@conference {12106,
	title = {A Framework for Software Engineering Experimental Replications},
	booktitle = {Engineering of Complex Computer Systems, 2008. ICECCS 2008. 13th IEEE International Conference on},
	year = {2008},
	month = {2008/04/31/3},
	pages = {203 - 212},
	abstract = {Experimental replications are very important to the advancement of empirical software engineering. Replications are one of the key mechanisms to confirm previous experimental findings. They are also used to transfer experimental knowledge, to train people, and to expand a base of experimental evidence. Unfortunately, experimental replications are difficult endeavors. It is not easy to transfer experimental know-how and experimental findings. Based on our experience, this paper discusses this problem and proposes a Framework for Improving the Replication of Experiments (FIRE). The FIRE addresses knowledge sharing issues both at the intra-group (internal replications) and inter-group (external replications) levels. It encourages coordination of replications in order to facilitate knowledge transfer for lower cost, higher quality replications and more generalizable results.},
	keywords = {engineering, engineering;, evidence;experimental, experimental, Experiments;experimental, for, Framework, Improving, knowledge, of, replication, replication;software, sharing;software, the, transfer;knowledge},
	doi = {10.1109/ICECCS.2008.38},
	author = {Mendonca,M.G. and Maldonado,J.C. and de Oliveira,M.C.F. and Carver, J. and Fabbri,C.P.F. and Shull, F. and Travassos,G.H. and Hohn,E.N. and Basili, Victor R.}
}
@article {17798,
	title = {Optimal models of disjunctive logic programs: semantics, complexity, and computation},
	journal = {Knowledge and Data Engineering, IEEE Transactions on},
	volume = {16},
	year = {2004},
	month = {2004/04//},
	pages = {487 - 503},
	abstract = {Almost all semantics for logic programs with negation identify a set, SEM(P), of models of program P, as the intended semantics of P, and any model M in this class is considered a possible meaning of P with regard to the semantics the user has in mind. Thus, for example, in the case of stable models [M. Gelfond et al., (1988)], choice models [D. Sacca et al., (1990)], answer sets [M. Gelfond et al., (1991)], etc., different possible models correspond to different ways of "completing" the incomplete information in the logic program. However, different end-users may have different ideas on which of these different models in SEM(P) is a reasonable one from their point of view. For instance, given SEM(P), user U<sub>1</sub> may prefer model M<sub>1</sub> isin;SEM(P) to model M<sub>2</sub> isin;SEM(P) based on some evaluation criterion that she has. We develop a logic program semantics based on optimal models. This semantics does not add yet another semantics to the logic programming arena - it takes as input an existing semantics SEM(P) and a user-specified objective function Obj, and yields a new semantics Opt(P)_ sube; SEM(P) that realizes the objective function within the framework of preferred models identified already by SEM(P). Thus, the user who may or may not know anything about logic programming has considerable flexibility in making the system reflect her own objectives by building "on top" of existing semantics known to the system. In addition to the declarative semantics, we provide a complete complexity analysis and algorithms to compute optimal models under varied conditions when SEM(P) is the stable model semantics, the minimal models semantics, and the all-models semantics.},
	keywords = {complexity;, computational, disjunctive, function;, knowledge, LANGUAGE, Logic, minimal, model, nonmonotonic, objective, optimisation;, OPTIMIZATION, problems;, program, Programming, programming;, reasoning;, representation;, semantics;, stable, user-specified},
	isbn = {1041-4347},
	doi = {10.1109/TKDE.2004.1269672},
	author = {Leone,N. and Scarcello,F. and V.S. Subrahmanian}
}
@conference {15029,
	title = {Strategies for exploring large scale data},
	booktitle = {Parallel Architectures, Algorithms and Networks, 2004. Proceedings. 7th International Symposium on},
	year = {2004},
	month = {2004/05//},
	pages = {2 - 2},
	abstract = {We consider the problem of querying large scale multidimensional time series data to discover events of interest, test and validate hypotheses, or to associate temporal patterns with specific events. This type of data currently dominates most other types of available data, and will very likely become even more prevalent in the future given the current trends in collecting time series of business, scientific, demographic, and simulation data. The ability to explore such collections interactively, even at a coarse level, will be critical in discovering the information and knowledge embedded in such collections. We develop indexing techniques and search algorithms to efficiently handle temporal range value querying of multidimensional time series data. Our indexing uses linear space data structures that enable the handling of queries in I/O time that is essentially the same as that of handling a single time slice, assuming the availability of a logarithmic number of processors as a function of the temporal window. A data structure with provably almost optimal asymptotic bounds is also presented for the case when the number of multidimensional objects is relatively small. These techniques improve significantly over standard techniques for either serial or parallel processing, and are evaluated by extensive experimental results that confirm their superior performance.},
	keywords = {algorithms;, association;, asymptotic, bounds;, business, data, data;, database, databases;, demographic, discovery;, Indexing, indexing;, information, knowledge, large, linear, mining;, multidimensional, objects;, optimal, Parallel, pattern, processing;, query, querying;, range, scale, scientific, search, serial, series, series;, simulation, space, structure;, structures;, techniques;, temporal, TIME, value, very, window;},
	doi = {10.1109/ISPAN.2004.1300447},
	author = {JaJa, Joseph F.}
}
@article {12165,
	title = {User interface evaluation and empirically-based evolution of a prototype experience management tool},
	journal = {Software Engineering, IEEE Transactions on},
	volume = {29},
	year = {2003},
	month = {2003/09//},
	pages = {838 - 850},
	abstract = {Experience management refers to the capture, structuring, analysis, synthesis, and reuse of an organization{\textquoteright}s experience in the form of documents, plans, templates, processes, data, etc. The problem of managing experience effectively is not unique to software development, but the field of software engineering has had a high-level approach to this problem for some time. The Experience Factory is an organizational infrastructure whose goal is to produce, store, and reuse experiences gained in a software development organization. This paper describes The Q-Labs Experience Management System (Q-Labs EMS), which is based on the Experience Factory concept and was developed for use in a multinational software engineering consultancy. A critical aspect of the Q-Labs EMS project is its emphasis on empirical evaluation as a major driver of its development and evolution. The initial prototype requirements were grounded in the organizational needs and vision of Q-Labs, as were the goals and evaluation criteria later used to evaluate the prototype. However, the Q-Labs EMS architecture, data model, and user interface were designed to evolve, based on evolving user needs. This paper describes this approach, including the evaluation that was conducted of the initial prototype and its implications for the further development of systems to support software experience management.},
	keywords = {data, development;, empirical, EMS;, engineering;, evaluation;, experience, experience;, Factory;, interface, interfaces;, knowledge, management, management;, model;, models;, organization, performance, prototype, Q-Labs, re-engineering;, reusability;, reuse;, software, system;, systems, tool;, user},
	isbn = {0098-5589},
	doi = {10.1109/TSE.2003.1232288},
	author = {Seaman,C.B and Mendonca,M.G. and Basili, Victor R. and Kim,Y. M}
}
@article {12133,
	title = {Experience in implementing a learning software organization},
	journal = {Software, IEEE},
	volume = {19},
	year = {2002},
	month = {2002/06//may},
	pages = {46 - 49},
	abstract = {In an effort to improve software development and acquisition processes and explicitly reuse knowledge from previous software projects, DaimlerChrysler created a software experience center (SEC). The authors report on challenges the company faced in creating the SEC},
	keywords = {ACQUISITION, center;software, centres;project, DaimlerChrysler;explicit, development, experience, improvement;, improvement;automobile, industry;computer, knowledge, management;software, organization;previous, process, processes;software, projects;software, reuse;learning, software},
	isbn = {0740-7459},
	doi = {10.1109/MS.2002.1003453},
	author = {Schneider,K. and von Hunnius,J.-P. and Basili, Victor R.}
}
