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Systematic literature reviews (SLRs) are a major tool for supporting evidencebased software engineering. Adapting the procedures involved in such a review to meet the needs of software engineering and its literature remains an ongoing process. As part of this process of refinement, we undertook two case studies which aimed 1) to compare the use of targeted manual searches with broad automated searches and 2) to compare different methods of reaching a consensus on quality. For Case 1, we compared a tertiary study of systematic literature reviews published between which used a manual search of selected journals and conferences and a replication of that study based on a broad automated search. We found that broad automated searches find more studies than manual restricted searches, but they may be of poor quality. Researchers undertaking SLRs may be justified in using targeted manual searches if they intend to omit low quality papers, or they are assessing research trends in research methodologies. For Case 2, we analyzed the process used to evaluate the quality of SLRs. We conclude that if quality evaluation of primary studies is a critical component of a specific SLR, assessments should be based on three independent evaluators incorporating at least two rounds of discussion.

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When conducting a systematic literature review, researchers usually determine the relevance of primary studies on the basis of the title and abstract. However, experience indicates that the abstracts for many software engineering papers are of too poor a quality to be used for this purpose. A solution adopted in other domains is to employ structured abstracts to improve the quality of information provided. This study consists of a formal experiment to investigate whether structured abstracts are more complete and easier to understand than non-structured abstracts for papers that describe software engineering experiments. We constructed structured versions of the abstracts for a random selection of 25 papers describing software engineering experiments. The 64 participants were each presented with one abstract in its original unstructured form and one in a structured form, and for each one were asked to assess its clarity (measured on a scale of 1 to 10) and completeness (measured with a questionnaire that used 18 items). Based on a regression analysis that adjusted for participant, abstract, type of abstract seen first, knowledge of structured abstracts, 436 Empir Software Eng (2008) 13:435-468 software engineering role, and preference for conventional or structured abstracts, the use of structured abstracts increased the completeness score by 6.65 (SE 0.37, p < 0.001) and the clarity score by 2.98 (SE 0.23, p < 0.001). 57 participants reported their preferences regarding structured abstracts: 13 (23%) had no preference; 40 (70%) preferred structured abstracts; four preferred conventional abstracts. Many conventional software engineering abstracts omit important information. Our study is consistent with studies from other disciplines and confirms that structured abstracts can improve both information content and readability. Although care must be taken to develop appropriate structures for different types of article, we recommend that Software Engineering journals and conferences adopt structured abstracts.

This paper discusses the issues involved in evaluating a software bidding model. We found it difficult to assess the appropriateness of any model evaluation activities without a baseline or standard against which to assess them. This paper describes our attempt to construct such a baseline. We reviewed evaluation criteria used to assess cost models and an evaluation framework that was intended to assess the quality of requirements models. We developed an extended evaluation framework and an associated evaluation process that will be used to evaluate our bidding model. Furthermore, we suggest the evaluation framework might be suitable for evaluating other models derived from expertopinion based influence diagrams. q