Information and Quality Assurance: An Unsolved, Perpetual Problem for Past and Future Generations

E very enterprise now lives and dies by the data stored on its computers and networks, and none can long survive if that data isn’t accurate and reliable. In addition to the damage that can come from the actual alteration of data, the impact on a company’s reputation can be substantial if customers are faced with unreliable, poor-quality products. Quality assurance (QA) and information assurance (IA) programs play crucial roles in protecting assets and developing trustworthy products and services. Many technical solutions and approaches are available to IT teams engaging in IA and QA, and certain broadly accepted principles apply across the board, but success generally depends on proper responses to issues that affect enterprises at local levels. Platform and application heterogeneity present one sort of challenge, and domainspecific requirements and legal issues add other layers of complexity throughout. A clear understanding of what you’re trying to achieve is thus key up front. The following theme articles present case studies and experience reports in several QA and IA initiatives and describe lessons learned that could benefit others facing similar challenges. Assurance and Trust This issue of IT Pro focuses on IA and QA in software development, but assurance is at least equally important for systems, security, and safety. Although people often use these concepts interchangeably, doing so is a mistake because they represent separate areas of concern, each with its own specific challenges. For example, systems assurance requires the ability to build assurance cases in which evidence and context are propagated upwardly to enable specific arguments that system-level assurance has been achieved. IA typically deals with confidence that certain data and information assets are secure and private. QA is a well-known field, particularly in areas such as the six-sigma manufacturing paradigm, which deals with defect-density rates (1 part in 1 million is defective, for instance). Athough six-sigma can be applied to software with some success, it’s better known in the physical, manufacturing arena, because software isn’t mass produced, as with hardware parts. Wiktionary.org lists the following among its definitions of assurance: Jeffrey Voas, SAIC Linda Wilbanks, US Dept. of Energy Guest editors’ introduction