Call for Papers

ABOUT: The PROMISE conference seeks verifiable and repeatable models that are useful for the implementation, evaluation, and management of software processes and projects. Such models relate to software development efforts (both in general or software development for specific domains such as telecom, finance, scientific applications, etc).

TOPICS: Our topics of interest include but are not limited to:

• Effort prediction models
• Defect prediction models
• Meta-analysis and generalizations of predictive models exploring certain questions (e.g., defect prediction)
• Replicated studies
• Predicting various intermediate or final outcomes of interest regarding business, team, human, people, process, and organizational aspects of software engineering
• Privacy and ethical issues in sharing and modeling
• Qualitative research guiding and informing the process of building future predictive models
• Instance-based models predicting outcomes by examining similarities to earlier experiences
• Industrial experience reports detailing the application of software technologies - processes, methods, or tools - and their effectiveness in industrial settings.
• Tools for software researchers that effectively gather and analyze data to support reproducible and verifiable research.

DATA: PROMISE 2011 will give the highest priority to empirical studies based on publicly available datasets. It is therefore encouraged, but it is not mandatory, that conference attendees contribute the data used in their analysis to the on-line PROMISE data repository. The repository currently holds 130 data sets, which can be used to repeat/confirm/refute/improve previous results.

PAPERS: Papers must not exceed 10 pages (including references). Submissions must be original work, not published or under review elsewhere. Accepted papers will be published in the ACM digital library.

SPECIAL ISSUE: Authors of selected papers from PROMISE'11 will be invited to submit extended versions to a special section in Information and Software Technology (Elsevier).

SUBMISSION: To submit, follow the instructions at http://promisedata.org/2011/submit.php