SPRE elements have typical signals. For instance, “Problem” signals include

1. SPRE elements have typical signals. For instance, “Problem” signals include although, however, problem, difficult, only Moves also have typical signals. In abstracts, “Approach” signals include first, next, then, by __ing, method, [Passive] Be careful – there is no one-to-one association between signalling words and moves or SPRE elements. Lexical signals

2. Signalling through repetition Another type of signalling is repetition. “Repetition” includes Exact repetition (e.g., method, method) Repetition of the word root (e.g. method, methodical) Rewording (e.g., method, approach) Pronoun reference (e.g., method, this) In general, what does repetition signal?

3. Look at the abstract on leaf venation. Which phrases are “repeated” at least twice? Repeated phrases

4. Most Content-Based Image Retrieval systems use image features such as textures, colors, and shapes. However, in the case of a leaf image, it is not appropriate to rely on color or texture features only as such features are very similar in most leaves. In this paper, we propose a new and effective leaf image retrieval scheme. In this scheme, we first analyze leaf venation which we use for leaf categorization. We then extract and utilize leaf shape features to find similar leaves from the already categorized group in a leaf database. The venation of a leaf corresponds to the blood vessels in organisms. Leaf venations are represented using points selected by a curvature scale scope corner detection method on the venation image. The selected points are then categorized by calculating the density of feature points using a non-parametric estimation density. We show this technique's effectiveness by performing several experiments on a prototype system. Repeated phrases

5. Most Content-Based Image Retrieval systems use imagefeatures such as textures, colors, and shapes. However, in the case of a leaf image, it is not appropriate to rely on color or texture features only as such features are very similar in most leaves. In this paper, we propose a new and effective leafimage retrieval scheme. In this scheme, we first analyze leafvenation which we use for leaf categorization. We then extract and utilize leaf shape features to find similar leaves from the already categorized group in a leaf database. The venation of a leaf corresponds to the blood vessels in organisms. Leafvenations are represented using points selected by a curvature scale scope corner detection method on the venationimage. The selected points are then categorized by calculating the density of featurepoints using a non-parametric estimation density. We show this technique's effectiveness by performing several experiments on a prototype system. Repeated phrases

6. Key words can be used in titles The key words in the abstract are leaf8 image5 feature(s)5 we5 venation(s)4 points3 The title uses four of these key words: Utilizing venation features for efficient leaf image retrieval

7. Look at the abstract about software innovation. Which phrases occur three or more times? Can you think of a good title using some of those phrases? Exercise 1: Repeated phrases

8. Exercise 1: Repeated phrases To ensure smooth and successful transition of softwareinnovations to enterprise systems, it is critical to maintain properlevels of knowledge about the system configuration, the operational environment, and the technology in both existing andnew systems. We present a three-tier knowledge managementscheme through a systematic planning of actions spanning thetransition processes in levels from conceptual exploration toprototypedevelopment, experimentation, and product evaluation.The three-tier scheme is an integrated effort for bridging thedevelopment and operation communities, maintaining stability tothe operational performance, and adapting swiftly to softwaretechnology innovations. The scheme combines experiences ofacademic researches and industrial practitioners to providenecessary technical expertise and qualifications for knowledgemanagement in software engineering support (SES) processes.

9. A three-tier knowledge management scheme for software engineering support and innovation To ensure smooth and successful transition of softwareinnovations to enterprise systems, it is critical to maintain properlevels of knowledge about the system configuration, the operational environment, and the technology in both existing andnew systems. We present a three-tierknowledgemanagementscheme through a systematic planning of actions spanning thetransition processes in levels from conceptual exploration toprototypedevelopment, experimentation, and product evaluation.The three-tier scheme is an integrated effort for bridging thedevelopment and operation communities, maintaining stability tothe operational performance, and adapting swiftly to softwaretechnology innovations. The scheme combines experiences ofacademic researches and industrial practitioners to providenecessary technical expertise and qualifications for knowledgemanagement in software engineering support (SES) processes.

10. Look at the abstract about effort estimation. Which phrases occur three or more times? Can you think of a good title using some of those phrases? Is this a descriptive or informative abstract? Make a table with three columns: moves, SPRE steps and text Label the move structure. Label the SPRE structure Exercise 2: mixed analysis

11. Exercise 2: Repeated phrases Expert judgment-based effort estimation of software development work is partly based on non-mechanical and unconscious processes. For this reason, a certain degree of intra-person inconsistency is expected, i.e., the same information presented to the same individual at different occasions sometimes lead to different effort estimates. In this paper, we report from an experiment where seven experienced software professionals estimated the same sixty software development tasks over a period of three months. Six of the sixty tasks were estimated twice. We found a high degree of inconsistency in the software professionals’ effort estimates. The mean difference of the effort estimates of the same task by the same estimator was as much as 71%. The correlation between the corresponding estimates was 0.7. Highly inconsistent effort estimates will, on average, be inaccurate and difficult to learn from. It is consequently important to focus estimation process improvement on consistency issues and thereby contribute to reduced budget-overruns, improved time-to-market, and better quality software .

12. Exercise 2: Repeated phrases Inconsistency of expert judgment-based estimates of software development Expert judgment-based effortestimation of software development work is partly based on non-mechanical and unconscious processes. For this reason, a certain degree of intra-person inconsistency is expected, i.e., the same information presented to the same individual at different occasions sometimes lead to different effortestimates. In this paper, we report from an experiment where seven experienced software professionals estimated the same sixty software development tasks over a period of three months. Six of the sixty tasks were estimated twice. We found a high degree of inconsistency in the software professionals’ effortestimates. The mean difference of the effortestimates of the same task by the same estimator was as much as 71%. The correlation between the corresponding estimates was 0.7. Highly inconsistenteffortestimates will, on average, be inaccurate and difficult to learn from. It is consequently important to focus estimation process improvement on consistency issues and thereby contribute to reduced budget-overruns, improved time-to-market, and better quality software.

13. Exercise 2: Repeated phrases Inconsistency of expert judgment-based estimates of software development