Release notes

Abstract: This paper introduces ARENA (Automatic RElease Notes generAtor), an approach for the automatic generation of release notes. ARENA extracts changes from the source code, summarizes them, and integrates them with information from versioning systems and issue trackers. It was designed based on the manual analysis of 1,000 existing release notes. To evaluate the quality of the ARENA release notes, we performed three empirical studies involving a total of 53 participants (45 professional developers and 8 students). The results indicate that the ARENA release notes are very good approximations of those produced by developers and often include important information that is missing in the manually produced release notes.

Abstract: Release notes document corrections, enhancements, and, in general, changes that were implemented in a new release of a software project. They are usually created manually and may include hundreds of different items, such as descriptions of new features, bug fixes, structural changes, new or deprecated APIs, and changes to software licenses. Thus, producing them can be a time-consuming and daunting task. This paper describes ARENA ( A utomatic RE lease N otes gener A tor), an approach for the automatic generation of release notes. ARENA extracts changes from the source code, summarizes them, and integrates them with information from versioning systems and issue trackers. ARENA was designed based on the manual analysis of 990 existing release notes. In order to evaluate the quality of the release notes automatically generated by ARENA, we performed four empirical studies involving a total of 56 participants (48 professional developers and eight students). The obtained results indicate that the generated release notes are very good approximations of the ones manually produced by developers and often include important information that is missing in the manually created release notes.

Abstract: Release notes are an important source of information about a new software release. Such notes contain information regarding what is new, changed, and/or got fixed in a release. Despite the importance of release notes, they are rarely explored in the research literature. Little is known about the contained information, e.g., contents and structure, in release notes. To better understand the types of contained information in release notes, we manually analyzed 85 release notes across 15 different software systems. In our manual analysis, we identify six different types of information (e.g., caveats and addressed issues) that are contained in release notes. Addressed issues refer to new features, bugs, and improvements that were integrated in that particular release. We observe that most release notes list only a selected number of addressed issues (i.e., 6-26 % of all addressed issues in a release). We investigated nine different factors (e.g., issue priority and type) to better understand the likelihood of an issue being listed in release notes. The investigation is conducted on eight release notes of three software systems using four machine learning techniques. Results show that certain factors, e.g., issue type, have higher influence on the likelihood of an issue to be listed in release notes. We use machine learning techniques to automatically suggest the issues to be listed in release notes. Our results show that issues listed in all release notes can be automatically determined with an average precision of 84 % and an average recall of 90 %. To train and build the classification models, we also explored three scenarios: (a) having the user label some issues for a release and automatically suggest the remaining issues for that particular release, (b) using the previous release notes for the same software system, and (c) using prior releases for the current software system and the rest of the studied software systems. Our results show that the content of release notes vary between software systems and across the versions of the same software system. Nevertheless, automated techniques can provide reasonable support to the writers of such notes with little training data. Our study provides developers with empirically-supported advice about release notes instead of simply relying on adhoc advice from on-line inquiries.

Abstract: An example customized documentation generation apparatus is disclosed that generates documents relevant to a software update/upgrade of a particular process control system. A notes instrumentation module instruments general release notes for at least one of an update or an upgrade of a process control system to correlate the release notes with a general process control system configuration to produce instrumented notes. An upgrade assessment module determines configuration information for a particular process control system to provide default filter settings. An items of interest filter applies the default filter settings for the particular process control system to the instrumented notes to filter the instrumented notes and produce custom release notes for the particular process control system. The custom release notes are provided to a user to alert the user regarding potential effects of the update/upgrade on the particular process control system.