and focuses each inspection session on one perspective. We conducted a controlled experiment to study its effectiveness, using a post-test only control group experimental design, with 24 professionals as subjects. The control group used heuristic evaluation, which is the most popular technique for usability inspection. The experimental design and the results are presented, which show that inspectors applying perspective-based inspection not only found more usability problems related to their assigned perspectives, but also found more overall problems. Perspective-based inspection was shown to be more effective for the aggregated results of multiple inspectors, finding about 30% more usability problems for 3 inspectors. A management implication of this study is that assigning inspectors more specific responsibilities leads to higher performance. Internal and external threats to validity are discussed to help better interpret the results and to guide future empirical studies.     

Property-based software engineering measurement

Little theory exists in the field of software system measurement. Concepts such as complexity, coupling, cohesion or even size are very often subject to interpretation and appear to have inconsistent definitions in the literature. As a consequence, there is little guidance provided to the analyst attempting to define proper measures for specific problems. Many controversies in the literature are simply misunderstandings and stem from the fact that some people talk about different measurement concepts under the same label (complexity is the most common case). There is a need to define unambiguously the most important measurement concepts used in the measurement of software products. One way of doing so is to define precisely what mathematical properties characterize these concepts, regardless of the specific software artifacts to which these concepts are applied. Such a mathematical framework could generate a consensus in the software engineering community and provide a means for better communication among researchers, better guidelines for analysts, and better evaluation methods for commercial static analyzers for practitioners. We propose a mathematical framework which is generic, because it is not specific to any particular software artifact, and rigorous, because it is based on precise mathematical concepts. We use this framework to propose definitions of several important measurement concepts (size, length, complexity, cohesion, coupling). It does not intend to be complete or fully objective; other frameworks could have been proposed and different choices could have been made. However, we believe that the formalisms and properties we introduce are convenient and intuitive. This framework contributes constructively to a firmer theoretical ground of software measurement     

Precipitation retrieval from spaceborne microwave radiometers basedon maximum a a posteriori probability estimation

A retrieval technique for estimating rainfall rate and precipitating cloud parameters from spaceborne multifrequency microwave radiometers is described. The algorithm is based on the maximum a posteriori probability criterion (MAP) applied to a simulated data base of cloud structures and related upward brightness temperatures. The cloud data base is randomly generated by imposing the mean values, the variances, and the correlations among the hydrometeor contents at each layer of the cloud vertical structure, derived from the outputs of a time-dependent microphysical cloud model. The simulated upward brightness temperatures are computed by applying a plane-parallel radiative transfer scheme. Given a multifrequency brightness temperature measurement, the MAP criterion is used to select the most probable cloud structure within the cloud-radiation data base. The algorithm is computationally efficient and has been numerically tested and compared against other methods. Its potential to retrieve rainfall over land has been explored by means of Special Sensor Microwave/Imager measurements for a rainfall event over Central Italy. The comparison of estimated rain rates with available raingauge measurements is also shown     

Comments on “Property-based software engineering measurement:refining the additivity properties”

The measure property set of Briand, Morasca, and Basili (1996) establishes the foundation of a real software measurement theory. Unfortunately, a number of inconsistencies related to additivity properties might hinder its acceptance and further elaboration. The authors show how to remove the ambiguity in the property definitions     

Simulating families of studies to build confidence in defect hypotheses

While it is clear that there are many sources of variation from one development context to another, it is not clear a priori what specific variables will influence the effectiveness of a process in a given context. For this reason, we argue that knowledge about software process must be built from families of studies, in which related studies are run within similar contexts as well as very different ones. Previous papers have discussed how to design related studies so as to document as precisely as possible the values of likely context variables and be able to compare with those observed in new studies. While such a planned approach is important, we argue that an opportunistic approach is also practical. The approach would combine results from multiple individual studies after the fact, enabling recommendations to be made about process effectiveness in context.

In this paper, we describe two processes with which we have been working to build empirical knowledge about software development processes: one is a manual and informal approach, which relies on identifying common beliefs or ‘folklore’ to identify useful hypotheses and a manual analysis of the information in papers to investigate whether there is support for those hypotheses; the other is a formal approach based around encoding the information in papers into a structured hypothesis base that can then be searched to organize hypotheses and their associated support. We test these processes by applying them to build knowledge in the area of defect folklore (i.e. commonly accepted heuristics about software defects and their behavior). We show that the formal methodology can produce useful and feasible results, especially when it is compared to the results output from the more manual, expert-based approach. The formalized approach, by relying on a reusable hypothesis base, is repeatable and also capable of producing a more thorough basis of support for hypotheses, including results from papers or articles that may have been overlooked or not considered by the experts.