Software Measurement Activities in Small and Medium Enterprises: an Empirical Assessment

An empirical study for evaluating the proper implementation of measurement/metric programs in software companies in one area of Turkey is presented. The research questions are discussed and validated with the help of senior software managers (more than 15 years’ experience) and then used for interviewing a variety of medium and small scale software companies in Ankara. Observations show that there is a common reluctance/lack of interest in utilizing measurements/metrics despite the fact that they are well known in the industry. A side product of this research is that internationally recognized standards such as ISO and CMMI are pursued if they are a part of project/job requirements; without these requirements, introducing those standards to the companies remains as a long-term target to increase quality

A research review of quality assessment for software

Measures were recommended to assess the quality of software submitted to the AdaNet program. The quality factors that are important to software reuse are explored and methods of evaluating those factors are discussed. Quality factors important to software reuse are: correctness, reliability, verifiability, understandability, modifiability, and certifiability. Certifiability is included because the documentation of many factors about a software component such as its efficiency, portability, and development history, constitute a class for factors important to some users, not important at all to other, and impossible for AdaNet to distinguish between a priori. The quality factors may be assessed in different ways. There are a few quantitative measures which have been shown to indicate software quality. However, it is believed that there exists many factors that indicate quality and have not been empirically validated due to their subjective nature. These subjective factors are characterized by the way in which they support the software engineering principles of abstraction, information hiding, modularity, localization, confirmability, uniformity, and completeness

Optimal Release Time: Numbers or Intuition?

Despite the exponential increase in the demand for software and the increase in our dependence on software, many software manufacturers behave in an unpredictable manner. In such an unpredictable software manufacturer organization, it is difficult to determine the optimal release time. An economic model is presented supporting the evaluation and comparison of different release or market entry alternatives. This model requires information with respect to achieved reliability and maintainability. Existing literature reveals many models to estimate reliability and limited models to estimate maintainability. The practicality of most available models is however criticized. A series of case studies confirmed that software manufacturers struggle with determining the reliability and maintainability of their products prior to releasing them. This leads to a combination of non-analytical methods to decide when a software product is good enough for release: intuition prevails where sharing convincing information is required. Next research steps are put forward to investigate ways increasing the economic reasoning about the optimal release time

Performance Comparison of Projective Elliptic-curve Point Multiplication in 64-bit x86 Runtime Environment

For over two decades, mathematicians and cryptologists have evaluated and presented the theoretical performance of Elliptic-curve scalar point-multiplication in projective geometry. Because computation in projective domain is composed of a wide array of formulations and computing optimizations, there is not a comprehensive performance comparison of point-multiplication using projective transformation available to verify its realistic efficiency in 64-bit x86 computing platforms. Today, research on explicit mathematical formulations in projective domain continues to excel by seeking higher computational efficiency and ease of realization. An explicit performance evaluation will help implementers choose better implementation methods and improve Elliptic-curve scalar point-multiplication. This paper was founded on the practical solution that obtaining realistic performance figures should be based on more precise computational cost metrics and specific computing platforms. As part of that solution, an empirical performance benchmark comparison between two approaches implementing projective Elliptic-curve scalar point-multiplication will be presented to provide the selection of, and subsequently ways to improve scalar point-multiplication technology executing in a 64-bit x86 runtime environment

APPLICATION AND REFINEMENTS OF THE REPS THEORY FOR SAFETY CRITICAL SOFTWARE

With the replacement of old analog control systems with software-based digital control systems, there is an urgent need for developing a method to quantitatively and accurately assess the reliability of safety critical software systems. This research focuses on proposing a systematic software metric-based reliability prediction method. The method starts with the measurement of a metric. Measurement results are then either directly linked to software defects through inspections and peer reviews or indirectly linked to software defects through empirical software engineering models. Three types of defect characteristics can be obtained, namely, 1) the number of defects remaining, 2) the number and the exact location of the defects found, and 3) the number and the exact location of defects found in an earlier version. Three models, Musa's exponential model, the PIE model and a mixed Musa-PIE model, are then used to link each of the three categories of defect characteristics with reliability respectively. In addition, the use of the PIE model requires mapping defects identified to an Extended Finite State Machine (EFSM) model. A procedure that can assist in the construction of the EFSM model and increase its repeatability is also provided. This metric-based software reliability prediction method is then applied to a safety-critical software used in the nuclear industry using eleven software metrics. Reliability prediction results are compared with the real reliability assessed by using operational failure data. Experiences and lessons learned from the application are discussed. Based on the results and findings, four software metrics are recommended. This dissertation then focuses on one of the four recommended metrics, Test Coverage. A reliability prediction model based on Test Coverage is discussed in detail and this model is further refined to be able to take into consideration more realistic conditions, such as imperfect debugging and the use of multiple testing phases

Measurement Technique to Evaluate Model- Based Tools for Safety Critical Embedded Systems

Abstract: Model-based systems engineering is a state of art engineering process being adopted by industry all over the world to develop a safe, reliable, maintainable and available system. Industry standards like IEC 61508, EN50128 and RTCA DO-178C recognize the capabilities of the model-based approach for an effective engineering process performance. There are number of model-based tools available in the market and the selection of an appropriate tool is very critical for the success of the project. Hence there should be benchmark to select the appropriate tool for the project. This paper provides a measurement technique for evaluating model-based tools based on the tool features like its applicability, portability, scalability, and compatibility, conformance to standards, versioning and reporting to name a few. The effectiveness of the techniques proposed is evaluated for a proven system as a case study. The outcome provides the metrics for the selection of appropriate tool for an application and probable combination of tools that can be used in various phases of the life cycle. The proposed technique helps in selection of the most appropriate tool for a particular application based on the project schedule, budget and safety requirements resulting into an effective process

Exploring Government Contractor Experiences Assessing and Reporting Software Development Status

Reports from academic, commercial, and government organizations have documented software-intensive system cost and schedule overruns for decades. These reports have identified lack of management insight into the software development process as one of many contributing factors. Multiple management mechanisms exist. However, these mechanisms do not support the assessment, and subsequent reporting, of software completion status. Additionally, the conceptual framework, based on industry standards, is limited in its relevance to this study due to an emphasis on what is needed while deferring implementation details. The purpose of this phenomenological study was to explore U.S. government contractors\u27 lived experiences of assessing and reporting software completion status with current measurement mechanisms. Twenty program or project managers responded to interview questions targeting positive and challenging experiences with current measurement mechanisms. Qualitative analysis of the experiential data was based on open and axial coding conducted on interview transcripts. Analysis indicated that costly resources are applied to metrics that do not provide the required level of management insight into completion status. These findings have positive social change implications for program managers, project managers, and researchers by documenting the need to develop relevant and cost-efficient status metrics to provide the critical insight required by management to reduce overruns

Model-based risk assessment

In this research effort, we focus on model-based risk assessment. Risk assessment is essential in any plan intended to manage software development or maintenance process. Subjective techniques are human intensive and error-prone. Risk assessment should be based on architectural attributes that we can quantitatively measure using architectural level metrics. Software architectures are emerging as an important concept in the study and practice of software engineering nowadays, due to their emphasis on large-scale composition of software product, and to their support for emerging software engineering paradigms, such as product line engineering, component based software engineering, and software evolution.;In this dissertation, we generalize our earlier work on reliability-based risk assessment. We introduce error propagation probability in the assessment methodology to account for the dependency among the system components. Also, we generalize the reliability-based risk assessment to account for inherent functional dependencies.;Furthermore, we develop a generic framework for maintainability-based risk assessment which can accommodate different types of software maintenance. First, we introduce and define maintainability-based risk assessment for software architecture. Within our assessment framework, we investigate the maintainability-based risk for the components of the system, and the effect of performing the maintenance tasks on these components. We propose a methodology for estimating the maintainability-based risk when considering different types of maintenance. As a proof of concept, we apply the proposed methodology on several case studies. Moreover, we automate the estimation of the maintainability-based risk assessment methodology