Integrating automated support for a software management cycle into the TAME system

Software managers are interested in the quantitative management of software quality, cost and progress. An integrated software management methodology, which can be applied throughout the software life cycle for any number purposes, is required. The TAME (Tailoring A Measurement Environment) methodology is based on the improvement paradigm and the goal/question/metric (GQM) paradigm. This methodology helps generate a software engineering process and measurement environment based on the project characteristics. The SQMAR (software quality measurement and assurance technology) is a software quality metric system and methodology applied to the development processes. It is based on the feed forward control principle. Quality target setting is carried out before the plan-do-check-action activities are performed. These methodologies are integrated to realize goal oriented measurement, process control and visual management. A metric setting procedure based on the GQM paradigm, a management system called the software management cycle (SMC), and its application to a case study based on NASA/SEL data are discussed. The expected effects of SMC are quality improvement, managerial cost reduction, accumulation and reuse of experience, and a highly visual management reporting system

Increasing U.S. Hard Red Winter Wheat Competitiveness in Latin American Markets

The United States wheat sector leadership in world markets is facing serious challenges. Canada, Australia, Argentina, the European Union (EU), and the Former Soviet Union (FSU) are growing contenders for international wheat markets. Wheat buyers´ concerns about quality specifications and its consistency have intensified without precedents in the last years. The study focuses on identifying the attributes that wheat buyers most value at the moment of purchase. The study will be done in two stages. The first stage will focus in estimating preferences from actual wheat transactions from different grain-sheds in the HRW growing area. The second stage will focus on the demand from Latin American millers and will estimate their attribute preference and elicit willingness to pay. The second stage will start with Mexican millers, given their importance for the HRW exports. A hedonic price model will be used for the first stage. The second part of the study will attempt to elicit miller´s preferences by using a self explicated approach. Expected results are that the "easy-to-measure attributes": test weight, and protein levels; and all functionality characteristics such as bake absorption, farinograph peak time, farinograph stability, alveograph p/l ratio will be the most valued by the wheat customers. We hypothesize that millers will be willing to pay a premium if those attributes are present in desirable levels. The information should provide insight into the efforts being made by wheat marketing agencies and the U.S. Wheat Associates to promote quality-based marketing of wheat to domestic and foreign millers. Discussion may also include the impacts of quality-based marketing on U.S. share of the world wheat market.International Relations/Trade,

Investigating Automatic Static Analysis Results to Identify Quality Problems: an Inductive Study

Background: Automatic static analysis (ASA) tools examine source code to discover "issues", i.e. code patterns that are symptoms of bad programming practices and that can lead to defective behavior. Studies in the literature have shown that these tools find defects earlier than other verification activities, but they produce a substantial number of false positive warnings. For this reason, an alternative approach is to use the set of ASA issues to identify defect prone files and components rather than focusing on the individual issues. Aim: We conducted an exploratory study to investigate whether ASA issues can be used as early indicators of faulty files and components and, for the first time, whether they point to a decay of specific software quality attributes, such as maintainability or functionality. Our aim is to understand the critical parameters and feasibility of such an approach to feed into future research on more specific quality and defect prediction models. Method: We analyzed an industrial C# web application using the Resharper ASA tool and explored if significant correlations exist in such a data set. Results: We found promising results when predicting defect-prone files. A set of specific Resharper categories are better indicators of faulty files than common software metrics or the collection of issues of all issue categories, and these categories correlate to different software quality attributes. Conclusions: Our advice for future research is to perform analysis on file rather component level and to evaluate the generalizability of categories. We also recommend using larger datasets as we learned that data sparseness can lead to challenges in the proposed analysis proces