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Query-based Test Generation for Database Applications

Query-based Test Generation for Database Applications. David Chays, Adelphi University John Shahid , Polytechnic University Phyllis G. Frankl , Polytechnic University. Outline. Issues in Testing DB Applications AGENDA Overview Generating Test Generation Queries

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Query-based Test Generation for Database Applications

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  1. Query-based Test Generation for Database Applications David Chays, Adelphi University John Shahid, Polytechnic University Phyllis G. Frankl, Polytechnic University DBTest '08, Vancouver, BC

  2. Outline • Issues in Testing DB Applications • AGENDA Overview • Generating Test Generation Queries • Conclusions and Future Work

  3. ssnname 001-00-0356 Johnson 012-34-5678 Smith 036-54-5555 Jones 051-88-9911 Blake Table E Relational databases • Data is viewed as a collection of relations • relation schema • relation (relation state) • Tables, tuples, attributes, constraints • for example, • create tableE(ssnchar(11)primary key, • namechar(25)not null)

  4. DB Application • SQL: declarative language for defining and manipulating databases. Includes statements to create and modify schema and to select, insert, delete, update table elements that satisfy certain conditions • Application typically written in high level language host program with SQL statements embedded or dynamically generated • SQL statements passed to DBMS for execution and results returned to host program • Communication via host variables

  5. Aspects of Correctness • Does the DBMS perform all operations correctly? • Is concurrent access handled correctly? • Is the system fault-tolerant? • Is the system secure? • ... • Does the application program behave as intended?

  6. function imperative nature function Semi-declarative nature Traditional vs. DB programs input DB state input output output DB state

  7. DB Application Testing Goal • Select “interesting” DB states along with user inputs that exercise “interesting” behavior • Cover wide variety of situations that could arise in practice • Do so in a way that facilitates checking of output to user and resulting DB state

  8. Current Practice • Testing is largely manual • Limited tool support • Database state generation • DBUnit – extension of JUnit with support for importing XML descriptions of database state and for checking results of individual tests supplied by tester • AGENDA goal: More thorough automation of entire test process for DB applications

  9. AGENDA Parser State Generator Input Generator State Validator Output Validator AGENDA DB

  10. AGENDA System Overview • Inputs • database schema • application source code • Sample values, divided into data groups • test heuristics • info about expected behavior of test cases • Constraints on expected database state and outputs • Outputs • Initial database state • Test cases • Hooks for validation of resulting DB state and output • Error reports when tests violate constraints

  11. AGENDA System Overview • Inputs • database schema • application source code • Sample values, divided into data groups • test heuristics • info about expected behavior of test cases • Constraints on expected database state and outputs • Outputs • Initial database state • Test cases • Hooks for validation of resulting DB state and output • Error reports when tests violate constraints

  12. Student Registration Application • Tables: • Person (id, name, passwd, type) • Class (crsCode, credit, enrollment, maxEnrollment, profId) • Transcript (sid, code, grade) • who’s registered for what and their grades • Constraints in schema: • primary keys (possibly composite) • foreign key • Transcript.sid references Person.id • Transcript.code references Class.crsCode

  13. Sample data values and groups Id: --choice_name: Student 112 252 334 121 013 311 ---- --choice_name: Faculty 888 887 CrsCode: --choice_name: Undergrad CS101 EL101 CS110 ---- --choice_name: Grad EL501 CS608 CS912 Name: Deng David Phyllis Gleb Eric Wang

  14. Sample output of State Generator Table Transcript Table Person Table Class

  15. Input Generator • Each combination of data groups can serve as a test template for test cases. • For each input parameter (input host variable) find info about data groups for the associated attribute along with candidate values in the Agenda DB. • Selection of arbitrary elements of data groups does not work • SELECT sid FROM transcript WHERE code = :hv1 and grade = :hv2 • Choosing hv1 = CS912, hv2 = ‘A’ leads to no rows that satisfy the where clause • OK for testing robustness, but one also wants test cases that test more typical behavior • Original approach: Combination of sample values from relevant data groups + automatic generation and execution of SELECT statements to extract related attribute values • New approach: more general, flexible, hopefully more effective

  16. Sample Code (Class Registration) BEGIN DECLARE SECTION; • int enroll, maxenroll ; • char sid[20], code [10]; END DECLARE SECTION; void register(char[] sid, char[] code) { 3) EXEC SQL SELECT enrollment, maxEnrollment INTO :enroll, :maxEnroll FROM Class WHERE crsCode = :code 4) if (enroll < maxEnroll) { 5) EXEC SQL UPDATE Class SET enrollment = :enroll + 1 WHERE crsCode = :code ; • EXEC SQL INSERT INTO TRANSCRIPT (sid, code) VALUES (:sid, :code); } // end if 7) COMMIT; } // end register transaction

  17. Approach • Test template • id: student • course code: undergrad • General approach: generate a query to select values of these parameters that correspond to tuples in the populated DB representing these data groups • Use auxiliary data: parameter_value_recs table

  18. Table parameter_value_recs

  19. SELECT enrollment, maxEnrollment INTO :enroll, :maxEnroll FROM Class WHERE crsCode = :code SELECT

  20. SELECT enrollment, maxEnrollment INTO :enroll, :maxEnroll FROM Class WHERE crsCode = :code SELECT temp1

  21. SELECT enrollment, maxEnrollment INTO :enroll, :maxEnroll FROM Class WHERE crsCode = :code SELECT temp1 FROM (

  22. SELECT enrollment, maxEnrollment INTO :enroll, :maxEnroll FROM Class WHERE crsCode = :code SELECT temp1 FROM ( (SELECT value AS temp1 FROM parameter_value_recs WHERE parameter_name = ‘:code’ AND group_name = ‘Undergrad’)

  23. SELECT enrollment, maxEnrollment INTO :enroll, :maxEnroll FROM Class WHERE crsCode = :code SELECT temp1 FROM ( (SELECT value AS temp1 FROM parameter_value_recs WHERE parameter_name = ‘:code’ AND group_name = ‘Undergrad’) ) WHERE EXISTS ( SELECT * FROM

  24. SELECT enrollment, maxEnrollment INTO :enroll, :maxEnroll FROM Class WHERE crsCode = :code SELECT temp1 FROM ( (SELECT value AS temp1 FROM parameter_value_recs WHERE parameter_name = ‘:code’ AND group_name = ‘Undergrad’) ) WHERE EXISTS ( SELECT * FROM Class

  25. SELECT enrollment, maxEnrollment INTO :enroll, :maxEnroll FROM Class WHERE crsCode = :code SELECT temp1 FROM ( (SELECT value AS temp1 FROM parameter_value_recs WHERE parameter_name = ‘:code’ AND group_name = ‘Undergrad’) ) WHERE EXISTS ( SELECT * FROM Class WHERE crsCode = temp1 )

  26. SELECT enrollment, maxEnrollment INTO :enroll, :maxEnroll FROM Class WHERE crsCode = :code SELECT temp1 FROM ( (SELECT value AS temp1 FROM parameter_value_recs WHERE parameter_name = ‘:code’ AND group_name = ‘Undergrad’) ) WHERE EXISTS ( SELECT * FROM Class WHERE crsCode = temp1 )

  27. UPDATE Class SET enrollment = :enroll + 1 WHERE crsCode = :code SELECT temp1 FROM ( (SELECT value AS temp1 FROM parameter_value_recs WHERE parameter_name = ‘:code’ AND group_name = ‘Undergrad’) ) WHERE EXISTS ( SELECT * FROM Class WHERE crsCode = temp1 )

  28. INSERT INTO Transcript (sid, code) VALUES (:sid, :code) SELECT

  29. INSERT INTO Transcript (sid, code) VALUES (:sid, :code) SELECT temp1, temp2

  30. INSERT INTO Transcript (sid, code) VALUES (:sid, :code) SELECT temp1, temp2 FROM (

  31. INSERT INTO Transcript (sid, code) VALUES (:sid, :code) SELECT temp1, temp2 FROM ( (SELECT value AS temp1 FROM parameter_value_recs WHERE parameter_name = ‘:sid’ AND group_name = ‘Student’)

  32. INSERT INTO Transcript (sid, code) VALUES (:sid, :code) SELECT temp1, temp2 FROM ( (SELECT value AS temp1 FROM parameter_value_recs WHERE parameter_name = ‘:sid’ AND group_name = ‘Student’) CROSS_JOIN (SELECT value AS temp2 FROM parameter_value_recs WHERE parameter_name = ‘:code’ AND group_name = ‘Undergrad’)

  33. INSERT INTO Transcript (sid, code) VALUES (:sid, :code) SELECT temp1, temp2 FROM ( (SELECT value AS temp1 FROM parameter_value_recs WHERE parameter_name = ‘:sid’ AND group_name = ‘Student’) CROSS_JOIN (SELECT value AS temp2 FROM parameter_value_recs WHERE parameter_name = ‘:code’ AND group_name = ‘Undergrad’) ) WHERE NOT EXISTS (SELECT sid, code FROM Transcript WHERE sid = temp1 and code = temp2)

  34. INSERT INTO Transcript (sid, code) VALUES (:sid, :code) SELECT temp1, temp2 FROM ( (SELECT value AS temp1 FROM parameter_value_recs WHERE parameter_name = ‘:sid’ AND group_name = ‘Student’) CROSS_JOIN (SELECT value AS temp2 FROM parameter_value_recs WHERE parameter_name = ‘:code’ AND group_name = ‘Undergrad’) ) WHERE NOT EXISTS (SELECT sid, code FROM Transcript WHERE sid = temp1 and code = temp2) AND EXISTS (SELECT id FROM Person WHERE id = temp1)

  35. INSERT INTO Transcript (sid, code) VALUES (:sid, :code) SELECT temp1, temp2 FROM ( (SELECT value AS temp1 FROM parameter_value_recs WHERE parameter_name = ‘:sid’ AND group_name = ‘Student’) CROSS_JOIN (SELECT value AS temp2 FROM parameter_value_recs WHERE parameter_name = ‘:code’ AND group_name = ‘Undergrad’) ) WHERE NOT EXISTS (SELECT sid, code FROM Transcript WHERE sid = temp1 and code = temp2) AND EXISTS (SELECT id FROM Person WHERE id = temp1) AND EXISTS (SELECT crsCode FROM Class WHERE crsCode = temp2)

  36. INSERT INTO Transcript (sid, code) VALUES (:sid, :code) SELECT temp1, temp2 FROM ( (SELECT value AS temp1 FROM parameter_value_recs WHERE parameter_name = ‘:sid’ AND group_name = ‘Student’) CROSS_JOIN (SELECT value AS temp2 FROM parameter_value_recs WHERE parameter_name = ‘:code’ AND group_name = ‘Undergrad’) ) W HERE NOT EXISTS (SELECT sid, code FROM Transcript WHERE sid = temp1 and code = temp2) AND EXISTS (SELECT id FROM Person WHERE id = temp1) AND EXISTS (SELECT crsCode FROM Class WHERE crsCode = temp2)

  37. What is the result? Table Transcript Table Person Table Class Test Cases (112, CS101) (112, EL101) (252, EL101) (311, CS101)

  38. Status of Test Generation Query Generator • Implemented • Automatically generates test generation queries given info about application unit’s SQL statements and parameters • Parsing application for useful test information • Working on automating this for Java programs

  39. Initial evaluation • 5 transactions of TPC-C Benchmark • Produced Type A test cases that caused all 5 transactions to commit • Current work: How effective are these tests? • Seeded faults in the transactions • If transaction commits, check specification violation • If transaction does not commit, this means the test case was not Type A or there was a bug • Initial results on error-seeded versions • Some transactions identified as buggy but most committed with no specification violation

  40. Conclusions • Interplay between input parameters and DB state, and SQL statements under test • Integration, flexibility • Test template • Type A inputs • Non-empty result sets • Honoring constraints in updates

  41. Ongoing and Future Work • Improve State Generator • Experiment • Evaluate effectiveness and performance • Complex manipulation of host variables by host program • Symbolic execution • Type A and type B test cases • Other kinds of test templates • Further automate and integrate Java static analysis tools

  42. Related Work • Willmor and Embury, “An intensional approach to the specification of test cases for database applications”, ICSE 2006 • Binnig et al, “Reverse query processing”, ICDE 2007 • Binnig et al, “Qagen: generating query-aware test databases”, ACM SIGMOD 2007. • Emmi et al, “Dynamic test input generation for database applications”, ISSTA 2007.

  43. Previous work on AGENDA • “A Framework for Testing Database Applications”, ISSTA 2000 • Earlier version of AGENDA System was demonstrated at ASE03/ICSE03 • “An AGENDA for testing relational database applications”, Journal of Software Testing, Verification and Reliability, Mar 2004. • “Testing Database Transaction Concurrency”, International Conference on Automated Software Engineering 2003 • “Testing Web Database Applications”, TAV-WEB workshop, ACM SIGSOFT Notes, Sept 2004 • “Testing Database Transaction with AGENDA”, International Conference on Software Engineering 2005

  44. Questions? chays@adelphi.edu

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