http://www.computer.org/tse The IEEE Transactions on Software Engineering is an archival journal published monthly. We are interested in well-defined theoretical results and empirical studies that have potential impact on the construction, analysis, or management of software. The scope of this Transactions ranges from the mechanisms through the development of principles to the application of those principles to specific environments. Since the journal is archival, it is assumed that the ideas presented are important, have been well analyzed, and/or empirically validated and are of value to the software engineering research or practitioner community. Specific topic areas include: a) development and maintenance methods and models, e.g., techniques and principles for the specification, design, and implementation of software systems, including notations and process models; b) assessment methods, e.g., software tests and validation, reliability models, test and diagnosis procedures, software redundancy and design for error control, and the measurements and evaluation of various aspects of the process and product; c) software project management, e.g., productivity factors, cost models, schedule and organizational issues, standards; d) tools and environments, e.g., specific tools, integrated tool environments including the associated architectures, databases, and parallel and distributed processing issues; e) system issues, e.g., hardware-software trade-off; and f) state-of-the-art surveys that provide a synthesis and comprehensive review of the historical development of one particular area of interest. en-us Mon, 20 May 2013 10:00:04 GMT http://csdl.computer.org/common/images/logos/tse.gif List of recently published journal articles http://www.computer.org/tse http://doi.ieeecomputersociety.org/10.1109/TSE.2012.28 This paper provides a systematic meta-analysis of 27 studies that investigate the impact of Test-Driven Development (TDD) on external code quality and productivity. The results indicate that, in general, TDD has a small positive effect on quality but little to no discernible effect on productivity. However, subgroup analyses have found both the quality improvement and the productivity drop to be much larger in industrial studies in comparison with academic studies. A larger drop of productivity was found in studies where the difference in test effort between the TDD and the control group's process was significant. A larger improvement in quality was also found in the academic studies when the difference in test effort is substantial, however, no conclusion could be derived regarding the industrial studies due to the lack of data. Finally, the influence of developer experience and task size as moderator variables was investigated, and a statistically significant positive correlation was found between task size and the magnitude of the improvement in quality. http://doi.ieeecomputersociety.org/10.1109/TSE.2012.28 http://doi.ieeecomputersociety.org/10.1109/TSE.2013.21 This paper proposes using a simulation model of software testing to assess the cost effectiveness of test effort allocation strategies based on fault prediction results. The simulation model estimates the number of discoverable faults with respect to the given test resources, the resource allocation strategy, a set of modules to be tested, and the fault prediction results. In a case study applying fault prediction of a small system to acceptance testing in the telecommunication industry, results from our simulation model showed that the best strategy was to let the test effort be proportional to "the number of expected faults in a module x log(module size)". By using this strategy with our best fault prediction model, the test effort could be reduced by 25% while still detecting as many faults as were normally discovered in testing, although the company required about 6% of the test effort for metrics collection and modeling. The simulation results also indicate that the lower bound of acceptable prediction accuracy is around .78 in terms of an effort-aware measure, Norm(Popt). The results indicate that reduction of the test effort can be achieved by fault prediction only if the appropriate test strategy is employed with a high enough fault prediction accuracy. http://doi.ieeecomputersociety.org/10.1109/TSE.2013.21 http://doi.ieeecomputersociety.org/10.1109/TSE.2013.12 Reading reference documentation is an important part of programming with APIs. Reference documentation complements the API by providing information not obvious from the API syntax. To improve the quality of reference documentation and the efficiency with which the relevant information it contains can be accessed, we must first understand its content. We report on a study of the nature and organization of knowledge contained in the reference documentation of the hundreds of APIs provided as part of two major technology platforms: Java SDK 6 and .NET 4.0. Our study involved the development of a taxonomy of knowledge types based on grounded methods and independent empirical validation. Seventeen trained coders used the taxonomy to rate a total of 5574 randomly-sampled documentation units to assess the knowledge they contain. Our results provide a comprehensive perspective on the patterns of knowledge in API documentation: observations about the types of knowledge it contains, and how this knowledge is distributed throughout the documentation. The taxonomy and patterns of knowledge we present in this paper can be used to help practitioners evaluate the content of their API documentation, better organize their documentation, and limit the amount of low-value content. They also provides a vocabulary that can help structure and facilitate discussions about the content of APIs. http://doi.ieeecomputersociety.org/10.1109/TSE.2013.12